Surgical site infections (SSIs) are a major concern in public healthcare, leading to increased morbidity, pro-longed hospital stays length, and significant economic costs. Understanding the epidemiology and risk fac-tors of SSIs is crucial for developing effective prevention and management strategies. In the last century, CDC ‘s HICPAC improved a bundle for prevention of HAIs based on the use of aseptic procedures, disin-fection of the skin and correct use of antibiotics for SSIs. In our country, Gelli-Bianco law introduced the national health guidelines system that include the prophylaxis antibiotic therapy pre- and post-surgery. The aim of our study is to evaluate adherence and appropriateness of the use of antibiotic-preoperative prophylaxis in a province of southern Italy and to identify risk factors that may influence the development of an SSI. The study found many statistically significant associations among the factors examined, i.e. the timing of administration adherent to guidelines, with 47% of the analyzed files administering antibiotics within 60 min before the intervention and 62.7% using intravenous administration.

Myasthenia gravis (MG) is a disease characterized by typical clinical and immunopathogenic pe-culiarities, which correlate with age and sex/gender. Accordingly, MG patients show thymic al-terations and auto-antibodies productions, that can be the expression of a different pathogenetic mechanism related to age and gender. This determines, in relation to age at and sex/gender, a dif-ferent MG onset, prognosis, and outcome. Therefore, diverse MG forms can be identified, classi-fied, and characterized in relation to their different features, and precisely there are early onset and late-onset forms of MG. It has been hypothesized that the cause of appearance the two diverse forms of MG can be ascribed mainly to the diverse genetic and epigenetic factors. In this narrative review, we will analyze and discuss about the interplay of age- and sex-related factors (i.e. genet-ic and epigenetic factors) related to two different MG forms and how they contribute to their di-verse pathogenesis.

Dynamic optical structural color is always desired in various display applications and usually involves active materials. Full-color generation, especially bi-directional full-color generation in both reflective and transmissive modes, without any active materials included has been rarely investigated. Herein, we demonstrate a scheme of bi-directional full-color generation based on a plasmonic metasurface modulated by rotation of the polarization angle of the incident light without varying the geometry and the optical properties of the materials and the environment where the metasurface resides. The metasurface unit cell consists of plasmonic modules aligning in three directions and is patterned in a square array. The metasurface structural color device generates full colors in both reflection and transmission. Based on the proposed polarization-dependent structural color, information encoding of three multiplexed animal images and quick-responsive (QR) codes is demonstrated to verify the efficient information encoding and decoding of the proposed scheme. The animals can be seen under different polarization incidence and the QR codes can be successfully decoded by the polarization rotation in transmission. The proposed bi-directional full-color generation metasurface has great potential in applications such as kaleidoscope generation, anti-counterfeiting, dynamic color display, and optical information encoding.

Non-coding RNAs have been described as crucial regulators of gene expression and guards for cellular homeostasis. Some recent papers are focused on vault RNAs, one of the classes of non-coding RNA, and their role in cell proliferation, tumorigenesis, apoptosis, cancer response to therapy, and autophagy, which made them potential therapy targets in oncology. In the human genome, four vault RNA paralogues can be distinguished. They are associated with vault complexes, considered the largest ribonucleoprotein complex. The protein part of these complexes consists of a major vault protein (MVP) and two minor vault proteins (vPARP and TEP1). The name of the complex, as well as vault RNA, comes from the hollow barrel-shaped structure that reminds a vault. Their sequence and structure are highly evolutionary conserved and show many similarities in comparison with different species, but vault RNAs show various roles. Vaults were discovered in 1986, and their functions remained unclear for many years. Although not much is known about their contribution to cell metabolism, it has become clear that vault RNAs are involved in various processes and pathways associated with cancer progression and modulating cell functioning in normal and pathological stages. In this review, we discuss known functions of the human vault RNAs in the context of cellular metabolism, emphasizing processes related to cancer and cancer therapy efficacy.

Background: This study assesses the effects of the ‘Radiant’ image enhancement technique on fetal nuchal translucency (NT) measurements during first trimester sonographic ex-ams. Methods: A retrospective analysis of 263 ultrasound images of first trimester midsagittal sections was conducted. NT measurements were obtained using a semi-automatic tool. Statistical methods were applied to compare NT measurements with and without ‘Radi-ant’ enhancement. An in-vitro setup with predefined line distances provided additional data. Results: Incremental increases in NT measurements were observed with varying levels of ‘Radiant’ application: An average increase of 0.19 mm with ‘Radiant min’, 0.24 mm with ‘Radiant mid’ and 0.30 mm with ‘Radiant max.’ The in-vitro results supported these findings, showing consistent effects on line thickness and measurement accuracy, with the smallest mean deviation occurring at the ‘Radiant mid’ setting. Conclusions: ‘Radiant’ image enhancement leads to significant increases in NT measure-ments. To avoid systematic biases in clinical assessments, it is advisable to disable ‘Radi-ant’ during NT measurement procedures. Further studies are necessary to corroborate these findings and to consider updates to the NT reference tables based on this technology.

Deep Neutral Networks (DNNs) were initially proposed towards the midst of the 20th century, motivated by the neural structure and mechanism of the human brain. Thanks to major ad-vancements in computational resources, during the past decade DNN-based systems have demonstrated unprecedented performance in terms of accuracy and speed. However, recent work has shown that such models may not be sufficiently robust during the inference process. Furthermore, due to the data-driven learning nature of DNNs, designing interpretable and gen-eralizable networks is a major challenge, especially in critical applications, such as medical Computer Aided Diagnostics (CAD) and other medical imaging tasks, including classification, regression and reconstruction. Within this context, a line of physics-driven approaches for deep learning has recently emerged, aimed at improving the stability and generalization capacity of DNNs for medical imaging applications. In this paper, we review recent work focused on phys-ics-driven or prior-information learning for a variety of imaging modalities and medical applica-tions. We discuss how the inclusion of domain-related knowledge into the learning process and networks’ design supports their stability and generalization capability. In addition, we highlight current and future challenges within this scope.

Diffusion magnetic resonance imaging (dMRI) is an imaging technique that provides information on the microstructural organization of biological tissue. dMRI allows for non-invasive visualization and quantitative assessment of white matter architecture in the brain by characterizing restrictions on the random motion of water molecules. Ultra-high field MRI scanners, such as those operating at 7 Tesla (7T) or higher, can boost signal-to-noise ratio (SNR) to improve dMRI compared with what is attainable at conventional field strengths such as 3T or 1.5T. However, at 7T wavelength effects cause lower transmit magnetic field efficiency in the human brain, mainly in the posterior fossa region, manifesting as signal dropouts in this region. Recently, we reported a simple approach of using a wireless radiofrequency (RF) surface array to improve transmit efficiency and signal sensitivity at 7T. Here we demonstrate the feasibility and effectiveness of using this RF enhancer for in-vivo dMRI at 7T. The use of the RF enhancer can effectively recover signal dropouts in the regions with intrinsically lower SNR such as cerebellum, leading to a better depiction of principal fiber orientations and enhanced visualization of extended tracts to the brainstem and pons enabling more comprehensive delineation of the full white matter architecture.

Extremely low-frequency electromagnetic fields (ELF-EMF) are ubiquitous in industrial-11 ized environments due to the continuous use of electrical devices. Our previous studies demon-12 strated ELF-EMF affects muscle cells by modulating oxidative stress and enhancing myo-genesis. 13 This pilot study investigated these effects on skeletal muscles of sedentary adult mice, assessing 14 physiological responses to ELF-EMF exposure and potential modulation by antioxidant supplemen-15 tation. Male C57BL/6 mice were exposed to ELF-EMF (0.1 or 1.0 mT) 1 hour/day up to 5 weeks, and 16 fed a standard diet without or with N-acetyl-cysteine (NAC). Results showed transient increases in 17 muscle strength (after 2-weeks’ exposure at 1.0 mT), potentially linked to muscle fiber recruitment 18 and activation, revealed by higher PAX7 and MyH expression levels. After ELF-EMF exposure, ox-19 idative status assessment revealed transient increases in expression levels of SOD1 and catalase en-20 zymes, in total antioxidant capacity and in protein carbonyl levels, marker of oxidative damage. 21 These effects were partially reduced by NAC. In conclusion, ELF-EMF exposure affects skeletal 22 muscle physiology and NAC supplementation partially mitigates these effects, highlighting the 23 complex interactions between ELF-EMF and antioxidant pathways in vivo. Further investigations 24 on ELF-EMF as a therapeutic modality for muscle health are necessary.

Barrett’s esophagus (BE) is a known precursor to Esophageal Adenocarcinoma (EAC). Guidelines recommend BE screening in populations with multiple risk factors, for which non-endoscopic esophageal cell collection with biomarker testing is considered an acceptable alternative to esophagogastroduodenoscopy (EGD). This study presents analytical validation of EsoGuard® (EG), a two gene DNA methylation biomarker assay, in esophageal cell samples collected with the 510(k)-cleared, swallowable EsoCheck® (EC) device. EG is a Next Generation Sequencing (NGS) assay that evaluates methylated Vimentin (VIM) and Cyclin A1 (CCNA1) genes, clinically validated biomarkers for detection of BE and EAC. The studies were conducted according to standards of College of American Pathology (CAP), Clinical Laboratory Improvement Amendments (CLIA), and New York (NY) state requirements for analytical validation of molecular assays. Comparison to Sanger sequencing showed EG was 100% accurate at all 31 CpG sites evaluated by the assay. Analytical sensitivity, specificity and accuracy of the assay was 89%, 100% and 96% respectively. Intra- and inter-assay precision was 100%. Limit of detection (LOD) was 1 in 400 methylated cells and reference range was 84%. In summary, EsoGuard is a robust DNA methylation test to detect BE with high accuracy, repeatability, and reproducibility in samples collected using the EsoCheck device.

Alzheimer’s disease (AD) is a progressive irreversible neurodegenerative disorder that represents a major global public health concern. Traditionally, AD is diagnosed using cerebrospinal fluid biomarker analysis or brain imaging modalities. Recently, less burdensome, more widely available blood biomarker (BBM) assays for amyloid-beta (Aβ42/40) and phosphorylated-tau concentrations have been found to accurately identify the presence/absence of brain amyloid plaques and tau tangles and have helped to streamline AD diagnosis. However, few BBMs have been rigorously analytically validated. Herein, we report the analytical validation of a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying plasma phosphorylated-tau217 (p-tau217) and non-phosphorylated-tau217 (np-tau217) peptide concentrations. We combined the p-tau217/np-tau217 concentrations ratio (%p-tau217) and the previously validated LC-MS/MS assay for plasma Ab42/40 into a new multiple analyte blood test and algorithm (PrecivityAD2™) that identifies brain amyloid status based on brain amyloid positron emission tomography. We found: (a) the %p-tau217 assay is precise, accurate, sensitive, linear over a wide analytical measurement range, and free from carryover and interference; (b) the pre-analytical specimen collection, processing, storage and shipping conditions that maintain plasma tau peptide stability; and (c) using the measured analytical imprecision for plasma Aβ42/40 and p-tau217/np-tau217 levels in a worst-case scenario model, the PrecivityAD2 test algorithm for amyloid pathology classification changed for only 3.5% of participants from brain amyloid positive to negative, or negative to positive. The plasma sample preparation and LC-MS/MS methods underlying the PrecivityAD2 test are suitable for use in the clinical laboratory and valid for the test’s intended purpose: to aid in the diagnostic evaluation of individuals aged 55 and older with signs or symptoms of mild cognitive impairment or dementia.

Some peptide-based drugs including oxytocin, vasopressin, ziconotide, pramlintide, nesiritide, and octreotide, contain one intramolecular disulfide bonds. A novel and reusable monodispersed silica nanosphere-supported Pt(IV) complex (SiO2@TPEA@Pt(IV)) was synthesized via a four-step procedure and used for formation of intramolecular disulfide bonds in peptides. TEM and chemical mapping results for the Pt(II) intermediates and for SiO2@TPEA@Pt(IV) show that the silica nanospheres possess a monodisperse spherical structure and contain uniformly distributed Si, O, C, N, Cl, and Pt. The valence state of Pt on the silica nanospheres was characterized by XPS. The Pt(IV) loaded on SiO2@TPEA@Pt(IV) was 0.15 mmol/g, as determined by UV-vis spectrometry. Formation of intramolecular disulfides in six dithiol-containing peptides of variable lengths by use of SiO2@TPEA@Pt(IV) was investigated and the relative oxidation yields were determined by HPLC. In addition, peptide 1 (Ac-CPFC-NH2) was utilized to study the reusability of SiO2@TPEA@Pt(IV). No significant decrease in the relative oxidation yield was observed after ten reaction cycles. Moreover, the structure of SiO2@TPEA@Pt(IV) after being used ten cycles was determined to be similar to its initial one, demonstrating the cycling stability of the complex.

Juvenile idiopathic arthritis (JIA) is a disease with unknown causes within all forms of arthritis in children under 16 years of age. The diagnosis is made when another joint pathology is excluded. Difficulties in early and differential diagnosis lead to the rapid disability of patients and an unfavourable life prognosis. Therefore, timely diagnosis is necessary to prevent irreversible damage to the joints and preserve their function. Due to the widespread use of new technologies, modern multimodal imaging has gained recognition, which includes X-ray, ultrasound, and MRI. The combination of methods plays a key role in confirming the diagnosis, monitoring disease activity, prognosis during the course, and outcome in children with JIA. Each method has its own advantages and disadvantages. The introduction of the method of passive microwave radiometry (MWR), in combination with other imaging methods, makes it possible to expand the possibilities of screening the disease in the preclinical and early clinical phases.

Laser Photoacoustic Spectrometers (LPAS), which provide photoacoustic spectra for detecting food frauds or adulteration, and fluorescence-based systems for recognition of contamination by heavy metal ions in water are two important families of sensors for health and environmental purposes. Both sensor families require one or more low-frequency Lock-In Amplifiers (LIAs) to extract the signal of interest from background noise. In the cited applications, the required LIA frequency is quite low (up to 1kHz), and this leads to a simplification of the hardware with consequent good results in portability, economy, reduced size, weight and low-cost characteristics. The present system, called ENEA DSP Box Due, is based on a very inexpensive microcontroller proto-board and can replace four commercial LIAs, resulting in significant savings in both cost and space. Furthermore, it incorporates a dual-channel oscilloscope and a sinusoidal function generator. This article outlines the architecture of the ENEA DSP Box Due, its electrical characterization and its applications within a project concerning laser techniques for food and water safety.

Background: Studies have tried to identify predictors of functional markers of keratoconus progression, whereas structural outcomes of collagen cross-linking have not been properly investigated. Objective: find and set up a combination of diagnostic modalities and measurements to reliably reflect CXL efficiency. Material and methods: We retrospectively reviewed the medical histories of 107 KC patients (131 eyes) who underwent CXL in a medical center from January 2018 to December 2022. The dataset included preoperative examinations and follow-up results, which provided a total of 796 observations. The cases of other corneal diseases, repeated CXL, pregnancy, and observations without follow-up examinations were excluded. Results: The study findings revealed a significant drop in the central and corneal thickness during 14.01±9.98 months of observations. Linear and polynomial equations suggested different trends in pachymetry change after CXL. The linear model showed corneal thinning, and according to the polynomials, pachymetry findings return to baseline values two years after CXL. Conclusion: The most reliable prognosis of postoperative corneal thickness is achieved with the models trained on keratometry readings and topography indices. BAD indices are also reliable predictors of the corneal thickness after CXL. A combination of the aforementioned structural parameters and their derivatives can reliably predict CXL efficiency.

Epilepsy is a common neurological condition, typically diagnosed using Electroencephalogram (EEG). Large scale EEG datasets have recently been made publicly available, allowing the use of advanced Machine Learning (ML) algorithms to analyze EEG patterns associated with epilepsy. While most existing studies focus on identifying seizures in the EEG, few have tried to identify preictal EEG segments. Identifying preictal EEG segments are not only useful in developing early warning systems but also helps inform the course of treatment for the patient. In this study, we propose to represent EEG segments as images, instead of time-series data, and identify preictal EEG segments using a preexisting ML algorithm (YOLOv8) designed for image processing. Multiplexed images (containing the original EEG signal represented on a 2D grid, kurtosis, and spectral entropy) achieve the best accuracy of 95.75% on the dataset while images just containing the EEG signal result in an accuracy of 91.25%. Using only spectrograms, generated from the original EEG signal, results in an accuracy of 90.15%.

Drowsiness is a main factor for various costly defects, even fatal accidents in areas such as construction, transportation, industry and medicine, due to the lack of monitoring vigilance in the mentioned areas. The implementation of a drowsiness detection system can greatly help to reduce the defects and accident rates by alerting individuals when they enter a drowsy state. This research proposes an Electroencephalography (EEG) based approach for detecting drowsiness. EEG signals are passed through a preprocessing chain composed of artifact removal and segmentation to ensure accurate detection followed by different feature extraction methods to extract the different features related to drowsiness. This work explores the use of various machine learning algorithms such as Support Vector Machine (SVM) the K Nearest Neighbor (KNN) the Naive Bayes (NB) the Decision Tree (DT) and the Multilayer Perceptron (MLP) to analyze EEG signals sourced from the DROZY database, carefully labeled into two distinct states of alertness (awake, and drowsy). Segmentation into 10-second intervals ensures precise detection, while a relevant feature selection layer enhances accuracy and generalizability. The proposed approach achieves high accuracy rates of 99.84% and 96.4% for intra (subject by subject) and inter (cross-subject) modes, respectively. SVM emerges as the most effective model for drowsiness detection in the intra mode, while MLP demonstrates superior accuracy in the inter mode. This research offers a promising avenue for implementing proactive drowsiness detection systems to enhance occupational safety across various industries.

Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

Long COVID is a persistent symptom that appears in many COVID-19 patients, regardless of whether they are asymptomatic, mild, or severe. At least 10% worldwide are suffering from long COVID. The anti-inflammatory effect was evaluated in LPS-treated RAW264.7 cells using six Korean national insurance-covered herbal prescriptions with therapeutic potential for mitigating inflammation in the respiratory tract, and additional network pharmacology analysis was performed. Soshihotang (SST) significantly downregulated iNOS and COX2 expression, reduced the production of NO (nitric oxide) and inflammatory cytokines, such as TNFα, IL-1β, and IL-6, and inhibited IκBα phosphorylation and reduced the nuclear translocation of NF-κB in LPS-treated RAW264.7 cells. Network pharmacological analysis showed that SST was closely related to the NF-κB signaling pathway. Further study on the potential of herbal prescriptions will be needed before they can be used clinically by long COVID patients.

This study aimed to demonstrate the potential role of Dual Energy CT in assessing Bone Mineral Density (BMD) in postmenopausal women. A retrospective study was conducted on 51 postmenopausal female patients who underwent DXA and DECT examinations for other clinical reasons. DECT images were acquired with spectral imaging using a 256-slice system. These images were processed and visualized using an HAP(fat) map. Statistical analysis was performed using the Bland-Altman method to assess agreement between DXA and DECT HAP(fat) measurements. Mean BMD, vertebral and femoral T-scores were obtained. For vertebral analysis, the Bland-Altman plot showed an inverse correlation (R2: -0.042; RMSE: 0.690) between T-scores and DECT HAP(fat) values for measurements from L1 to L4, while a good linear correlation (R2: 0.341; RMSE: 0.589) it was found for measurements at the femoral neck. In conclusion, we demonstrated the enhanced accuracy of BMD calculation through DECT, finding a statistically significant correlation only at the femoral neck where BMD results do not seem to be influenced by the overlap of the measurements on cortical and trabecular bone. This outcome could be beneficial in the future by reducing radiation exposure for patients already undergoing follow-up for chronic conditions.

Comprehensive next-generation sequencing (NGS) assays enable identification of clinically relevant mutations, enhancing the capability for targeted therapeutic interventions. In addition, genomic alterations driving the oncogenic roadmap and lead to resistance mechanisms are reshaping precision oncology. We report, workflow, informatics validation of OncoIndx NGS platform – a comprehensive genomic profiling (CGP)-base assay for pan-cancer investigation. We evaluated the concordance between the OncoIndx® test findings and clinically established hotspot findings using SeraSeq reference standards. OncoIndx is a hybridization capture-based NGS assay for targeted deep sequencing of all exons and selected introns of 1080 cancer related genes. We show the outcome in the form of -tier I and tier II single nucleotide variants (SNVs), copy number alterations (CNAs), and specific gene rearrangements (fusion). OncoIndx® also enables tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and genomic loss of heterozygosity (gLOH). We show maximum clinical sensitivity of 98% and a positive predictive value (PPV) of 100% for the clinically actionable genomic variants detected by the assay. In addition, we demonstrate analytical validation with performance of the assay, limit of detection (LoD), precision, and orthogonal concordance for various types of SVs, CNAs, genomic rearrangements, and complex biomarkers like TMB, MSI, and HRD. The assay offers reliable genomic predictions with high precision detection of actionable variants, validated by established reference standards.

Background: G6PD is a rate-limiting enzyme of the pentose phosphate pathway. The loss of G6PD activity in red blood cells exposes to the risk of acute haemolytic anaemia under oxidative stress, induced by infections, some medications, or fava beans. More than 200 single missense mutations are known in the G6PD gene. This study reports a 41-year-old woman coming from Basilicata region (Italy) that carried out the G6PD status in our hospital for prenatal investiga-tions. Methods: DNA was extracted from peripheral blood sample and genotyped for common-est G6PD pathogenic variants (PVs). Positive results obtained by Restriction Fragment Length Polymorphism (RFLP), as per practice in our laboratory, are then re-confirmed in Sanger se-quencing. Results: RFLP analysis highlighted a variant compatible with G6PD Cassano variant. Confirmatory testing by Sanger unexpectedly identified a novel variant: c.1357G>A, p.(Val453Met) (NM_001360016.2). In silico models predicted a deleterious effect of this variant at the protein level. The novel G6PD variant was named "G6PD Potenza", on the basis of the pa-tient's regional origin. Conclusion: This case describes a novel G6PD variant. It also highlights how the Sanger sequencing technique still represents an indispensable confirmatory standard method for variants that could be miss-interpreted by using of “first-level” approached, as the RFLP. We stress that the evaluation of clinical manifestations in G6PD deficient patients is of primary importance for the classification of each new G6PD mutation, in agreement with the new WHO guidelines.

Despite the existing effective treatment methods, tuberculosis (TB) is the second most deadly infectious disease globally, its carriers in the latent and active phases accounting for more than 20% of the world population. An effective method to control TB and reduce the mortality is regular population screening and diagnosis of the latent form of TB in order to take preventive and curative measures. Numerous methods allow diagnosing TB and directly detecting Mycobacterium tuberculosis (M.tb) biomarkers, including M.tb DNA, proteins, and specific metabolites, as well as antibodies produced by the host immune system in response to M.tb. PCR, ELISA, immunofluorescence and immunochemical analyses, flow cytometry, and other methods allow the detection of M.tb biomarkers or the host immune response to M.tb by recording the optical signal of fluorescent or colorimetric dyes included in the diagnostic tools. Current research in biosensors is aimed at increasing the sensitivity of detection, which can be achieved by using brighter and more photostable optical tags containing fluorescent quantum dots. Here, we review current methods for detection of M.tb biomarkers using optical sensor systems, primarily quantum dot–based nanosensors, and summarize M.tb biomarkers whose detection can be made significantly more sensitive by using quantum dot–based nanosensors.

Background: The incidence of various types of cancer, for example papillary thyroid carcinoma (PTC), is on the rise. Since therapeutic success depends greatly on early diagnosis, reliable diag-nostic biomarkers must be identified and easy-to-apply tools for detecting them must urgently be standardized. Here, we contribute to solving this medical challenge by assessing miRNAs sus-pected of promoting carcinogenesis in extracellular vesicles (EVs) that can be routinely obtained via liquid biopsy. We profit from current progress in cancerology that provides innovations in liquid biopsy and EVs analysis along with identification of miRNAs and chaperone system (CS) components implicated in carcinogenesis. Methods: We measured in EVs obtained from circulat-ing blood plasma from PTC patients the levels of three miRNAs implicated in thyroid cancer, miR-1, miR-206, and miR-221, and most likely involved in the regulation of two members of the CS, Hsp60 and CCT. EVs were isolated from the plasma of patients with PTC and controls with benign goiter (BG), and from the culture medium of a PTC cell line (MDAT32) and were duly characterized. Results: The levels of miRNAs determined by RT-qPCR were consistently higher in PTC patients and decreased down to control levels after thyroidectomy. Bioinformatics showed that the miRNAs target genes were associated to the molecular pathogenesis of PTC. Conclusions: Thus, our exploratory study reaffirms the potential in clinics of the selected miRNAs in EVs as useful biomarkers of PTC easily accessible via liquid biopsy, which is minimally invasive and amenable to periodic repetition, an improvement compared to the established fine-needle aspirate biopsy.

Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity. Materials and Methods: This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns. Images were processed with ClariCT. AI deep learning model (DLM) for noise reduction. Objective image quality was assessed using metrics such as the differentiation between voxel values (ΔVVs), the artifact index (AIx), and the contrast-to-noise ratio (CNR). Subjective assessments were performed by two experienced readers, who rated overall image quality and artifact intensity on predefined scales. Results: Compared with native images, DLM reconstructions significantly reduced the AIx and increased the CNR (p<0.001), indicating improved image clarity and artifact reduction. Subjective assessments also favored DLM images, with higher ratings for overall image quality and lower artifact intensity (p<0.001). However, the ΔVV values were similar between the native and DLM images, indicating that while the DLM reduced noise, it maintained the overall density distribution. Orthodontic appliances produced the most pronounced artifacts, while implants generated the least. Conclusion: AI-based noise reduction using ClariCT. AI significantly enhances CBCT image quality by reducing noise and metal artifacts, thereby improving diagnostic accuracy and treatment planning. Further research with larger, multicenter cohorts is recommended to validate these findings.

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal intriguing construction of frizzling feather shaft through modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

Cystic artery bleeding (CAB), a relatively uncommon entity, can arise from both traumatic and non-traumatic etiologies. This pictorial essay aims to elucidate the computed tomography (CT) findings associated with CAB in these distinct contexts. In traumatic CAB, particularly blunt or penetrating trauma, a cystic artery lesion is the culprit behind the hemoperitoneum characteristically located within the gallbladder fossa. Prompt diagnosis is crucial. Fortunately, trans-arterial embolization offers a successful treatment option for traumatic cystic artery lesions, especially in settings where non-operative management is preferred. Non-traumatic CAB, on the other hand, often stems from inflammation in the hepatobiliary and pancreatic system, gallbladder tumours, or iatrogenic injuries. The underlying mechanism typically involves cystic artery wall damage, either due to inflammation or procedural complications, leading to the formation of a cystic artery pseudoaneurysm (CAP). Notably, CAP bleeding can manifest long after the causative event, posing a diagnostic challenge with a variable clinical presentation. This pictorial essay serves to illustrate the CT signs and features of CAB in both traumatic and non-traumatic scenarios. Additionally, it will delve into the characteristic CT appearance of CAP.

Detecting IgE sensitizations in the serum of allergic dogs is commonly done using allergen extracts, but these are difficult to standardize. This article details the development and validation of the Pet Allergy Xplorer (PAX; Nextmune, Stockholm, Sweden), the first multiplex macroarray for the detection of IgE sensitization in dogs using allergen extracts and molecular components; the PAX is derived from the Allergy Xplorer (ALEX2; MacroArray Diagnostics, Vienna, Austria). The selection of allergens, cartridge processing, strategy for identifying and blocking IgE directed against cross-reactive carbohydrate determinants (CCD), and the method used for determining the positivity threshold are described. The validation of the PAX included evaluations of the specificity of its anti-IgE monoclonal antibody, specificity of IgE binding to target allergens, assay precision, and internal consistency. Additionally, the influence of possible confounding factors, such as sample type, the influence of hemolysis, lipemia, bilirubinemia, and elevated CCD-IgE, was tested. Finally, the sensitization rates of 23,858 European dogs to 145 environmental and Hymenoptera venom allergens were summarized. The PAX is accurate and reproducible and has a unique CCD-detection and blocking strategy; its molecular allergens offer a unique window on allergen cross-reactivity.

Mesenteric ischemia diagnosis is challenging with an overall mortality in up to 50% of cases despite advances in treatment. The main problem that affects the outcome is the delayed diagnosis because of non-specific clinical presentation. Multi Detector CT Angiography (MDCTA) is the first line investigation for the suspected diagnosis of vascular abdominal pathologies and is the diagnostic test of choice in suspected mesenteric bowel ischemia. MDCTA can accurately detect the presence of arterial and venous thrombosis, determine the extension and the gastrointestinal tract involved, and provide detailed information determining the subtype and the stage progression of the diseases helping clinicians and surgeons for the proper management. CT can differentiate forms that are still susceptible to pharmacological or interventional treatment (NOM= non-operative management) from advanced disease with transmural necrosis in which a surgical approach is required. Knowledge of CT imaging patterns and corresponding vascular pathways is mandatory in Emergency settings to reach a prompt and accurate diagnosis. The aims of this paper are 1. to provide technical information about the optimal CTA protocol; 2. To empathize the CTA arterial and venous supply to gastrointestinal tract and relative ischemic pattern; 3. To describe vascular, bowel and extraintestinal CT findings for the diagnosis of acute mesenteric ischemia.

Background: The aim of this systematic review was to evaluate diagnostic accuracy of molecular-based LTPs serum IgE for the diagnosis of food allergies in patients with suspected allergy to one of the LTPs-containing food. Methods: cohort, prospective or retrospective cross- sectional studies were considered for inclusion in the review. Oral food challenge (both open and double-blind placebo-controlled) was the reference standard for the diagnosis. Pubmed (MEDLINE), Web of Science, Scopus, and ClinicalTrial.org were searched for relevant papers. Risk of bias was assigned by QUADAS-2 tool. Data were reported as sensitivity and specificity. Study protocol was registered in the PROSPERO database (CRD42022321985). Results: Fifteen articles, including 2395 individuals, were included. Sensitivity of Ara h 9 for peanut allergy diagnosis ranged from 6 to 61%; specificity ranged from 57 to 100%. Cor a 8 sensitivity ranged from 11 to 43%, with specificity ranging from 59 to 94%. Conclusions: Ara h9 and Cor a 8 serum IgE may be useful to confirm diagnosis of peanut and hazelnut allergy in symptomatic patients, although diagnostic accuracy is limited by low sensitivity. More investigation on other LTPs and in adult population may be important to define the clinical role of this test in food allergies diagnostics.

The nuclear magnetic resonance (NMR) metabolomic analysis was applied to investigate the differences within nineteen Sicilian Nocellara del Belice mono varietal Extra Virgin Olive Oils (EVOO), grown in two zones different for altitude and soil composition. Several classes of endogenous olive oil metabolites were quantified through a nuclear magnetic resonance (NMR) three-experiment protocol coupled with a yet developed data-processing called MARA-NMR. This method, taking around one-hour experimental time per sample, faces the possible quantification of different class of compounds at different concentration’s range which would require at least three alternative traditional methods. NMR results were compared with the data of traditional analytical methods to quantify free fatty acidity (FFA), fatty acid methyl esters (FAMEs), and total phenol content. The presented NMR methodology is compared with traditional analytical practices and its consistency is also tested through slightly different data treatment. Despite the rich literature about the NMR of EVOOs, the paper points out that there are still several advances potentially improving this general analysis and overcoming the other cumbersome and multi-devices analytical strategies. Monovarietal EVOO’s composition is mainly affected by pedoclimatic conditions in turn relaying upon the nutritional properties, quality, and authenticity. Data collection, analysis and statistical processing are discussed touching the important issues related to the climate changes in Sicily and to the specific influence of pedoclimatic conditions.

Brain tumors still remain a deadly cancer that, in most cases, is difficult to diagnose at an earlier stage. Therefore, it is necessary to develop rapid, sensitive methods for detecting cancer biomarkers. Such a biomarker may be a microRNA which expression level in body fluids is strongly correlated with cancer. Numerous studies have demonstrated changes in the expression of microRNAs in cerebrospinal fluid and blood samples collected from patients with brain tumors. These new biomarkers have the potential to help diagnose brain cancers at an early stage, avoiding the most invasive procedures. This review discusses the functional role of microRNAs and the prospects for their use as diagnostic biomarkers in patients with brain tumors.

Background and Objectives To compare navigator-gated three-dimensional T1-weighted gradient-echo sequences (NG-3D T1W-GRE) with standard breath-hold T1W-GRE (BH T1W-GRE) for the detection of HCC nodules in patients with chronic viral hepatitis which undergo at magnetic resonance imaging (MRI) using gadoxetic acid. Methods and materials We evaluated 58 patients with hepatic nodules at least 1 cm in diameter detected by ultrasound who underwent liver MRI including NG-3D T1W-GRE sequences and breath hold T1-weighted gradient-echo sequences with different flip angles(FA) at 10-25-40° after contrast administration of gadoxetic acid at magnetic scanner operating at1.5 Tesla. Image quality and relative hepatic and nodular enhancement were evaluated by three blinded reviewers. Results In these patients, image quality of NG-3D T1W-GRE was assessed significantly better than quality of BHT1W- GRE (P < 0.005) and relative enhancement was significantly higher than that of BH- T1W-GRE ( P

Background: Despite recent advancements, medical technology has not yet reached its peak. Precision medicine is growing rapidly, thanks to machine learning breakthroughs powered by increased computational capabilities. This article explores a deep-learning application for computer-aided diagnosis in dermatology. Methods: Using a custom model based on EfficientNetB3 and deep learning, we propose an approach for skin lesion classification that offers superior results with smaller, cheaper, and faster inference times compared to other models. The skin images dataset used for this research includes 8,222 files selected from the authors' collection and the ISIC2019 archive, covering six dermatological conditions. Results: The model achieved 95.4% validation accuracy on four categories—melanoma, basal cell carcinoma, benign keratosis-like lesions, and melanocytic nevi—using an average of 1,600 images per category. Adding two categories with fewer images (about 700 each)—squamous cell carcinoma and actinic keratoses—reduced the validation accuracy to 88.8%. The model maintained accuracy on new clinical test images taken under the same conditions as the training dataset. Conclusions: The custom model demonstrated excellent performance on the diverse skin lesions dataset, with significant potential for further enhancements.

Background and Objectives: High job strain is worsening the outcome in coronary artery disease, CAD. Severe dissatisfaction on workplace, imbalance between high demands , and low rewards, are affecting the quality of life, and diminishing the duration of life, especially in CAD patients. Our study included two samples : CAD patients (experimental group), and without CAD patients, but with traditional risk factors (control group). The main objective of the study was the role played by high sensitivity C reactive protein, hs CRP, and microalbuminuria, as mediators of job strain and CAD relationship. Secondary objectives were the following: identification of the most vulnerable patients( with significant job strain) and intervention towards this category, for cardiovascular events prevention (primary or secondary). Materials and Methods: The utilized methods were the following : clinical exam; electrocardiogram; echocardiogram; non contrast enhanced computed chest tomography; laboratory findings ( lipid profile, glycemia, hs CRP, microalbuminuria); type D scale, DS 14; depression questionnaire, PHQ-9; and satisfaction with work scale, SWWS. Results: The highest values for hs CRP and microalbuminuria were noticed in patients with the lowest Likert score, for both samples CAD, and without CAD patients. The highest job strain was noticed in females. More than half of CAD patients ,with low Likert scores, revealed myocardial infarction. Conclusions: Microalbuminuria and hs CRP were statistical significant in the study as intercessors, in job strain and CAD relationship. The most vulnerable patients for vascular events were females, in both groups : CAD and “CAD waiting desk”. In CAD sample, the vascular vulnerability was also increased by high job strain.

Search for the new non-invasive methods of investigating the functioning of human internal organs is an urgent task. One of these methods for assessing the functioning of the human res-piratory system is electromagnetic sensing, based on a significant difference in the dielectric permittivity of muscle tissue and air. During breathing, when the lungs are filled with air, the dielectric permittivity of the lungs decreases, which leads to a change in the level of the elec-tromagnetic signal passing through the body. Results of experiments on recording changes in the level of electromagnetic radiation passing through the human body, performed on an experimental device consisting of eight transmitting and receiving antennas located on opposite sides of the chest have been presented in the article. The possibility of visualizing the measured “pulmonograms” in the form of dynamic two-dimensional images showing the process of filling various parts of the lungs with air has been demonstrated.

Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are “black box” to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffer from poor generalization ability in presence of dataset shift. Here, we present a comparison between an explainable-by-design (“white box”) model (Bayesian Network (BN)) versus a black-box model (Random Forest), both studied with the aim to support clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.

Currently, SARS-CoV-2 has evolved into various variants, including the numerous highly mutated Omicron sub-lineages, significantly increasing immune evasion ability. The development raises concerns about possibly diminished effectiveness of available vaccines and antibody-based therapeutics. Here, we describe those representative categories of broadly neutralizing antibodies (bnAbs) that retain prominent effectiveness against emerging variants including Omicron sub-lineages. The molecular characteristics, epitope conservation, and resistance mechanisms of these antibodies are further detailed, aiming to offer suggestion or direction for the development of therapeutic antibodies, and facilitate the vaccine design with broad-spectrum potential.

The MAPK signaling pathway with BRAF mutations has been shown to drive the pathogenesis of 40-60% of melanomas. Inhibitors of this pathway's BRAF and MEK components are currently used to treat these malignancies. However, responses to these treatments are not always successful. Therefore, identifying noninvasive biomarkers to predict treatment responses is essential for personalized medicine of melanoma patients. Using noninvasive 1H magnetic resonance spectroscopy (1H MRS), we previously showed that BRAF inhibition reduces lactate and alanine tumor levels at early stages of effective therapy and could be construed as metabolic imaging biomarkers for drug response. The present work aimed to demonstrate if these metabolic changes and those assessed by 31P MRS are also found in preclinical human melanoma models treated with MEK inhibitors. Apart from 1H and 31P MRS, additional supporting in vitro biochemical analyses are described. Our results indicate significant early metabolic correlations with response levels to MEK inhibition in the melanoma models and are consistent with our previous study of BRAF inhibition. Given these results, our study supports the potential clinical utility of noninvasive MRS to objectively image metabolic biomarkers for early predicting melanoma response to MEK inhibition.

Alzheimer's disease (AD) is the most prevalent form of dementia. With the global aging population, the incidence of AD and related dementias is projected to rise dramatically, posing significant public health challenges. Traditionally, the diagnosis of AD has relied on the detection of amyloid-beta (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau in the brain, assessed through invasive cerebrospinal fluid (CSF) analysis and costly positron emission tomography scans. However, these methods are not feasible for widespread screening or use in low-resource settings. Recent advances in blood-based biomarkers offer a promising alternative for the early detection and monitoring of AD. These biomarkers provide a minimally invasive, cost-effective means of tracking the pathological progression of AD before the onset of clinical symptoms, potentially enabling earlier and more accurate diagnosis. Blood-based biomarkers, including those related to Aβ, phosphorylated tau, and neurofilament light polypeptide, have demonstrated significant potential in reflecting the underlying neuropathology of AD and correlating with traditional CSF and imaging biomarkers. This review synthesizes the latest research on blood-based biomarkers in AD, highlighting their role in the disease's etiopathogenesis, diagnostic accuracy, and prognostic value. We discuss the emerging evidence on proteinopathies, neuroinflammation, vascular pathology, and bioenergetic profiles, emphasizing the clinical applicability of these biomarkers. Furthermore, we explore the integration of blood-based biomarkers with advanced neuroimaging techniques and their potential to revolutionize the diagnostic landscape of AD, particularly in resource-limited settings. We have integrated protein-protein interaction (PPI) and miRNA network analyses to enhance the analysis. By incorporating these, we can explore the interactions and relationships between different proteomic, genomic, and epigenomic biomarkers, potentially unveiling new insights into the underlying biological mechanisms of AD. The continued development and validation of these biomarkers could lead to more accessible and equitable AD diagnostics, ultimately improving patient outcomes.

For the first time to optimize the creation of new neuroprotective agents based on bioflavonoids, we applied information technologies - docking analysis to calculate the binding of candidate molecules to the pharmacological target protein transthyretin, as well as the program of virtual screening of NO scavengers. As a result of this approach, the substance catechin was isolated from candidate molecules - quercetin, catechin, Epicatechin gallate, Epicatechin, Procyanidin B1, Procyanidin B2, Procyanidin B3, Catechin-3-gallate according to docking analysis. As a result of virtual screening, catechin was identified as a potential NO scavenger (55.15% prediction). The results of the prediction were confirmed by in vitro experiments. Course administration of catechin to animals with experimental multiple sclerosis (MS) against the background of methylprednisolone administration completely eliminated lethal cases, reduced the number of diseased animals by 20%, as well as prevented the development of severe neurological symptoms by 20% (compared to the methylprednisolone group) and by 60% compared to the control group. Course administration of catechin with methylprednisolone leads to decrease of neurodegradation markers in the cytosol of rats with EAE: NSE by 37%, and S-100 - by 54.8%. The combined administration of methylprednisolone significantly exceeds the combination of methylprednisolone with the reference drug mexidol by the degree of NSE reduction. The obtained results indicate a significant neuroprotective effect of ocular combinations of methylprednisolone and catechin. The above-mentioned confirms the correctness of bioflavonoid selection with the help of virtual screening program.

It is generally assumed that spirochetemia does not take place at the early localized stage of Lyme disease. This misassumption is due to the lack of sensitive and specific methods for detection. This paper reports that separation of the platelet-rich plasma immediately after venous blood collection to prevent the spirochetes from invading the lymphocytes in the test tube is crucial in molecular detection of a single Borrelia burgdorferi cell spun down in platelet pellets. In 2023, we tested the venous blood specimens of 145 people residing in Lyme disease-endemic areas in the United States. In 98 of them, who were suspected of having early localized Lyme disease irrespective of the absence or presence of a skin lesion, we found 33 specimens (33.7%) positive for B. burgdorferi, including 17 positive for FlaB gene only, 15 positive for both FlaB gene and 16S rRNA gene, and 1 positive for 16S rRNA gene only. Eight (17.0%) of the 47 asymptomatic resident controls were positive for FlaB PCR only. FlaB is a more sensitive chromosomal target than the 16S rRNA gene for the detection of 1-3 B. burgdorferi cells in 1 mL of platelet-rich plasma due to spirochetes gaining or retaining FlaB paralogs at the early localized stage of Lyme disease.

Quantum correlations, especially time correlations, are crucial in ghost imaging in order to significantly reduce the background noise on the one hand while increasing the imaging resolution. Moreover, the time correlations serve as a critical reference, distinguishing between signal and noise, which in turn enable clear visualization of biological samples. Quantum imaging also addresses the challenge involved in imaging delicate biological structures with minimal photon exposure and sample damage. Here we explore the recent progress in quantum correlation-based imaging, notably its impact on secure imaging and remote sensing protocols as well as on biological imaging. We also exploit the quantum characteristics of heralded single-photon sources (HSPS) combined with decoy-state methods for secure imaging. This method uses Quantum Key Distribution (QKD) principles to reduce measurement uncertainties and protect data integrity. It is highly effective in low-photon-number regimes for producing high-quality, noise-reduced images. The versatility of decoy-state methods with WCSs (WCS) is also discussed, highlighting their suitability for scenarios requiring higher photon numbers. We emphasize the dual advantages of these techniques: improving image quality through noise reduction and enhancing data security with quantum encryption, suggesting significant potential for quantum imaging in various applications, from delicate biological imaging to secure quantum communication.

One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Images of an experimental peach orchard were acquired from the Parma Research and Extension Center of the University of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (Near-infrared, Green, Blue). The orchard has different stone fruit varieties and different plant training system. Individual tree images (high-resolution) and arrays of trees images (low-resolution) were acquired to evaluate the detection capability. The image processing algorithm was based on different vegetation indices. Initial results showed that the image processing algorithm could detect peach blossoms and demonstrate good potential as a monitoring tool for orchard management.

Hypoxia is a hallmark of solid tumors, including hepatocellular carcinoma (HCC). Hypoxia has proved to be involved in multiple tumor biological processes and associated with malignant progression and resistance to therapy. Transarterial chemoembolization (TACE) is a well-established locoregional therapy for patients with unresectable HCC. However, TACE-induced hypoxia regulates tumor angiogenesis, energy metabolism, epithelial-mesenchymal transition (EMT), and immune processes through hypoxia-inducible factor 1 (HIF-1), which may have adverse effects on the therapeutic efficacy of TACE. Hypoxia has emerged as a promising target for combination with TACE in treatment of HCC. This review summarizes impact of hypoxia on HCC tumor biology, adverse effects of TACE-induced hypoxia on its therapeutic efficacy, highlighting the therapeutic potential of hypoxia-targeted therapy in combination with TACE for HCC.

The increasing emergence of multidrug resistant (MDR) pathogens causes difficult-to-treat infections, with long-term hospitalizations and high incidence of death, thus representing a global public health problem. To manage MDR bacteria bugs, new antimicrobial strategies are necessary, and their introduction in practice is a daily challenge for scientists in the field. An extensively studied approach to treat MDR infections consists in inducing high levels of reactive oxygen species (ROS) by several methods. Although further clinical investigations are mandatory on the possible toxic effects of ROS to mammalian cells, clinical evaluations are extremely promising, and their topical use to treat infected wounds and ulcers, also in presence of biofilm, is already clinically approved. Biochar (BC) is a carbonaceous material obtained by pyrolysis of different vegetable and animal biomass feedstocks, at 200−1000 °C in limited presence of O2. Recently, it has been demonstrated that BC capability of removing organic and inorganic xenobiotics is mainly due to the presence of persistent free radicals (PFRs), which can activate oxygen, H2O2 or persulfate in the presence or not of transition metals by electron transfer thus generating ROS, which in turn degrade pollutants by advanced oxidation processes (AOPs). In this context, the antibacterial effects of BC containing PFRs have been demonstrated by some authors against Escherichia coli and Staphylococcus aureus, thus giving birth to our idea of the possible use of BC-derived PFRs as a novel method capable of inducing ROS generation for antimicrobial oxidative therapy. Here, the general aspects concerning ROS physiological and pathological production and regulation, and the mechanism by which they could exert antimicrobial effects have been reviewed. The methods currently adopted to induce ROS production for antimicrobial oxidative therapy have been discussed. Finally, for the first time, BC-related PFRs have been proposed as a new source of ROS for antimicrobial therapy via AOPs.

Introduction Atherosclerotic disease is a major contributor to heart failure, stroke, and myocardial infarction, significantly lowering the quality of life and life expectancy, with a significant burden on healthcare. Not all lesions deemed non-significant are benign, and conversely, not all significant lesions are causative of ischemia. Fractional flow reserve (FFR) provides a functional assessment of coronary lesions, while optical coherence tomography (OCT) offers detailed imaging of plaque morphology, aiding in therapeutic decision-making. The objective of this study was to evaluate the utility of OCT and FFR as adjunctive tools in the catheterization laboratory for guiding therapeutic decisions in patients with multivessel disease for non-culprit vessels. Specifically, we aimed to assess how OCT and FFR influence therapeutic decision-making in patients with multi-vessel coronary artery disease. Methods 36 patients with acute coronary syndrome (ACS) and multivessel disease were randomized 1:1 into two groups: one guided by FFR alone, and the other by a combination of FFR and OCT. For the FFR group, revascularization decisions for non culprit lesions were based solely on FFR measurements. If the FFR was >0.8, the procedure concluded, and the patient received maximal medical treatment. If the FFR was ≤0.8, a stent was placed. For the FFR + OCT group, if the FFR was >0.8, the revascularization decision was based on OCT findings. If there were no vulnerable plaques (VP), the procedure concluded, and the patient received maximal medical treatment. If OCT imaging indicated VP, then the patient underwent revascularization. If the FFR was ≤0.8, the patient underwent revascularization regardless of OCT findings. Results OCT imaging altered the therapeutic decision in 11 cases where FFR measurements were above 0.8, but the lesions were characterized as VP. Analyzing the total change in the decision to stent, 4 cases in the FFR group and 15 cases in the FFR and OCT group (4 based on FFR and 11 on OCT) revealed a statistically significant difference (p = 0.0006; Relative Risk = 0.2556; 95% CI: 0.1013 to 0.5603). When analyzing the change in the total decision both to stent and not to stent, we observed a statistically significant difference, with Group 1 having 7 cases and Group 2 having 15 cases (p = 0.0153; Relative Risk = 0.4050; 95% CI: 0.2004 to 0.7698) Conclusion Based on the findings of this study, OCT significantly increases the percentage of stenting procedures by identifying vulnerable lesions. The use of intracoronary imaging facilitates the timely identification and treatment of these vulnerable lesions. This underscores the crucial role of OCT in enhancing the precision of coronary interventions by ensuring timely intervention for vulnerable lesions, thereby potentially improving patient outcomes Acknowledgment funding „This work was supported by the University of Medicine, Pharmacy, Science and Technology ,, George Emil Palade’’ of Targu Mures Research Grant number 510/14/17.01.2022”

Selenium is essential for the synthesis and function of various selenoenzymes, such as glutathione peroxidases, selenoprotein P, and thioredoxin reductase, which play an important role in both antioxidant defense and limiting oxidative damage. Associations between serum selenium concentration and obstetric complications as well as pregnancy outcomes has been reported in many studies. The aim of this study was to determine whether the dietary intake of selenium, its concentration in serum and the activity of glutathione peroxidase in subsequent trimesters of pregnancy affect the birth condition of newborns assessed on the basis of the Apgar score in the 1st and 5th minute of life, birth weight, body length and head and chest circumference in physiological and complicated pregnancy course. Twenty-seven pregnant women at a mean age 29.6 ± 4.8 years from the Lower Silesia region of Poland were recruited to the study, 55% of studied group had pregnancy complications. The mean reported Se intake and serum selenium content for Polish pregnant women was in the first trimester – 56.53 μg/day and 43.75 μg/l, the second trimester – 61.79 μg/day and 41.77 μg/l and the third trimester – 58.37 μg/day and 42.13 μg/l, respectively. In the subgroup of pregnant women with a physiological pregnancy course, a weak, although statistically significant, positive correlation was found in the first trimester between Se intake and the length (R=0.48, p=0.019) and birth weight of newborns (R=0.472, p=0.022), and in the second trimester with the APGAR score at 1 (R=0.680, p=0.005) and 5 minutes (R=0.55, p=0.033), as well as in the third trimester with th APGAR score at 1 minut (R=0.658, p=0.019). The GPX value had a strong positive correlation with the APGAR score at 1 min. (R=0.650, p=0.008) in the second trimester and with the birth weight of the newborns (R=0.598, p=0.039) in the third trimester. There was no correlation between newborns' birth measurements and serum selenium concentration. In the subgroup of pregnant women with pregnancy complications, a strong, statistically significant, negative correlation was found between Se intake in the second trimester and gestational age (R=-0.618, p=0.032), and in the third trimester, a positive correlation between Se concentration in serum and head circumference (R=0.587, p=0.021). The obtained results indicate that there is a relationship between the maternal selenium status during pregnancy, both in terms of the intake of this element, its serum concentration as well as the glutathione peroxidase activity, and the anthropometric parameters of the newborn, such as birth weight, length and APGAR score, especially in the group with physiological course of pregnancy, but when pregnancy complications occur, these relationships lose their importance.

This study investigated a novel radioimmunotherapy strategy for targeting tumor angiogenesis. We developed a radiopharmaceutical complex by labeling an anti-adenosine triphosphate syn-thase (ATPS) monoclonal antibody (mAb) with the radioisotope 177Lu using DOTA as a chelating agent. 177Lu-DOTA-ATPS mAb demonstrated high labeling efficiency (99.0%) and stability in se-rum. MKN-45 cancer cells exhibited the highest cellular uptake, which could be specifically blocked by unlabeled ATPS mAb. In mice, 177Lu-DOTA-ATPS mAb accumulated significantly in tumors, with a tumor uptake of 16.0 ± 1.5%ID/g on day 7. 177Lu-DOTA-ATPS mAb treatment sig-nificantly reduced the viability of MKN-45 cells in a dose-dependent manner. In a xenograft tumor model, this radioimmunotherapy strategy led to substantial tumor growth inhibition (82.8%). Furthermore, combining 177Lu-DOTA-ATPS mAb with sunitinib, an anti-angiogenic drug, en-hanced the therapeutic efficacy of sunitinib in the mouse model. Our study successfully developed 177Lu-DOTA-ATPS mAb, a radioimmunotherapy agent targeting tumor blood vessels. This ap-proach demonstrates significant promise for inhibiting tumor growth, both as a single therapy and in combination with other anti-cancer drugs.

Background: SARS-CoV-2 Omicron JN.1 has the highest number of amino acid mutations in its receptor binding domain (RBD) and has acquired a hallmark L455S mutation. The immune evasion capability of JN.1 is a subject of scientific investigation. The US CDC used RT-qPCR SGTF as the proxy indicator of JN.1 infections for evaluation of the effectiveness of updated monovalent XBB.1.5 COVID-19 vaccines against JN.1 and recommended that all persons aged ≥6 months should receive an updated COVID-19 vaccine dose. Objective: Recommend Sanger sequencing for diagnosis of JN.1 infections to generate the data based on which guidelines are made to direct vaccination policies. Methods: The RNA in nasopharyngeal swab specimens from patients with clinical respiratory infection was subjected to nested RT-PCR, targeting a 398-base segment of the N-gene and a 445-base segment of the RBD of SARS-CoV-2 for amplification. The DNA sequences were analyzed for amino acid mutations. Results: The N-gene sequence showed Q229K, usually associated with Omicron BA.2.86 (+JN.1). The RBD sequence showed 24 amino acid mutations, including the hallmark L455S mutation for JN.1 and the V483del for BA.2.86 lineage. Conclusions: The CDC should consider Sanger sequencing of the RBD to diagnose JN.1 infections for statistical analysis in making vaccination policies.

In the contemporary world of science, continuous observation of specific fixed regions is required, awaiting the emergence of targets or phenomena within those areas to locate and identify them. Astronomy requires continuous monitoring of stars, swiftly pinpointing occurrences, such as flares, and acquiring their spectral data to aid identification. In military contexts, continuous observation of specific areas is essential for promptly locating enemy movements and obtaining target spectral data for deciphering enemy disguises. Additionally, continuous observation of experimental samples in biochemistry is mandatory to pinpoint localized changes and acquire spectral data from those areas. Hence, this paper develops a novel imaging spectrometer solution to monitor localized regions continuously. Specifically, this paper first elaborates on the developed instrument’s characteristics and optical structure, followed by optical design software simulations. The instrument has an F-number of 5, a focal length of 100mm, and a field of view covering the wavelength range from 400nm to 600nm. The optical path diagram indicates that the system’s dispersion and imaging images can be separated, meeting the system’s requirements. Besides, the Modulation Transfer Function (MTF) graph confirms that the image quality meets the requirements. Furthermore, a region-monitoring type imaging spectrometer was constructed to assess the instrument’s capability for spectral observation of fixed regions. The instrument can detect a fixed area, with the target placed within the detection area. Spectral data were successfully obtained by conducting image processing on the acquired images. The correlation coefficient between this data and reference data was as high as 0.9226, indicating the instrument’s successful measurement of the target’s spectrum. Thus, the developed instrument demonstrated that it can image the observed areas and acquire spectral data from targets within those regions.

Although ovarian cystic teratoma is the most common ovarian tumor, complications are quite rare. However, it is important to be recognized by the radiologist in order to avoid inaccurately diagnosing them as malignant lesions. This case report describes a 61-year-old postmenopausal woman, who presented to the emergency room with abdominal pain following a minor blunt abdominal trauma. In this context, a CT scan was performed, which showed the presence of round, hypodense masses randomly distributed in the peritoneum, with coexisting ascites in moderate amount; ovarian carcinoma with peritoneal carcinomatosis was suspected. The patient was hospitalized and an MRI of the abdomen and pelvis was recommended for a more detailed lesion characterization. Following this examination, the patient was diagnosed with mature cystic ovarian teratoma complicated by rupture. Surgery was performed, and the outcome was favorable. The cases of ruptured cystic teratomas are rare, and to our knowledge, this is the first occurrence described in literature. Special attention must be paid when confronting with such a case in medical practice, since it can easily misdiagnosed as peritoneal carcinomatosis

This review is focused on the current status of quantitative MR (qMR) of skeletal muscle. The first section covers the techniques of qMR in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/ pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1 weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, diffusion tensor imaging to emerging qMR features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMR of muscle; the intent is to demonstrate the utility qMR in different disease states of the muscle rather than a complete comprehensive survey.

During the COVID-19 pandemic, antibody-based vaccines targeting the SARS-CoV-2 spike glycoprotein were the key focus for development because neutralizing antibodies were associated with protection against the SARS-CoV-2 infection in pre-clinical models and human trials. While deploying these spike-based vaccines saved millions of lives worldwide, it has become clear that the immunological mechanisms of protection against severe disease are multifaceted and involve non-neutralizing antibody components. Here, we describe a novel pan-sarbecovirus T-cell vaccine, ChAdOx1.COVconsv12, designed to complement and broaden the protection of spike vaccines. The vaccine immunogen COVconsv12 employs the two regions in the viral proteome most conserved among sarbecoviruses delivered by replication-deficient vector ChAdOx1. It focuses T cells towards epitopes shared among sarbecoviruses including evolving SARS-CoV-2 variants. Here, we show that ChAdOx1.COVconsv12 induced broad T-cell responses in the BALB/c and C57BL/6 mice. In the Syrian hamster challenge model, ChAdOx1.COVconsv12 alone did not protect against the SARS-CoV-2 infection, but when co-administered with 1/50th of the ChAdOx1 nCoV-19 spike vaccine protective dose, faster recovery and lower oral swab viral load were observed. Induction of CD8+ T cells may decrease COVID-19 severity and extend the T-cell response coverage of variants to match the known (and as yet unknown) members of the beta-coronavirus family.

Although migraine belongs to the main causes of disability worldwide the mechanisms of its pathogenesis are poorly known, which is among the reasons that this disease is underdiagnosed and undertreated. As migraine diagnosis is based on the subjective assessment of symptoms, there is a need to establish objective markers of its occurrence and severity. Tryptophan (TRP) metabolism has been associated with the pathogenesis of neurological and psychiatric disorders. In the present work, we investigated an association between migraine and the urine concentration of TRP and its metabolites 5-hydroxyindoleacetic acid (5-HIAA), kynurenine (KYN), kynurenic acid (KYNA) and quinolinic acid (QA) in 21 low-frequency episodic migraine patients and 32 controls. Migraine patients displayed lower urinary levels of 5-HIAA and KYNA, but KYN and QA were enhanced as compared with the controls. Consequently, the patients were characterized by different values of the 5-HIAA/TRP, KYN/TRP, KYNA/KYN, and KYNA/QA ratios. Furthermore, urinary concentration of 5-HIAA was negatively correlated with Migraine Disability Assessment score, monthly migraine, and monthly headache days. A negative correlation between Patient Health Questionnaire 9 scores assessing depression. In conclusion, the urinary 5-HIAA level may be an easy-to-determine marker of migraine occurrence and severity and may contribute to the identification of migraine patients with depression.

Background: Reliable HPV testing and genotyping are essential for quality assurance in HPV-based primary screening, disease management and for monitoring the impact of HPV vaccination. The clinical validation of HPV molecular diagnostic assays has significantly contributed to these objectives, however little emphasis has been placed in assuring sample quality. This study aims to assess the accuracy of sample cellularity assessment using C-C Motif Chemokine Receptor 5 (CCR5) gene target as a marker of sample adequacy in molecular diagnostics. Methods: Jurkat cell line samples were counted both using Thoma cell-counting chamber and Fluorescent-Activated Cell Sorting (FACS). Jurkat cell line samples at three different concentrations were subsequently evaluated using the OncoPredict HPV Quality Control (QC) real-time PCR assay, employing CCR5 for molecular cellularity quantification. Results: Cellularity values obtained were comparable across the 3 different methods for all dilutions of the cell line tested. Conclusions: The results obtained from this study show that CCR5 represents a promising molecular marker for the accurate quantification of sample cellularity, confirming its use as a reliable sample adequacy control, thus reducing the risk of “false negative” results.

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which provides powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.

A series of conditions can mimic musculoskeletal infections on imaging, complicating their diagnosis and affecting the treatment. Depending on the anatomical location, different conditions can manifest with clinical and imaging findings that mimic infections. Herein we present a wide spectrum of the musculoskeletal disorders of the axial skeleton, long bones, peripheral joints and soft-tissue which may manifest as an infectious process, besides focusing on the potential mimics of osteomyelitis, septic arthritis and infectious spondylodiscitis that are common in clinical practice. We present the typical imaging characteristics of each musculoskeletal infection, followed by mimicking conditions.

Traditional photodynamic therapy (PDT) is often limited in its efficacy by insufficient light penetration, inefficient photosensitizer energy transfer, and inadequate target tissue oxygenation. X-ray activated PDT (XPDT), using nanoparticle (NPs) photosensitizers comprised of europium-doped yttrium oxide cores encased within silica shells (Y₂O₃:Eu@SiO₂), offers the potential of overcoming most of these limitations. Aimed at maximizing the generation of reactive oxygen species (ROS), this study reports methodologies for investigation of the effects of synthesis conditions on the characteristics of Y₂O₃:Eu@SiO₂ NP. Transmission electronic microscope (TEM) revealed that the NP core diameter was linearly, positively correlated with condensation time (R2 = 0.7357, p < 0.05) and linearly, negatively correlated with urea concentration (R2 = 0.958, p < 0.05). The addition of cetyltrimethylammonium bromide (CTAB) during core synthesis demonstrated enhanced particle dispersion. Silica coating via APTES-1 and TEOS-3 conditions resulted in Y₂O₃:Eu@SiO₂ NPs that generated the highest ROS, with 8.7-fold and 8.9-fold increase respectively in relative fluorescence intensity at 8 Gy irradiation compared to a 5.2-fold increase in PBS under the same condition. In vivo evaluation using 18F-fluorothymidine positron emission tomography (18F-FLT PET) of mouse xenografts of a human prototypical cancer (ovarian) revealed a 55% reduction in tumor proliferation of radiation-sensitive CAOV3 tumors treated with Y₂O₃:Eu@SiO₂ NPs compared to a 19% reduction in tumor proliferation of radiation-resistant SKOV3 tumors on the fourth day post-treatment. Taken together, these findings suggest Y₂O₃:Eu@SiO₂ NPs can serve as effective photosensitizers for XPDT and their performance characteristics can be optimized by selecting synthesis conditions and parameters to deliver the desirable therapeutic effects, offering novel approaches to circumventing many of the limitations of conventional PDT in the treatment of cancer.

D-dimer testing in combination with clinical assessment is commonly used to diagnose suspected DVT and pulmonary embolism. However, as D-dimer levels are physiologically higher in elderly patients, this test loses clinical specificity in the setting of geriatric patients. The aim of our study was to investigate the changes in D-dimer levels with age and the specificity of the D-dimer test in the diagnosis of pulmonary embolism. 1617 elderly patients consecutively admitted to the Geriatric Emergency Care Department of the INRCA-IRCCS hospital between January 2013 and February 2014 and for whom D-dimer results were available were included. The D-dimer immunoturbidimetric assay was performed on a cs-2100i Sysmex Siemens using a conventional cut-off level of 500 µg/L. The median D-dimer level was 1200 [550-2990] µg/L FEU, and the percentage of patients with D-dimer levels below the conventional cut-off was only 22.1%. As expected, there was a significant age-related increase in D-dimer, even when sex was considered, and a significant decrease in the specificity of D-dimer assay with age. The most established use of D-dimer testing is in the diagnosis of deep vein thrombosis or pulmonary embolism. Our study confirms the need for an age-adjusted cut-off for D-dimer testing in geriatric patients.

Ultrasound (US) scans of the inferior vena cava (IVC) provide useful information on the volume status of a patient. However, their investigation is user-dependent and prone to measurement errors. An important technical problem is the objective difficulty in studying a very compliant blood vessel like IVC, which makes large respirophasic movements and shows a complicated three dimensional geometry. Using bi-dimensional (2D) B-mode views either in long or short axis has improved the characterization of IVC dynamics compared to a measurement along a single direction (M-mode). However, specific movements of the IVC can challenge also the information provided by these 2D sections. Thus, these two orthogonal views, provided by an US system in X-plane, are here integrated by an innovative method. It is tested on simulated videos of the IVC performing complicated movements, that are compensated by the new method, overcoming the biased measurements provided by 2D scans. The method is then applied on example experimental data.

The advent of AI in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. With the growing number of AI applications and commercially available tools, there is an increase in their usage in orthodontic practices worldwide. This review aims to explore the principles of artificial intelligence (AI), its applications in the diagnostic process of modern orthodontic practices, and concerns associated with the implementation of AI algorithms in clinical practice. A comprehensive review of the literature was conducted, focusing on five categories where AI has been applied in orthodontics: dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, and extraction decision making. AI has demonstrated high efficacy in all those fields. However, variations in performance and the necessity of manual supervision indicate that AI should be used cautiously in clinical settings. Nevertheless, the high complexity and potential unpredictability of AI algorithms call for cautious implementation and regular manual validation of results. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for the successful integration of AI into orthodontic practice.

A time-sequential working, spatially multiplexed autostereoscopic 3D display design consisting of a fast switchable RGB-color filter array is presented. The wavelength-selective filter barrier emits the light from a display over a larger active area than common autostereoscopic barrier displays. An optical modelling of wavelength-selective barriers has been used for instance to calculate the light ray distribution properties of that arrangement. To find well working display designs, automated searches by simulation and computational evaluation has been proceeded. Wavelength-selective filter barrier arrangements exhibit characteristics different from common barrier displays with similar barrier pitch and ascent. In particular, these constructions show strong angular luminance dependency under barrier inclination specified by correspondent slant angle. In time-sequential implementation it is important to avoid that quick eye or eyelid movement lead to visible color artifacts. In the millisecond regime tunable liquid crystal Fabry-Pérot color filters for the colors red, green and blue are presented. They consist of a sub-micrometer thick nematic layer sandwiched between dielectric mirrors and ITO-electrodes. These cells shall switch narrow-banding light of red, green or blue. An array for a glasses-free 3D display has to be equipped with several thousand switchable filter elements having different color apertures. The newly introduced design is usable as a multi user display as well as a single user system with user adaptive control.

Mitral regurgitation (MR) is a broadly diffuse valvular heart disease (VHD) with a significant impact on healthcare system and patient’s prognosis. Transcatheter mitral valve interventions (TMVI) are now well-established techniques included in the therapeutic armamentarium for managing patients with mitral regurgitation, either primary or functional MR. Even if guidelines give indications regarding the correct management of this VHD, the wide heterogeneity of patient’s clinical background, valvular and heart’s anatomy make each patient a unique case, in which the appropriate device’s selection requires a multimodality imaging evaluation and a multidisciplinary discussion. Proper pre-procedural evaluation plays a pivotal role to judge the feasibility of TMVI, as well as a cooperative works between imagers and interventionalist is crucial for procedural success. This manuscript aims to provide an exhaustive overview of the main parameters that need to be evaluated for appropriate device selection, pre-procedural planning, intraprocedural guidance and post-operative assessment in the setting of TMVI. In addition, it tries to give some insights about next perspective of structural cardiovascular imaging.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Traumatic vascular injuries consist in direct or indirect damage to arteries and/or veins and accounts for 3% of all traumatic injuries. Typical consequences are hemorrhage and ischemia. Extremities vascular injuries can occur isolated or in association in major trauma with other organ injuries. They account for 1-2% of patients admitted to Emergency Department, for approximately 50% of all arterial injuries. Lower extremities are more frequently injured than the upper ones in adult population. The outcome of vascular injuries is strictly correlated to the environment and the time background. Treatment can be challenging notably in polytrauma because of the dilemma of which injury should be prioritized and treatment delay can cause disability or even death especially for limb vascular injury. Our purposes are to discuss the role of Computed Tomography Angiography (CTA) in the diagnosis of vascular trauma and its optimized protocol to achieve the definitive diagnosis, and to assess the radiological signs of vascular injuries and the possible pitfalls.

The growing expansion of the economy and population has resulted in an increased inclination towards the utilization of groundwater resources. Conducting a geophysical survey is a widely employed method for subsurface mapping and the detection of groundwater. A geophysical study was conducted in Nanshan township, Huarong County, located in the Hunan province of the South-Central region of China. The investigation involved the utilization of a 2D Electrical Resistivity Imaging technique employing forward and inverse pole-dipole electrode array. A total of six survey lines were established, each with an electrode distance from the nearest measuring point to exceeding 800 m. The maximum current electrode separation was utilized in this setup. The spacing between the electrical resistivity sounding points was established at regular intervals. The findings from the exploration indicate the existence of multiple faults within the surveyed region. The study additionally identified two regions of structural failure, which occurred due to the convergence of faults oriented in different directions. This convergence led to the fracturing of rocks, an increase in water content, and a decrease in resistivity. The findings from the exploration were utilized in the formulation of five verification target boreholes. The results of this study offer significant insights that can inform future investigations into groundwater exploration endeavors within the region.

Motor intention is a high-level brain function related to planning for movement. Although studies have shown that motor intentions can be decoded from brain signals before movement execution, it was unclear whether intentions relating to mental imagery of movement could be decoded. Here, we investigated whether differences in spatial and temporal patterns of brain activation were elicited by intentions to perform different types of motor imagery and whether the patterns could be used by a multivariate pattern classifier to detect such differential intentions. The results showed that it is possible to decode intentions before the onset of different types of motor imagery from functional MR signals obtained from fronto-parietal brain regions, such as the premotor cortex and posterior parietal cortex, while controlling for eye movements and for muscular activity of the hands. These results highlight the critical role played by the aforementioned brain regions in covert motor intentions. Moreover, they have substantial implications for rehabilitating patients with motor disabilities.

The combination of immunoPET—where an antibody (Ab) is labeled with an isotope for PET imaging—and radioimmunotherapy (RIT), using the same antibody with a therapeutic isotope, offers significant advantages in cancer management. ImmunoPET allows non-invasive imaging of antigen expression, which aids in patient selection for a subsequent radioimmunotherapy. It also facilitates the assessment of tumor response to therapy, allowing for treatment adjustments if necessary. In addition, immunoPET provides critical pharmacokinetic data, including antibody biodistribution and clearance rates, which are essential for dosimetry calculations and treatment protocol optimization. There are still challenges to overcome. Identifying appropriate target antigens that are selectively expressed on cancer cells while minimally expressed on normal tissues remains a major hurdle to reduce off-target toxicity. In addition, it is critical to optimize the pharmacokinetics of radio-labeled antibodies to maximize tumor uptake and minimize normal tissue uptake, particularly in vital organs such as the liver and kidney. This approach offers the potential for targeted and personalized cancer therapy with reduced systemic toxicity by exploiting the specificity of monoclonal antibodies and the cytotoxic effects of radiation. However, further research is needed to address remaining challenges and to optimize these technologies for clinical use.

Delineating the epidemic of vaccine injury from the coterminous condition long covid is a challenging prospect, but one with many implications not just for treatment, but also has important legal considerations for settlements of vaccine injury. The shared etiological factor of the spike protein in both vaccine injury and long covid make differentiation difficult, and while treatment is largely similar between vaccine injury and long covid, there are important distinctions. Furthermore, diagnostics are important for monitoring treatment progress and assessing the extent of subclinical vaccine injury in population having received a covid-19 vaccine. The development of rigorous diagnostics is an important step towards the recognition of both long covid and vaccine injury, as those suffering these conditions have faced immense challenges in having their conditions recognized, treated, and compensated by insurance companies or national health services.

Many fields of human activity benefit from the ability to create images of obscured objects placed behind walls and to map their displacement in a noninvasive way. Usually, imaging devices like Synthetic Aperture Radars (SAR) and Ground Penetrating Radars (GPR) use expensive dedicated electronics which results in prohibitive prices. This paper presents the experimental implementation and the results obtained from an imaging system capable of performing SAR imaging and interferometric displacement mapping of targets located behind walls, as well as 3D GPR imaging using a low-cost general-purpose radar sensor. The proposed solution uses for the RF section of the system a K-band microwave radar sensor module implementing Frequency Modulated Continuous Wave operation. The low-cost sensor was originally intended for simple presence detection and ranging for domestic applications. The proposed system was tested in several scenarios and proved to operate as intended for a fraction of the cost of a commercial imaging device.

Type 2 Diabetes Mellitus is a chronic metabolic disease that poses a significant long-term health risk due to its debilitating complications. While the diagnosis and monitoring of diabetes are well-established, the monitoring of its numerous complications presents a challenge, which can compromise patients' prognosis and quality of life. We analyzed the proteome of ten saliva samples, five from healthy individuals and five from patients with Type 2 Diabetes Mellitus. The aim was to identify potential biomarkers of Type 2 Diabetes Mellitus and its complications. We used PANTHER and FUNRICH tools to conduct a functional analysis and enrichment approach. Our findings revealed 622 proteins involved in 16 disrupted biological processes, which are linked to Type 2 Diabetes Mellitus. Metabolic processes, response to stimuli, processes of the immune system, and signaling are notable due to their known relation with Type 2 Diabetes Mellitus. Enrichment analysis has revealed that there are eleven biological processes that have been deregulated. These processes involve twenty different salivary proteins that are associated with multiple complications in diabetes. Our findings demonstrate that saliva is a dependable source of possible biomarkers that can be used to monitor diabetes and its complications.

Sports traumatic brain injury (TBI) accounts for up to 20% of all sports injuries, and the number of cases is growing year by year due to an increase in the number of people involved in sports, the growing popularity of extreme and contact sports, as well as a high level of motivation to achieve record results. Mild TBI dominates, which can provoke the development of a very wide range of complications and negative consequences. In the programs for the prevention of complications and the rehabilitation of athletes after TBI, TBI features are not sufficiently considered, which significantly differ from household, road or criminal injuries. There are no instrumental methods for diagnosing the severity of the injury. Sports TBI is characterized by repeated frequent TBI, elevated body and brain temperature, peripheral redistribution of blood flow and hypocapnia, which significantly affect cerebral blood flow. Brain injury is an independent cause of the development of cerebral hyperthermia, which significantly worsens the consequences of TBI. To diagnose sports TBI, the method of microwave radiometry of the brain (MWR) can be used. For the prevention of complications, the technology of craniocerebral hypothermia (CCH), which allows for to reduce of physical general and cerebral hyperthermia, and increases the resistance of cerebral cortex neurons to hypoxia and trauma could be used However, these approaches in sports medicine are used sporadically, which, is due to the lack of awareness of coaches and doctors of sports teams. The purpose of the review is to present MWR and CCH in sports TBI.

The progression of the recent COVID-19 pandemic surprised political authorities as well as scientists. The possibility to design powerful strategies for health care and preserving economic and social activities strongly relies on the capacity to monitor correctly the virus spreading and the immune response in the symptomatic and asymptomatic population. The available data relative to the first pandemic months indicate that the test reliability was progressively improved but also that the extremely variable methodologies used in the diagnostic studies generated data that are often not comparable. This condition prevents a simple metadata analysis for the identification of reliable diagnostics guidelines. Nevertheless, there are converging evidences that combinations of complementary approaches may enable more precise identification of virus infection. Furthermore, it appears that the similarities between SARS-CoV2 and the related types SARS-CoV1 and MERS that caused outbreaks in the last 20 years can be exploited to infer some information for which no direct evidence is still available

Localized protein translation occurs through trafficking of mRNAs and protein translation machineries to different compartments of the cell, leading to rapid on-site synthesis of proteins in response to signaling cues. The spatiotemporally precise nature of the local translation process necessitates continual developments of technologies reviewed herein to visualize and map biomolecular components and the translation process with better spatial and temporal resolution, and with fewer artifacts. We also discuss approaches to control local translation, which can serve as a design paradigm for subcellular genetic devices for eukaryotic synthetic biology.

Camouflage is a natural or artificially process to prevent an object from being detected while camouflage breaking is a countering process for the identification of the concealed object. We report that a perfectly camouflaged object in a two-dimensional scene can be retrieved and detected with stereo-vision assisted three-dimensional (3D) imaging perceived with stereopsis. The analysis is based on binocular energy model applied to general 3D settings. We show that a perfectly concealed object with random noise background can be retrieved with vision’s stereoacuity to resolve the hidden structures. The theoretical analysis is further tested and demonstrated with distant natural images taken by a drone-camera, processed with a computer and displayed in an autostereoscopy. The recovered imaging is presented with removal of the background interference to demonstrate the general applicability for camouflage breaking with stereo imaging and sensing.

Background and Objectives: Fibrillinopathies have different phenotypic expression: Marfan- like skeleton features, MLSF; mitral valve prolapse syndrome, MVPS; MASS phenotype, M= mitral valve prolapse, MVP, A= aortic root dilation, S= skeletal features, and the second S= (cutaneous) striae; Marfan syndrome, MS. These are inherited connective tissue diseases, provoked by a mutation of the encoding gene for a protein(fibrillin 1, FBN1) which has major importance in the formation of elastic fibers.The study had the following main objectives: the correlation between disc displacement, DD( a major sign for temporomandibular joint dysfunction, TMD) on magnetic resonance imaging, MRI, and aortic Z score(a major sign for aortic root dilation) on echocardiography; the predictive value of DD towards aortic Z score. DD had 2 types of severity: DD with reduction(the mild type, DDwR) , and DD without reduction( the severe type, DDwoR). Materials and Methods: The type of fibrillinopathy was precised by clinical exam( systemic score), ophthalmic exam(for ectopia lentis), and echocardiography(aortic Z score, MVP). Medical treatment consisted in betablockers, BB(for patients with tachycardia), or angiotensin II receptor blockers, ARB. Surgical treatment was addressed to aortic root aneurysm, and severe MR. DD benefited by dental conservatory treatment, or surgical restoration.Results: DD- Z score had a powerful correlation in MASS(Rho= 0.787, p&lt; 0.01), and in MS patients(Rho=0.819, p&lt; 0.01). For the entire sample, both DDwR- Z score, and DDwoR- Z score had a moderate correlation(Rho= 0.469, and respectively 0.669). Muchmore, DD was an important predictor for Z score. DDwoR had a double power of prediction for Z score, comparative with DDwR(B coefficient= 1.661 for DDwR, and 3.281 for DDwoR). Conclusions: TMD had a powerful correlation with aortic root dilation, in MASS, and MS patients from the sample. Likewise, TMD was a major predictor for aortic root dilation, in the entire sample. We can utilize in clinical practice, an extracardiac finding, TMD, obtained by a non-invasive technique, MRI, for cardiac severity stratification of fibrillinopathies.

Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. Early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings pose challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we developed a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieved the highest performance with accuracy, sensitivity, specificity, and combined AUC of 0.93±0.04, 0.94±0.04, 0.93±0.08 and 0.97 respectively in a 5-fold cross-validation study with pulmonary sarcoidosis (n=126) and LCa (n=93) cases. The model offers promising potential for improving the diagnosis of pulmonary sarcoidosis. A detailed ablation study showing the impact of CNN+ViT compared to CNN or ViT alone, and CT+radiomics input, compared to CT or radiomics alone, is also presented in this work.

Scedosporium species are human pathogenic fungi, responsible for chronic, localised, and life-threatening disseminated infections in both immunocompetent and immunocompromised individuals. Diagnosis of Scedosporium infections currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Scedosporium-specific biomarkers. Here we report the development of a rapid (30 min) and sensitive (pmol/L sensitivity) lateral-flow device (LFD) test, incorporating a Scedosporium-specific IgG1 monoclonal antibody (mAb), HG12, which binds to extracellular polysaccharide (EPS) antigens of between ~15 kDa and 250 kDa secreted during hyphal growth of the pathogens. The test is compatible with human serum, and allows the detection of the Scedosporium species most-frequently reported as agents of human disease (Scedosporium apiospermum, Scedosporium aurantiacum, and Scedosporium boydii), with limits of detection (LOD) of the EPS biomarkers in human serum of ~0.81 ng/mL (S. apiospermum), ~0.94 ng/mL (S. aurantiacum), and ~1.95 ng/mL (S. boydii). The Scedosporium-specific LFD (ScedLFD) test therefore provides a potential novel opportunity for the detection of infections caused by different Scedosporium species.

Ovarian cancer is the third most common female genital cancer. Therefore, the timely diagnosis and comprehensive treatment of postmenopausal patients with benign ovarian tumors remains crucial in the field of gynecology. The significance of ovarian tumors depends on their frequency and their effects on the quality of life of a woman, as well as the possible development of ovarian cancer. Most ovarian cancers are diagnosed late and as a result are difficult to treat and often carry a poor prognosis. Currently there is no clear algorithm available for examining and accurately diagnosing patients with postmenopausal ovarian tumors; moreover, reliable criteria allowing dynamic observation and determining surgical access and optimal surgical intervention measures in postmenopausal patients is lacking.

AbstractWhile the technology is relatively new, low cost 3D printing has impacted many aspects of human life. 3D printers are being used as manufacturing tools for a wide variety of devices in a spectrum of applications ranging from diagnosis to implants to external prostheses. The ease of use and availability of 3D design software and low cost has made 3D printing an accessible manufacturing and fabrication tool in many research laboratories. 3D printers can print materials with varying density, optical character, strength and chemical properties providing platforms for a huge number of strategies that can be chosen for user’s needs. In this review, we focus on applications in biomedical diagnostics and how this revolutionary technique is facilitating development of low cost, sensitive and often geometrically complex tools. 3D printing in fabrication of microfluidics, supporting equipment, optical and electronic components of diagnostic devices is presented. Emerging diagnostic 3D bioprinting as a tool to incorporate living cells or biomaterials into 3D printing is also discussed.

The influence of playing formations and team ranking on the physical performance of professional soccer players is an open question that needs to be explored. The present study aimed to investigate the impact of these factors on the physical exertion of Serie A soccer players. We analyzed match data from 375 players, categorizing teams based on their final ranking and comparing performance across different playing formations. Krustal-Wallies test, and Dunn test with Bonferroni adjustment, revealed that high-ranking (HR) teams exhibited a higher percentage of high-intensity (HI) accelerations compared to mid-ranking teams, suggesting the critical role of HI efforts in achieving favorable match outcomes. Moreover, the 4-3-3 playing formation was associated with greater acceleration demands than other formations, particularly in HR teams. Our study also established benchmarks for various performance metrics, enabling coaches to assess player performance and identify potential signs of overtraining. These findings contribute to a deeper understanding of the physical demands in soccer and offer practical implications for coaches and players in optimizing training and performance strategies.

Breast cancer prevention is very important for a woman's health worldwide. We have demonstrated a correlation between mammography and ultrasound with diagnoses using passive microwave radiometry (MWR) and a miRNA oncopanel. While mammography screening dynamics could be completed in 3-6 months, MWR will provide us with a prediction in a matter of weeks or even days with the potential for complementary miRNA diagnostics. An early breast cancer diagnosis may be accomplished using either one of these novel techniques alone or in conjunction with more established techniques

Zika virus (ZIKV) co-circulates with several closely related flaviviruses which exhibit similar clinical manifestations thus, clinicians rely on molecular and serological techniques for diagnosis. Cross-reactivity of patient specimens to flaviviruses is a significant impediment to serological diagnosis in areas where multiple flaviviruses co-circulate. Furthermore, patient exposure history to any of these viruses could complicate serological response patterns which could result in over and/or underdiagnosis of ZIKV infection. Three strains of ZIKV, dengue serotypes 1-4, West Nile virus, Japanese Encephalitis virus, and Yellow Fever virus were evaluated for neutralizing properties against 3 monoclonal antibodies, 4 ZIKV-naïve patients with flavivirus exposure history, 5 patients with verified ZIKV exposure and unknown flavivirus exposure history, and 5 flavivirus-naive patients with ZIKV-only exposure. Patients naïve for ZIKV exposure effectively neutralized multiple strains of ZIKV. Overall, the prototype ZIKV isolate MR-766 did not behave like the other ZIKV isolated used in this study. MR-766 was neutralized more completely by polyclonal patient serum than recent ZIKV isolates. MR-766 was neutralized better than dengue virus in ZIKV-naïve patients with prior dengue exposure. MR-766 was neutralized significantly less than recent ZIKV isolates when treated with monoclonal antibodies. The data herein show that without RT-PCR, serological diagnosis may not be possible in areas where multiple flaviviruses are endemic.

Background/Objectives: Although the role of F-18 FDG PET/CT imaging is well established in oncology, its diagnostic value in routine monitoring for recurrent colorectal cancer (CRC) is still controversial. The aim was to evaluate the diagnostic value of FDG PET/CT in detecting recurrent CRC in correlation with CEA, CA 19-9 levels, and conventional imaging modalities (CIM). Methods: Between 2009 and 2023, we retrospectively studied 134 CRC patients referred for FDG PET/CT imaging on the suspicion of recurrence based on elevated CEA and/or CA 19-9, and/or equivocal radiological findings. According to the Institutional Tumor Board CRC protocol, after initial treatment which was dependent on TNM stage (neoadjuvant therapy, primary resection or adjuvant treatment), patients underwent a standard 5-year surveillance including CEA and CA 19-9 measurements, CIM, and colonoscopy every 6 months. The statistics including univariate and multivariable analyses were conducted using the IBM SPSS 20.0 statistical software. P-values <0.05 were considered statistically significant. Results: Recurrent CRC was confirmed in 54/134 (40.3%) patients with elevated tumor markers. FDG PET/CT shows high diagnostic performance in detecting recurrent CRC with sensitivity, specificity, PPV, NPV, and accuracy of 94.4%, 82.5%, 78.5%, 95.7%, and 87.3%, respectively. The CEA shows a high sensitivity of 98.1%, but both low specificity and accuracy of 15% and 48.5%, respectively. The sensitivity, specificity, and accuracy, for CA 19-9 and CIM for the correct diagnosis in CRC patients were: 44.4%, 67.5%, 58.2%, and 51.9%, 98.8%, 79.9%, respectively. The AUC for FDG PET/CT, elevated CEA levels, CIM, and elevated CA 19-9 levels was 0.885 (95% CI: 0.824-0.946; p<0.001), 0.844 (95% CI: 0.772-0.916; p<0.001), 0.753 (95% CI: 0.612-0.844; p<0.001); and 0.547 (95% CI: 0.442-0.652; p=0.358). Univariate analysis shows that both FDG PET/CT- and CIM-positive results were highly associated with CRC recurrence (p<0.001 and p<0.001, respectively), while gender, mucinous tumor type, presence of initial lymph node metastasis (N+), and presence of initial distant metastasis (M+) have no significance (p=0.211, p=0.158, p=0.583, and p=0.201, respectively). Our multivariate analysis shows that independent predictors for CRC recurrence are: positive FDG PET/CT scans (p<0.001), positive CIM results (p=0.001) and elevated CA19-9 levels (p=0.023). Although CA 19-9 was not detected as a statistically significant predictor in the univariate analysis (p=0.358), in a multivariate analysis it was recognized as a significant predicting factor in detecting CRC recurrence (p=0.023). Conclusions: FDG PET/CT shows a high diagnostic efficacy in CRC recurrence detection, in correlation with CEA levels, CA 19-9 levels, and CIM. This imaging modality should be routinely integrated into the postoperative follow-op in patients with elevated tumor markers.

Backyard chickens often suffer from foot pad dermatitis (FPD), a condition exacerbated by poor husbandry, nutritional deficiencies, and obesity. Pressure-relieving bandages, commonly used in treatment of FPD, are impractical for outdoor chickens as they quickly become wet and dirty, necessitating daily changes which are often unfeasible. This retrospective study explores the use of custom-fit silicone shoes, created via 3D-printed molds, as an alternative to traditional bandages. CT scans were used to design shoes, adapted from a design used for birds of prey. Over three years, 16 chickens with varying degrees of FPD were treated. The results demonstrated that sili-cone shoes were an effective treatment for FPD, allowing outdoor activity, and facilitated daily lesion care without frequent bandage changes. The median shoe-wearing period was 14 days, and most owners provided positive feedback. Despite some attachment issues, the occurrence of sec-ondary pressure marks and feather regrowth challenges, the silicone shoes offered better ventila-tion, reusability, and consistent pressure relief compared to traditional bandages. This study con-cludes that silicone shoes are a viable solution for managing FPD in backyard chickens, promoting faster healing and improved owner compliance.

This study re-introduces a protein-free rapid test method for nucleic acids on paper based lateral flow assays utilizing special multichannel nitrocellulose membranes and DNA-Gold conjugates, achieving significantly enhanced sensitivity, easier protocols, reduced time of detection, reduced costs of pro-duction and advanced multiplexing possibilities. It is shown for the first time a protein-free nucleic acid based lateral flow assay (NALFA) with a limit of detection of 1 pmol of DNA. The total production duration of such an assay was successfully reduced from the currently known several days to just a few hours. The simplification and acceleration of the protocol make the method more accessible and practical for various applications. The developed method supports multiplexing, enabling the sim-ultaneous detection of up to six DNA targets. This multiplexing capability is a significant improve-ment over traditional line tests and offers more comprehensive diagnostic potential in a single assay. The approach significantly reduces the run time compared to traditional line tests, which enhances the efficiency of diagnostic procedures. The protein-free aspect of this assay minimizes the prevalent complications of cross-reactivity in immunoassays especially in cases of multiplexing. It is also demonstrated that the NALFA developed in this study is amplification-free and hence does not rely on specialized technicians, nor does it involve labour-intensive steps like DNA extraction and PCR processes. Overall, this study presents a robust, efficient, and highly sensitive platform for DNA or RNA detection, addressing several limitations of current methods documented in the literature. The advancements in sensitivity, cost reduction, production time, and multiplexing capabilities mark a substantial improvement, holding great potential for various applications in diagnostics, forensics, and molecular biology.

Dendritic cell (DC) cancer vaccines are a promising therapeutic approach, leveraging the immune system to fight tumors. These vaccines utilize DCs' ability to present tumor-associated antigens to T cells, triggering a robust immune response. DC vaccine development has progressed through three generations. The first generation involved priming DCs with tumor-associated antigens or messenger RNA outside the body, showing limited clinical success. The second generation improved efficacy by using cytokine mixtures and specialized DC subsets to enhance immunogenicity. The third generation uses blood-derived DCs to elicit a stronger immune response. Clinical trials indicate that cancer vaccines have lower toxicity than traditional cytotoxic treatments. However, achieving significant clinical responses with DC immunotherapy remains challenging. Combining DC vaccines with immune checkpoint inhibitors (ICIs) such as anti-cytotoxic T-lymphocyte Antigen 4 and anti-programmed Death-1 antibodies has shown promise by enhancing T cell responses and improving clinical outcomes. These combinations can transform non-inflamed tumors into inflamed ones, boosting ICIs' efficacy. Current research is exploring new checkpoint targets like LAG-3, TIM-3, and TIGIT, considering their potential with DC vaccines. Additionally, engineering T cells with chimeric antigen receptors or T cell receptors could further augment the anti-tumor response. This comprehensive strategy aims to enhance cancer immunotherapy, focusing on increased efficacy and improved patient survival rates.

Post-acute COVID-19 vaccination syndrome (PACVS) is distinguished from the normal post-vaccination state by altered receptor antibodies (Semmler et al. Vaccines 2023, 11, 1642). Here, we explore the symptoms registry and standard serum markers acquired in the above study to delineate the disease phenotype of PACVS. Symptoms reported by the participants overlapped with established complex dysautonomia syndromes (ME/CFS, POTS, MCAS, SFN). However, many participants were qualified for several (131/191) or none (31/191) of these syndromes. Unbiased clustering (modified Jaccard index) revealed a prevalent cross-cohort symptomatology of malaise and chronic fatigue (&gt; 80% of cases). Overlapping clusters of (i) peripheral nerve dysfunction, dysesthesia, motor weakness, pain, vasomotor dysfunction, (ii) cardiovascular impairment, and (iii) cognitive impairment, headache, optic, oculo-motoric and acoustic dysfunctions were also frequently represented. Conspicuous serum markers encompassed increases in interleukins 6 and 8 and low fT3 levels (&gt; 80%), IgG-subclass imbalances and impaired iron-storage (&gt; 50%), and increases in sNFL (&gt; 30%). Serum markers were not correlated to specific symptoms or symptom clusters. A single and unique cause (i. e. SARS-CoV-2 vaccination) is improbable to trigger several distinct etiologies. Therefore, the symptoms and serological features observed in our study cohort probably represent facets of a single complex syndrome.

FPGA-based data acquisition and processing systems play an important role in modern high-speed, multichannel measurement systems, especially in High-Energy and Plasma Physics. Such FPGA-based systems require an extended control and diagnostics part corresponding to the complexity of the controlled system. Managing the complex structure of registers while keeping the tight coupling between hardware and software is a tedious and potentially error-prone process. Various existing solutions aimed at helping that task do not perfectly match all specific requirements of that application area. The paper presents a new solution based on the XML system description, facilitating the automated generation of the control system’s HDL code and software components and enabling easy integration with the control software. The emphasis is put on reusability, ease of maintenance in case of system modification, easy detection of mistakes, and the possibility of use in modern FPGAs. The presented system has been successfully used in data acquisition and preprocessing projects in High-Energy Physics experiments. It enables easy creation and modification of the control system definition and convenient access to the control and diagnostic blocks. The presented system is an open-source solution and may be adopted by the user for particular needs.

The focus of the presented work was to isolate and characterize circulating endometrial cells (CECs) enriched from peripheral blood (PB) of patients with diagnosed endometriosis to support endometriosis diagnosis and treatment. Material and Methods Blood samples (n=423) were tested for CECs presence. Subsequently, gene expression analysis (GEA) was carried out for CECs. In parallel, the presence and character of CECs was tested during phases of menstrual cycle (MC) (n= 11). CECs were isolated by size-based separation from 2x 8ml PB. Results CECs were detected in 78.4% of blood samples. In line with the revised American Fertility Society (rAFS) classification CECs presence was confirmed in all the acknowledged endometriosis stages: minimal, mild, moderate and severe. Surprisingly, the highest CEC negativity rate was reported for severe disease (21.1%). The highest CEC numbers were detected in the mid-secretory periods of MC, which corresponds with uterine lining decidualization. The cytomorphology of CECs captured during MC is changing between the epithelial, stromal and stem cell-like. CECs captured in mid-secretory period expressed KRT18, NANOG and VIM in higher amounts when compared to the genes in the proliferative phase of MC when KRT19 and ESR1 were mostly observed. GEA of the super-positive CECs samples (1000 CECs/8mL PB) revealed high expression of KRT18, VIM, NANOG and FLT1. The expression of these genes was elevated in the endometriosis tissue samples and endometrioma, too. Conclusion The panel of the identified CECs - genes could be tested in a prospective manner to confirm the predictive value of CECs in endometriosis diagnostics.

A new data processing method based on Machine Learning (ML) algorithms has been developed and tested in clinical environments during COVID-19 trials at the Medical University of South Carolina (MUSC). Breath samples have been collected in 2020–2021 from 100 participants using gas chromatography combined with ion mobility spectrometry (GC-IMS, G.A.S. mbH). Polymerase chain reaction (PCR) tests combined with clinical diagnostics were used as a reference method. Once the ML training-testing cycle is completed, the diagnostics of a single data set may be completed in as little as a few seconds. A convincing difference in the Volatile Organic Compounds (VOS) breath biomarker signature with COVID-19 positive and negative participants has been found. This approach is a generic method that can be applied to data sets collected with other types of hardware, e.g., different settings of GC, GC-MS, GC-GC, or other methods providing high information density in 2-dimensional data sets.

Due to species barriers and poor adaptability to new host environments, few pathogens cause global pandemics. But, SARS-CoV-2 is one exception with its high transmissivity and delayed onset of symptoms. Fortunately, the world was able to tap on the technologies especially the maturing RT-qPCR designed to combat SARS to launch an initial offensive on SARS-CoV-2. These initial efforts may have bought time for scientists to develop more refined diagnostic tests that specifically target SARS-CoV-2. This article describes the effort put forth by the biotech industry and academia in Singapore to develop diagnostic tests that aid the early detection of positive cases, and thereby help contain the virus. Direct tests such as RT-qPCR and antigen rapid test profile the virus nucleic acid and surface proteins, respectively. But, of equal importance in case detection and treatment is serological tests that measure the relative abundance of IgM and IgG which is indicative of infection phase and quality of immune response in positive cases. Other tests such as isothermal amplification, CRISPR-based diagnostics and breath tests are also in development or at initial field deployment, and would undoubtedly provide valuable use experience useful for the development of molecular assays to detect and combat the next pathogen of global concern.

Brain is the most complex organ in the human body and it is divided into two hemispheres - left and right hemispheres. Left hemisphere is responsible for control of right side of our body whereas right hemisphere is responsible for control of left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts in clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal plane, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer's, Autism, Schizophrenia, Lesions and Epilepsy. Therefore, in this paper we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in various neuroimaging techniques (MRI/CT/PET/SPECT), which are utilized for detecting various brain related disorders.

Porphyromonas gingivalis is the major pathogenic bacteria found in the subgingival plaque of patients with periodontitis, leading to neuroinflammation. The bacteria destroy periodontal tissue through its virulence factors which are retained in the bacteria’s outer membrane vesicles (OMV). The purpose of this study was to determine the real time effect of intraperitoneal in-jection of P. gingivalis OMV on the production and expression of inflammatory markers as well as histopathological changes in the central nervous system (CNS) of adult zebrafish. Fol-lowing the LD50 (21 µg of OMV), the zebrafish were injected intraperitoneally with 18 µg of OMV and control group with normal saline at 7 different time points. Brains of experimental zebrafish were dissected at desired time points for colorimetric assays, ELISA and histology. This study discovered that nitric oxide and PGE2 were significantly increased at 45 minutes while IL-1β and IL-6 were expressed at subsequent 12- and 24-hours. respectively. Histopatho-logical changes such as blood coagulation, astrocytosis, oedema, spongiosis, and necrosis were also observed between 6- and 24-hours. The two apoptotic enzymes, caspases 3 and 9 were not expressed at any time point. In summary, the OMV induced neuroinflammatory responses and histopathological changes in adult zebrafish were time point dependent

Aquaculture is expected to play a vital role in solving the challenge of sustainably providing the growing world population with healthy and nutritious food. Pathogen outbreaks are a major risk for the sector, so early detection and a timely response are crucial. This can be enabled by monitoring of pathogen levels in aquaculture facilities. This paper describes a photonic biosensing platform based on silicon nitride waveguide technology with integrated active components, which could be used for such applications. Compared to the state of the art, the current system presents improvements in terms of miniaturization of the Photonic Integrated Circuit (PIC), and the development of wafer level processes for hybrid integration of active components and for material-selective chemical and biological surface modification. Furthermore, scalable processes for integrating the PIC in a microfluidic cartridge have been developed, as well as a prototype desktop readout instrument. Three bacterial aquaculture pathogens (Aeromonas salmonicida, Vagococcus salmoninarum, and Yersinia ruckeri) were selected for assay development. DNA biomarkers were identified, corresponding primer-probe sets designed, and qPCR assays developed. The biomarker for Aeromonas was also detected using the hybrid PIC platform. This is the first successful demonstration of biosensing on the hybrid PIC platform.

This article utilizes the Canny edge extraction algorithm based on contour curvature and the cross-correlation template matching algorithm to extensively study the impact of high-repetition-rate CO2 pulsed Laser on the target extraction and tracking performance of the infrared imaging detector. It establishes a quantified dazzling pattern for lasers on infrared imaging systems. By conducting laser dazzling and damage experiments, a detailed analysis of the normalized correlation between target and dazzling images is performed to quantitatively describe laser dazzling effects. Simultaneously, an evaluation system, including target distance and laser power evaluation factors, is established to determine the dazzling level and whether the target is recognizable. The research results reveal that laser power and target position are crucial factors affecting the detection performance of infrared imaging-guided weapon systems under laser dazzling. Different laser powers are required to successfully interfere with the recognition algorithm of infrared imaging-guided weapons at different distances. And laser dazzling will produce a lot of false edge information, which seriously affects the performance of pattern recognition algorithm. In laser damage experiments, the detector experienced functional damage, with a quarter of the image displaying as completely black. The energy density threshold required for functional damage to the detector is approximately 3 J/cm2. The dazzling assessment conclusions also apply to evaluating damage results. Finally, the proposed evaluation formula aligns with experimental results, objectively reflecting the actual impact of laser dazzling on the target extraction and tracking performance of infrared imaging systems. This study provides an in-depth and accurate analysis for understanding the influence of lasers on the performance of infrared imaging-guided weapons.

Inflammation and immune cell dysfunction are critical facilitators of endometriosis pathophysiology. The diverse cellular fractions in the endometriotic microenvironment are represented mainly by glands and stroma, which are infiltrated by immune cells, including macrophages. Macrophages are renowned for stimulating lesion growth, vascularization, and innervation and contributing to pain in the disorder. By combining macrophages and endometriotic cells, we determined if resveratrol and its natural analogs can target the immune dysregulation and oxidative imbalance in endometriosis. We studied the effect of analyzed compounds on the expression of key inflammatory and oxidative stress markers, cytokines release, and ROS production by applying q-PCR, ELISA, Cytometric Beads Array, and multiplexed fluorogenic staining and flow cytometry analysis with bioimaging. The results showed that endometriosis-related macrophages treated with resveratrol or its derivatives have impaired expression of pro-inflammatory markers such as IL6, IL8, IL1B, TNF, CCL2, CXCL10, and PTGS2. This study also reported a pronounced antioxidant effect of the compounds by reducing the accumulation of free radicals in macrophages, which correlated with the transcript activation of detoxification enzymes (SOD, GPx). Considering the harmful macrophage action in endometriosis, we described the prospects for potential therapy based on regulating the immune microenvironment and reducing the accumulation of free radicals.

Introduction: Although aging is a natural phenomenon, in recent years it has accelerated. One key factor implicated in the aging process is oxidative stress. Oxidative stress play also role in frailty (frail) and metabolic syndrome (MetS). Methods: 66 elderly persons (65 years old and older) with no acute or severe chronic disorders were assessed: waist circumference (WC), arterial blood pressure, glycemia, glycated hemoglobin (HbA1c), plasma lipids and activity of erythrocyte superoxide dismutase (SOD-1). Patients were classified as NonMetS-Nonfrail (n=19), NonMetS-frail (n=20), MetS-Nonfrail (n=17), and MetS-frail (n=10). Results: There were no significant differences in superoxide dismutase activity among investigated elderly groups. However, the data suggests that MetS individuals, both frail and nonfrail, have higher risk factors for cardiovascular disease compared to NonMetS individuals. The correlations analyses of SOD-1 and other metabolic indices suggest that SOD-1 levels may be influenced by age, total cholesterol, HDL cholesterol, and fasting glucose levels in certain groups of seniors. Conclusions: Aging is associated with decreased antioxidant enzyme SOD-1 activity with glucose alteration in frailty syndrome as well as with lipids disturbances in metabolic syndrome.

Increased activity of transforming growth factor-beta (TGF-β) is a key factor mediating kidney impairment in diabetes. Glomerular podocytes, the crucial component of the renal filter, are a direct target of TGF-β action, resulting in irreversible cell loss and progression of chronic kidney disease (CKD). Urolithin A (UA) is a member of the family of polyphenol metabolites produced by gut microbiota from ellagitannins and ellagic acid-rich foods. The broad spectrum of biological ac-tivities of UA makes it a promising candidate for the treatment of podocyte disorders. In this in vitro study, we investigated whether UA influences the changes exerted in podocytes by TGF-β and high glucose. Following a 7-day incubation in normal (NG, 5.5 mM) or high (HG, 25 mM) glucose the cells were treated with UA and/or TGF-β1 for 24 hours. HG and TGF-β1, each independent and in concert reduced expression of nephrin, increased podocyte motility and up-regulated expression of b3 integrin and fibronectin. These typical for epithelial-to-mesenchymal transition (EMT) effects were inhibited by UA in both HG and NG conditions. UA also reduced the typically elevated in HG expression of TGF-β receptors and activation of TGF-β signal transducer Smad2. Our results indicate that in podocytes cultured in conditions mimicking diabetic milieu, UA inhibits and reverses changes underlying podocytopenia in diabetic kidneys. Hence, UA should be considered as a po-tential therapeutic agent in podocytopathies.

Metasurface constitutes one of the most promising technologies for holographic imaging; however, the work for terahertz (THz) metasurface holographic imaging is relatively limited. Here, we propose a THz dielectric geometric-propagation phase metasurface, which can operate dual-mode (reflection and transmission) and reconfigurable multifunctional holographic imaging. The dual-mode is realized by controlling the Fermi energy level (Ef) of the graphene integrated into the metasurface unit, and the reconfigurable three-channel holographic imaging in reflection or transmission mode are achieved by switching the feed polarization among left-handed circular polarization (LCP), right-handed circular polarization (RCP) and linear polarization (LP). The metasurface is designed based on the transmission mode, and a physical model for switching to the reflection mode is established. For the first time to the best of our knowledge, a reflection-transmission dynamic modulation THz holographic imaging metasurface has been developed. The holographic metasurface operates in transmission mode at Ef = 0.1 eV, and in reflection mode at Ef = 0.9 eV. Compared with recently published holographic imaging metasurfaces, the proposed metasurface offers the following advantages: high holographic efficiencies (42.5% to 49%), more holographic imaging channels, dynamic modulation dual-mode operations, and reconfigurability.