Pediatric gallstone disease-Management difficulties in clinical practice.

BACKGROUND: Gallstone disease (GD) is no longer an exclusive condition of adulthood, and its prevalence is increasing in pediatric age. The management and the extent of the etiological investigation of GD in children and adolescents remains controversial. This study aimed to analyze the difficulties in the work-up and management of pediatric GD patients. METHODS: A retrospective study performed in a single tertiary center enrolled sixty-five patients with GD followed from January 2014 to June 2021. Patients were categorized conveniently according to their age at diagnosis: Group A (<10years, n=35) and Group B (≥10years, n=30). We analyzed demographic, clinical and laboratory data, ultrasonographic findings at presentation, therapeutics and complications. RESULTS: Symptoms were more frequent in patients >10years old (p=0.001). Cholecystectomy was performed in 31 patients (47.7%). A multivariate regression logistic model identified the age >10years (OR=6.440, p=0.005) and underlying entities (OR=6.823, p=0.017) as independent variables to perform surgery. Spontaneous resolution of GD was more common in children <2years old. A multivariate regression logistic model showed a trend for those >10years old to develop more complications. Two out of 18 patients were diagnosed with ABCB4 gene mutations in heterozygosity. CONCLUSIONS: Decision-making on cholecystectomy remains challenging in asymptomatic patients. Identifying predictive factors for the development of complications has proven difficult. However, we found a trend toward the development of complications in individuals older than 10years.

Two-layer reconstruction of Raman spectra in diffusive media based on an analytical model in the time domain.

We derive and validate an analytical model that describes the migration of Raman scattered photons in two-layer diffusive media, based on the diffusion equation in the time domain. The model is derived under a heuristic approximation that background optical properties are identical on the excitation and Raman emission wavelengths. Methods for the reconstruction of two-layer Raman spectra have been developed, tested in computer simulations and validated on tissue-mimicking phantom measurements data. Effects of different parameters were studied in simulations, showing that the thickness of the top layer and number of detected photon counts have the most significant impact on the reconstruction. The concept of quantitative, mathematically rigorous reconstruction using the proposed model was finally proven on experimental measurements, by successfully separating the spectra of silicone and calcium carbonate (calcite) layers, showing the potential for further development and eventual application in clinical diagnostics.

Survival of Zirconium-Based Metal-Organic Framework Crystallinity at Extreme Pressures.

Recent research on metal-organic frameworks (MOFs) has shown a shift from considering only the crystalline high-porosity phases to exploring their amorphous counterparts. Applying pressure to a crystalline MOF is a common method of amorphization, as MOFs contain large void spaces that can collapse, reducing the accessible surface area. This can be either a desired change or indeed an unwanted side effect of the application of pressure. In either case, understanding the MOF's pressure response is extremely important. Three such MOFs with varying pore sizes (UiO-66, MOF-808, and NU-1000) were investigated using in situ high-pressure X-ray diffraction and Raman spectroscopy. Partial crystallinity was observed in all three MOFs above 10 GPa, along with some recovery of crystallinity on return to ambient conditions if the frameworks were not compressed above thresholds of 13.3, 14.2, and 12.3 GPa for UiO-66, MOF-808, and NU-1000, respectively. This threshold was marked by an unexpected increase in one or more lattice parameters with pressure in all MOFs. Comparison of compressibility between MOFs suggests penetration of the pressure-transmitting oil into MOF-808 and NU-1000. The survival of some crystallinity above 10 GPa in all of these MOFs despite their differing pore sizes and extents of oil penetration demonstrates the importance of high-pressure characterization of known structures.

Spatially Offset Raman Spectroscopy-How Deep?

Spatially offset Raman spectroscopy (SORS) is a technique for interrogating the subsurface composition of turbid samples noninvasively. This study generically addresses a fundamental question relevant to a wide range of SORS studies, which is how deep SORS probes for any specific spatial offset when analyzing a turbid sample or, in turn, what magnitude of spatial offset one should select to probe a specific depth. This issue is addressed by using Monte Carlo simulations, under the assumption of negligible absorption, which establishes that the key parameter governing the extent of the probed zone for a point-like illumination and point-like collection SORS geometry is the reduced scattering coefficient of the medium. This can either be deduced from literature data or directly estimated from a SORS measurement by evaluating the Raman intensity profile from multiple spatial offsets. Once this is known, the extent of the probed zone can be determined for any specific SORS spatial offset using the Monte Carlo simulation results presented here. The proposed method was tested using experimental data on stratified samples by analyzing the signal detected from a thin layer that was moved through a stack of layers using both non-absorbing and absorbing samples. The proposed simple methodology provides important additional information on SORS measurements with direct relevance to a wide range of SORS applications including biomedical, pharmaceutical, security, forensics, and cultural heritage.

Estimating the Reduced Scattering Coefficient of Turbid Media Using Spatially Offset Raman Spectroscopy.

We propose a new method for estimating the reduced scattering coefficient, µs', of turbid homogeneous samples using Spatially Offset Raman Spectroscopy (SORS). The concept is based around the variation of Raman signal with SORS spatial offset that is strongly µs'-dependent, as such, permitting the determination of µs'. The evaluation is carried out under the assumptions that absorption is negligible at the laser and Raman wavelengths and µs' is approximately the same for those two wavelengths. These conditions are often satisfied for samples analyzed in the NIR region of the spectrum where SORS is traditionally deployed. Through a calibration procedure on a PTFE model sample, it was possible to estimate the µs' coefficient of different turbid samples with an error (RMSEP) below 18%. The knowledge of µs' in the NIR range is highly valuable for facilitating accurate numerical simulations to optimize illumination and collection geometries in SORS, to derive in-depth information about the properties of SORS measurements or in other photon applications, dependent on photon propagation in turbid media with general impact across fields such as biomedical, pharmaceutical, security, forensic, and cultural sciences.

Multimodal Imaging of Autofluorescent Sites Reveals Varied Chemical Speciation in SSZ-13 Crystals.

A multimodal imaging study of chabazite is used to show the distribution of and discriminate between different emissive deposits arising as a result of the detemplation process. Confocal imaging, 3D fluorescence lifetime imaging, 3D multispectral fluorescence imaging, and Raman mapping are used to show three different types of emissive behaviours each characterised by different spatial distributions, trends in lifetime, spectral signals, and Raman signatures. A notable difference is seen in the morphology of agglomerated surface deposits and larger subsurface deposits, which experience lifetime augmentation due to spatial confinement. The distribution of organic residue throughout the crystal volume is comparable to XRF mapping that shows Si enrichment on the outer edges and higher Al content through the centre, demonstrating that a fluorescence-based technique can also be used to indirectly comment on the compositional chemistry of the inorganic framework.

Plasmonic Nanoassemblies: Tentacles Beat Satellites for Boosting Broadband NIR Plasmon Coupling Providing a Novel Candidate for SERS and Photothermal Therapy.

Optical theranostic applications demand near-infrared (NIR) localized surface plasmon resonance (LSPR) and maximized electric field at nanosurfaces and nanojunctions, aiding diagnosis via Raman or optoacoustic imaging, and photothermal-based therapies. To this end, multiple permutations and combinations of plasmonic nanostructures and molecular "glues" or linkers are employed to obtain nanoassemblies, such as nanobranches and core-satellite morphologies. An advanced nanoassembly morphology comprising multiple linear tentacles anchored onto a spherical core is reported here. Importantly, this core-multi-tentacle-nanoassembly (CMT) benefits from numerous plasmonic interactions between multiple 5 nm gold nanoparticles (NPs) forming each tentacle as well as tentacle to core (15 nm) coupling. This results in an intense LSPR across the "biological optical window" of 650-1100 nm. It is shown that the combined interactions are responsible for the broadband LSPR and the intense electric field, otherwise not achievable with core-satellite morphologies. Further the sub 80 nm CMTs boosted NIR-surface-enhanced Raman scattering (SERS), with detection of SERS labels at 47 × 10-9 m, as well as lower toxicity to noncancerous cell lines (human fibroblast Wi38) than observed for cancerous cell lines (human breast cancer MCF7), presents itself as an attractive candidate for use as biomedical theranostics agents.

Non-invasive depth determination of inclusion in biological tissues using spatially offset Raman spectroscopy with external calibration.

Spatially offset Raman spectroscopy (SORS) allows chemical characterisation of biological tissues at depths of up to two orders of magnitude greater than conventional Raman spectroscopy. In this study, we demonstrate the use of SORS for the non-invasive prediction of depth of an inclusion within turbid media (e.g. biological tissues) using only external calibration data sets, thus extending our previous approach that required internal calibration. As with the previous methodology, the concept is based on relative changes in Raman band intensities of the inclusion that are directly related to the path length of Raman photons travelling through the medium thereby encoding the information of depth of the inclusion. However, here the calibration model is created using data only from external measurements performed at the tissue surface. This new approach facilitates a fully non-invasive methodology applicable potentially to in vivo medical diagnosis without any a priori knowledge. Monte Carlo simulations of photon propagation have been used to provide insight into the relationship between the spatial offset and the photon path lengths inside the tissues enabling one to derive a general scaling factor permitting the use of spatial offset measurements for the depth prediction. The approach was validated by predicting the depth of surface-enhanced Raman scattering (SERS) labelled nanoparticles (NPs) acting as inclusions inside a slab of ex vivo porcine tissue yielding an average root mean square error of prediction of 7.3% with respect to the overall tissue thickness. Our results pave the way for future non-invasive deep Raman spectroscopy in vivo by enabling, for example, the localisation of cancer lesions or cancer biomarkers in early disease diagnosis and targeted treatments.

Spatially Offset and Transmission Raman Spectroscopy for Determination of Depth of Inclusion in Turbid Matrix.

We propose an approach for the prediction of the depth of a single buried object within a turbid medium combining spatially offset Raman spectroscopy (SORS) and transmission Raman spectroscopy (TRS) and relying on differential attenuation of individual Raman bands brought about by the spectral variation of matrix absorption (and scattering). The relative degree of the Raman band changes is directly related to the path length of Raman photons traveling through the medium, thereby encoding the information on the depth of the object within the matrix. Through a calibration procedure with root mean square error of calibration (RMSEC) = 3.4%, it was possible to predict the depth of a paracetamol (acetaminophen) inclusion within a turbid matrix consisting of polyethylene (PE) by monitoring the relative intensity of two Raman bands of paracetamol exhibiting differential absorption by the matrix. The approach was shown to be largely insensitive to variations of the amount of the inclusion (paracetamol) and to the overall thickness of the turbid matrix (PE) with a root mean square error of prediction (RMSEP) maintained below 10% for the tested cases. This represents a major advantage over previously demonstrated comparable depth determination Raman approaches (with the exception of full Raman tomography requiring complex mathematical reconstruction algorithms). The obtained experimental data validate the proposed approach as an effective tool for the noninvasive determination of the depth of buried objects in turbid media with potential applications including determining noninvasively the depth of a lesion in cancer diagnosis in vivo.

Time-Resolved Photoluminescence Microscopy Combined with X-ray Analyses and Raman Spectroscopy Sheds Light on the Imperfect Synthesis of Historical Cadmium Pigments.

Recent studies have shown that modern pigments produced after the Second Industrial Revolution are complex systems characterized by a high level of heterogeneities. Therefore, it is fundamental to adopt a multianalytical approach and highly sensitive methods to characterize the impurities present within pigments. In this work we propose time-resolved and spectrally resolved photoluminescence (PL) microscopy for the mapping of luminescent crystal defects and impurities in historical cadmium-based pigments. PL analysis is complemented by X-ray diffraction, X-ray fluorescence and Raman spectroscopies, and by scanning electron microscopy to determine the chemical composition and crystal structure of samples. The study highlights the heterogeneous and complex nature of historical samples that can be associated with the imperfect manufacturing processes tested during the period between the 1850s and 1950s. The results also allow us to speculate on a range of synthesis processes. Since it is recognized that the stability of paints can be related to pigments synthesis, this research paves the way to a wider study on the relationship between synthesis methods and deterioration of cadmium pigments and paints. This rapid and immediate approach using PL can be applied to other semiconductor pigments and real case studies.

Frequency offset Raman spectroscopy (FORS) for depth probing of diffusive media.

We present a new technique, frequency offset Raman spectroscopy (FORS), to probe Raman spectra of diffusive media in depth. The proposed methodology obtains depth sensitivity exploiting changes in optical properties (absorption and scattering) with excitation wavelengths. The approach was demonstrated experimentally on a two-layer tissue phantom and compared with the already consolidated spatially offset Raman spectroscopy (SORS) technique. FORS attains a similar enhancement of signal from deep layers as SORS, namely 2.81 against 2.62, while the combined hybrid FORS-SORS approach leads to a markedly higher 6.0 enhancement. Differences and analogies between FORS and SORS are discussed, suggesting FORS as an additional or complementary approach for probing heterogeneous media such as biological tissues in depth.

Theoretical and Practical Considerations of Spatially Offset Raman Spectroscopy (SORS) and Micro-SORS.

Spatially offset Raman spectroscopy (SORS) is typically used to non-invasively investigate stratified samples that possess features on a millimeter scale, whereas micro-SORS usually deals with micrometer-thick layered samples. However, there are many instances where these boundaries are intertwined, sometimes indicating the possibility of using both techniques as well as circumstances that present mutual exclusion to their applicability. The aim of this study is to establish an application protocol that provides better insight into their suitability for deployment in various scenarios. The differences and similarities between the two approaches are investigated highlighting their strengths and limitations considering both theoretical and practical aspects. Diverse available parameters entail prospects and restrictions of both techniques and give rise to specific instrumental effects, namely, the overlap between the collection and excitation areas, the percentage of collected area for a given spatial offset, and the accuracy in the definition of the spatial offset (spread effect). These aspects are studied and exemplified on mockup samples relevant to the field of cultural heritage. The samples are characterized by high compositional complexity comprising features ranging from micrometer to millimeter scales. The conclusions reached are also relevant to other scientific areas such as biomedical, forensic, or energy harvest.

Application of Spatial Offset Raman Spectroscopy (SORS) and Machine Learning for Sugar Syrup Adulteration Detection in UK Honey.

Honey authentication is a complex process which traditionally requires costly and time-consuming analytical techniques not readily available to the producers. This study aimed to develop non-invasive sensor methods coupled with a multivariate data analysis to detect the type and percentage of exogenous sugar adulteration in UK honeys. Through-container spatial offset Raman spectroscopy (SORS) was employed on 17 different types of natural honeys produced in the UK over a season. These samples were then spiked with rice and sugar beet syrups at the levels of 10%, 20%, 30%, and 50% w/w. The data acquired were used to construct prediction models for 14 types of honey with similar Raman fingerprints using different algorithms, namely PLS-DA, XGBoost, and Random Forest, with the aim to detect the level of adulteration per type of sugar syrup. The best-performing algorithm for classification was Random Forest, with only 1% of the pure honeys misclassified as adulterated and <3.5% of adulterated honey samples misclassified as pure. Random Forest was further employed to create a classification model which successfully classified samples according to the type of adulterant (rice or sugar beet) and the adulteration level. In addition, SORS spectra were collected from 27 samples of heather honey (24 Calluna vulgaris and 3 Erica cinerea) produced in the UK and corresponding subsamples spiked with high fructose sugar cane syrup, and an exploratory data analysis with PCA and a classification with Random Forest were performed, both showing clear separation between the pure and adulterated samples at medium (40%) and high (60%) adulteration levels and a 90% success at low adulteration levels (20%). The results of this study demonstrate the potential of SORS in combination with machine learning to be applied for the authentication of honey samples and the detection of exogenous sugars in the form of sugar syrups. A major advantage of the SORS technique is that it is a rapid, non-invasive method deployable in the field with potential application at all stages of the supply chain.

Active Surface-Enhanced Raman Spectroscopy (SERS): A Novel Concept for Enhancing Signal Contrast in Complex Matrices Using External Perturbation.

Noninvasive detection of surface-enhanced Raman spectroscopy (SERS) signals from deep within tissue represents a common challenge in many biological and clinical applications including disease diagnosis and therapy monitoring. Such signals are typically weak and not readily discernible from often much larger Raman and fluorescence background signals (e.g., from surrounding tissue). Consequently, suboptimal sensitivity in the detection of SERS signals is often achieved in these situations. Similar issues can arise in SERS measurements in other diffusely scattering samples and complex matrices. Here, we propose a novel concept, active SERS, for the efficient retrieval of SERS signals from deep within complex matrices such as biological tissues that mitigates these issues. It relies on applying an external perturbation to the sample to alter the SERS signal from nanoparticles (NPs) deep inside the matrix. A measurement with and without, or before and after, such perturbation then can provide powerful contrasting data enabling an effective elimination of the matrix signals to reveal more clearly the desired SERS signal without the interfering background and associated artifacts. The concept is demonstrated using ultrasound (US) as an external source of perturbation and SERS NPs inserted deep within a heterogeneous tissue phantom mimicking a cluster of NPs accumulated within a small target lesion. The overall SERS signal intensity induced by the applied US perturbation decreased by ∼21% and the SERS signal contrast was considerably improved by eliminating subtraction artifacts present in a conventional measurement performed at a neighboring spatial location in a heterogeneous tissue sample. Although the technique was demonstrated with SERS gold NPs with a standard Raman label, it is envisaged that active SERS NPs (both the nanoscale metal geometry and Raman label) could be specifically designed to deliver an augmented response to the external stimulus to further enhance the achievable SERS signal contrast and yield even greater improvement in detection sensitivity. The method was demonstrated using transmission Raman spectroscopy; however, it is also applicable to other Raman implementations including spatially offset Raman spectroscopy and conventional Raman spectroscopy performed both at depth and at surfaces of complex matrices.

The Clinical Spectrum of Adrenoleukodystrophy at a Portuguese Tertiary Hospital: Case Series and Review of Literature.

Adrenoleukodystrophy, a rare genetic disease associated with the X chromosome (X-ALD - X-linked adrenoleukodystrophy), predominantly affects males and stems from mutations in the ABCD1 gene, responsible for transporting very long chain fatty acids (VLCFA) into peroxisomes. It leads to adrenal insufficiency (AI) and axonal demyelination. In males, the phenotype varies from isolated adrenocortical insufficiency and progressive myelopathy to cerebral adrenoleukodystrophy (CALD). The aim of this case series is to characterize patients with different clinical presentations of X-ALD with follow-up at a tertiary Portuguese hospital. All four patients were males, and the median age at the diagnosis was 5 years. Three patients were diagnosed through family screening, with the oldest already displaying hyperpigmentation. Two distinct forms were identified: adolescent CALD (25%) and isolated primary adrenal insufficiency (75%). Analytical studies revealed elevated plasma VLCFA levels in all cases, and genetic analysis demonstrated two different mutations in the ABCD1 gene. This disorder requires early diagnosis for improved prognosis. Screening male children with primary AIfor X-ALD using a VLCFA panel should be considered, particularly after ruling out the most common causes or when learning difficulties are evident. Genetic confirmation of the diagnosis is essential, enabling genetic counseling, family planning, and preimplantation genetic diagnosis.

Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening.

The global population is increasingly reliant on vaccines to maintain population health with billions of doses used annually in immunisation programmes. Substandard and falsified vaccines are becoming more prevalent, caused by both the degradation of authentic vaccines but also deliberately falsified vaccine products. These threaten public health, and the increase in vaccine falsification is now a major concern. There is currently no coordinated global infrastructure or screening methods to monitor vaccine supply chains. In this study, we developed and validated a matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS) workflow that used open-source machine learning and statistical analysis to distinguish authentic and falsified vaccines. We validated the method on two different MALDI-MS instruments used worldwide for clinical applications. Our results show that multivariate data modelling and diagnostic mass spectra can be used to distinguish authentic and falsified vaccines providing proof-of-concept that MALDI-MS can be used as a screening tool to monitor vaccine supply chains.

Repurposing rapid diagnostic tests to detect falsified vaccines in supply chains.

Substandard (including degraded) and falsified (SF) vaccines are a relatively neglected issue with serious global implications for public health. This has been highlighted during the rapid and widespread rollout of COVID-19 vaccines. There has been increasing interest in devices to screen for SF non-vaccine medicines including tablets and capsules to empower inspectors and standardise surveillance. However, there has been very limited published research focussed on repurposing or developing new devices for screening for SF vaccines. To our knowledge, rapid diagnostic tests (RDTs) have not been used for this purpose but have important potential for detecting falsified vaccines. We performed a proof-in-principle study to investigate their diagnostic accuracy using a diverse range of RDT-vaccine/falsified vaccine surrogate pairs. In an initial assessment, we demonstrated the utility of four RDTs in detecting seven vaccines. Subsequently, the four RDTs were evaluated by three blinded assessors with seven vaccines and four falsified vaccines surrogates. The results provide preliminary data that RDTs could be used by multiple international organisations, national medicines regulators and vaccine manufacturers/distributors to screen for falsified vaccines in supply chains, aligned with the WHO global 'Prevent, Detect and Respond' strategy.

Rituximab therapy for childhood onset idiopathic nephrotic syndrome: experience of a Portuguese tertiary center.

INTRODUCTION: Rituximab (RTX) is a therapeutic option in pediatric difficult-to-treat idiopathic nephrotic syndrome (NS). We aimed to assess the efficacy and safety of RTX use in these patients. METHOD: A retrospective study of all patients with idiopathic NS treated with RTX was conducted in a pediatric nephrology division of a tertiary hospital. Demographic, anthropometric, clinical and analytical data were collected prior to treatment and at 6, 12, and 24 months. RESULTS: Sixteen patients were included (11 males), with a median (25th-75th percentile, P25-P75) age at diagnosis of 2 (2.0-2.8) years. Fifteen were steroid-sensitive and 1 was steroid-resistant and sensitive to cyclosporine. The median age at administration of RTX was 10 (6.3-14.0) years. Throughout a median follow-up time of 2.5 (1.0-3.0) years, 6 (37.5%) patients achieved partial remission and 7 (43.8%) had no relapses and were not taking any immunosuppressants at the 24-month follow-up visit. Regarding complications, 1 patient presented persistent hypogammaglobulinemia. Compared with the 12-month period before RTX, there was a decrease in the median number of relapses at 6 and 12 months [3 (3.0-4.0) vs 0 (0-0.8) and 0.50 (0-1.0), respectively; p = 0.001] and in the daily steroids dose (mg/kg/day) at 6, 12, and 24 months [0.29 (0.15-0.67)vs [0.10 (0.07-0.13); p = 0.001], [0.12 (0.05-0.22); p = 0.005] and [0.07(0.04-0.18); p = 0.021]], respectively. There was also a reduction in the median BMI z score at 24 months [2.11 (0.45-3.70) vs. 2.93 (2.01-3.98); p = 0.049]. CONCLUSION: Our results confirm the efficacy and safety of RTX use in pediatric idiopathic NS and highlight its' potential cardiometabolic benefits.

10†kHz Shifted-Excitation Raman Difference Spectroscopy with Charge-Shifting Charge-Coupled Device Read-Out for Effective Mitigation of Dynamic Interfering Backgrounds.

In this work we demonstrate an advanced concept of a charge-shifting charge-coupled device (CCD) read-out combined with shifted excitation Raman difference spectroscopy (SERDS) capable of operating at up to 10 kHz acquisition rates for the effective mitigation of fast-evolving interfering backgrounds in Raman spectroscopy. This rate is 10-fold faster than that achievable with an instrument we described previously and is overall 1000-fold faster than possible with conventional spectroscopic CCDs capable of operating at up to ∼10 Hz rates. The speed enhancement was realized by incorporating a periodic mask at the internal slit of an imaging spectrometer permitting a smaller shift of the charge on the CCD (8 pixels) to be required during the cyclic shifting process compared with the earlier design which employed an 80-pixel shift. The higher acquisition speed enables the more accurate sampling of the two SERDS spectral channels, enabling it to effectively tackle highly challenging situations with rapidly evolving interfering fluorescence backgrounds. The performance of the instrument is evaluated for heterogeneous fluorescent samples which are moved rapidly in front of the detection system aiming at the differentiation of chemical species and their quantification. The performance of the system is compared with that of the earlier 1 kHz design and a conventional CCD operated at its maximum rate of 5.4 Hz as previously. In all situations tested, the newly developed 10 kHz system outperformed the earlier variants. The 10 kHz instrument can benefit a number of prospective applications including: disease diagnosis where high sensitivity mapping of complex biological matrices in the presence of natural fluorescence bleaching restricts achievable limits of detection; accurate data acquisition from moving heterogeneous samples (or moving a handheld instrument in front of the sample during data acquisition) or data acquisition under varying ambient light conditions (e.g., due to casting shadows, sample or instrument movement). Other beneficial scenarios include monitoring rapidly evolving Raman signals in the presence of largely static background signals such as in situations where a heterogeneous sample is moving rapidly in front of a detection system (e.g., a conveyor belt) in the presence of static ambient light.

The Association between Childhood Obesity and Cardiovascular Changes in 10 Years Using Special Data Science Analysis.

The increasing prevalence of overweight and obesity is a worldwide problem, with several well-known consequences that might start to develop early in life during childhood. The present research based on data from children that have been followed since birth in a previously established cohort study (Generation XXI, Porto, Portugal), taking advantage of State-of-the-Art (SoA) data science techniques and methods, including Neural Architecture Search (NAS), explainable Artificial Intelligence (XAI), and Deep Learning (DL), aimed to explore the hidden value of data, namely on electrocardiogram (ECG) records performed during follow-up visits. The combination of these techniques allowed us to clarify subtle cardiovascular changes already present at 10 years of age, which are evident from ECG analysis and probably induced by the presence of obesity. The proposed novel combination of new methodologies and techniques is discussed, as well as their applicability in other health domains.