Prior drug allergies are associated with worse outcome in patients with idiosyncratic drug-induced liver injury: A machine learning approach for risk stratification.

The impact of prior drug allergies (PDA) on the clinical features and outcomes of patients who develop idiosyncratic drug-induced liver injury (DILI) is largely unknown. We aimed to assess the clinical presentation and outcomes of DILI patients based on the presence or absence of PDA and explore the association between culprit drugs responsible for DILI and allergy. We analysed a well-vetted cohort of DILI cases enrolled from the Spanish DILI Registry. Bootstrap-enhanced least absolute shrinkage operator procedure was used in variable selection, and a multivariable logistic model was fitted to predict poor outcomes in DILI. Of 912 cases with a first episode of DILI, 61 (6.7%) had documented PDA. Patients with PDA were older (p = 0.009), had higher aspartate aminotransferase (AST) levels (p = 0.047), lower platelet count (p = 0.011) and higher liver-related mortality than those without a history of drug allergies (11% vs. 1.6%, p < 0.001). Penicillin was the most common drug associated with PDA in DILI patients (32%). A model including PDA, nR-based type of liver injury, female sex, AST, total bilirubin, and platelet count showed an excellent performance in predicting poor outcome in patients from the Spanish DILI Registry (area under the ROC curve [AUC] 0.887; 95% confidence interval [CI] 0.794 - 0.981) and the LATINDILI Network (AUC 0.932; 95% CI 0.884 - 0.981). Patients with suspected DILI should be screened for PDA as they would require a close monitoring for early detection of worsening clinical course.

Complementarity and sensitivity of benthic state indicators to bottom-trawl fishing disturbance.

Many indicators have been developed to assess the state of benthic communities and identify seabed habitats most at risk from bottom trawling disturbance. However, the large variety of indicators and their development and application under specific geographic areas and management contexts has made it difficult to evaluate their wider utility. We compared the complementarity/uniqueness, sensitivity, and selectivity of 18 benthic indicators to pressure of bottom trawling. Seventeen common datasets with broad regional representation covering a range of pressure gradients from bottom trawling disturbance (n = 14), eutrophication (n = 1), marine pollution (n = 1), and oxygen depletion (n = 1) were used for the comparison. The outcomes of most indicators were correlated to a certain extent with response to bottom trawling disturbance, and two complementary groups of indicators were identified: diversity-based and biological trait-based indicators. Trait-based indicators that quantify the changes in relative abundance of sensitive taxa were most effective in identifying benthic community change in response to bottom trawling disturbance. None of the indicators responded to the trawling pressure gradient in all datasets, and some showed a response that were opposed to the theoretical expectation for some gradients. Indicators that showed clear responses to bottom trawling disturbance also showed clear responses in at least one other pressure gradient, suggesting those indicators are not pressure specific. These results emphasize the importance of selecting several indicators, at least one from each group (diversity and trait-based), to capture the broader signals of change in benthic communities due to bottom trawling activities. Our systematic approach offers the basis from which scientific advisors and/or managers can select suitable combinations of indicators to arrive at a sensitive and comprehensive benthic status assessment.

Sarcoidosis with esophageal involvement: an uncommon clinical enigma.

We present the case of a 46-year-old male, a former smoker, with a medical history significant for morbid obesity grade III, hypothyroidism, hyperuricemia, and dyslipidemia. Four months ago, he was diagnosed with sarcoidosis involving mediastinal lymph nodes and is currently undergoing treatment with corticosteroids. The patient presented to the emergency department with persistent epigastric and thoracic pain lasting one week, accompanied by dysphagia and odynophagia intermittently. Laboratory tests showed elevated acute-phase reactants, with no other notable abnormalities. Chest X-ray revealed pre-existing mediastinal adenopathy. Despite an abdominal CT scan with contrast showing no significant findings, esophagogastroduodenoscopy revealed marked extrinsic compression of the esophagus between 25 and 32 cm from the dental arch, with less intensity distally. Although passage of the endoscope through this area caused significant pain, it did not hinder its advancement. A chest CT scan with oral contrast demonstrated filamentous narrowing of the esophagus in the middle third, along with concentric thickening of its walls and multiple paratracheal, parahilar, and periesophageal lymphadenopathies. Following a tapering regimen of corticosteroids, the patient was discharged with a clinical diagnosis of sarcoidosis with mediastinal and esophageal involvement secondary to extrinsic compression. Due to clinical improvement with the prescribed treatment, endoscopic ultrasound and biopsies to assess esophageal wall involvement were deemed unnecessary.

One-Week Suicide Risk Prediction Using Real-Time Smartphone Monitoring: Prospective Cohort Study.

BACKGROUND: Suicide is a major global public health issue that is becoming increasingly common despite preventive efforts. Though current methods for predicting suicide risk are not sufficiently accurate, technological advances provide invaluable tools with which we may evolve toward a personalized, predictive approach. OBJECTIVE: We aim to predict the short-term (1-week) risk of suicide by identifying changes in behavioral patterns characterized through real-time smartphone monitoring in a cohort of patients with suicidal ideation. METHODS: We recruited 225 patients between February 2018 and March 2020 with a history of suicidal thoughts and behavior as part of the multicenter SmartCrisis study. Throughout 6 months of follow-up, we collected information on the risk of suicide or mental health crises. All participants underwent voluntary passive monitoring using data generated by their own smartphones, including distance walked and steps taken, time spent at home, and app usage. The algorithm constructs daily activity profiles for each patient according to these data and detects changes in the distribution of these profiles over time. Such changes are considered critical periods, and their relationship with suicide-risk events was tested. RESULTS: During follow-up, 18 (8%) participants attempted suicide, and 14 (6.2%) presented to the emergency department for psychiatric care. The behavioral changes identified by the algorithm predicted suicide risk in a time frame of 1 week with an area under the curve of 0.78, indicating good accuracy. CONCLUSIONS: We describe an innovative method to identify mental health crises based on passively collected information from patients' smartphones. This technology could be applied to homogeneous groups of patients to identify different types of crises.

Obesogenic Diet-Induced Neuroinflammation: A Pathological Link between Hedonic and Homeostatic Control of Food Intake.

Obesity-induced neuroinflammation is a chronic aseptic central nervous system inflammation that presents systemic characteristics associated with increased pro-inflammatory cytokines such as interleukin 1 beta (IL-1ß) and interleukin 18 (IL-18) and the presence of microglia and reactive astrogliosis as well as the activation of the NLRP3 inflammasome. The obesity pandemic is associated with lifestyle changes, including an excessive intake of obesogenic foods and decreased physical activity. Brain areas such as the lateral hypothalamus (LH), lateral septum (LS), ventral tegmental area (VTA), and nucleus accumbens (NAcc) have been implicated in the homeostatic and hedonic control of feeding in experimental models of diet-induced obesity. In this context, a chronic lipid intake triggers neuroinflammation in several brain regions such as the hypothalamus, hippocampus, and amygdala. This review aims to present the background defining the significant impact of neuroinflammation and how this, when induced by an obesogenic diet, can affect feeding control, triggering metabolic and neurological alterations.

Changing perspectives: unveiling the risks of ashwagandha-induced hepatotoxicity.

Ashwagandha, an herb popular in Ayurvedic medicine, is renowned for its health-enhancing properties. However, its association with liver damage in recent years has raised significant concerns, necessitating careful assessment and management. This case underscores the dangers of Ashwagandha, particularly for individuals with preexisting liver conditions, where it can lead to life-threatening acute-on-chronic liver failure. The lack of solid clinical evidence supporting Ashwagandha's health claims emphasizes the need for an evidence-based approach. Public education is essential to raise awareness of the risks associated with herbal supplements and prevent liver diseases.

Long-term comparison between blind and ultrasound-guided corticoid injections in Morton neuroma.

OBJECTIVES: This work compares the effectiveness of blind versus ultrasound (US)-guided injections for Morton neuroma (MN) up to 3 years of follow-up. METHODS: This is an evaluator-blinded randomised trial in which 33 patients with MN were injected by an experienced orthopaedic surgeon based on anatomical landmarks (blind injection, group 1) and 38 patients were injected by an experienced musculoskeletal radiologist under US guidance (group 2). Patients were assessed using the visual analogue scale and the Manchester Foot Pain and Disability index (MFPDI). Injections consisted of 1 ml of 2% mepivacaine and 40 mg triamcinolone acetonide in each web space with MN. Up to 4 injections were allowed during the first 3 months of follow-up. Follow-up was performed by phone calls and/or scheduled consultations at 15 days, 1 month, 45 days, 2 months, 3 months, 6 months and 1, 2 and 3 years. Statistical analysis was performed using unpaired Student's t tests. RESULTS: No differences in age or clinical measures were found at presentation between group 1 (VAS, 8.5 ± 0.2; MFPDI, 40.9 ± 1.1) and group 2 (VAS, 8.4 ± 0.2; MFPDI, 39.8 ± 1.2). Improvement in VAS was superior in group 2 up to 3 years of follow-up (p < 0.05). Improvement in MFPDI was superior in group 2 from 45 days to 2 years of follow-up (p < 0.05). Satisfaction with the treatment was higher in group 2 (87%) versus group 1 (59.1%) at 3 years of follow-up. CONCLUSION: Ultrasound-guided injections lead to a greater percentage of long-term improvement than blind injections in MN. KEY POINTS: • Ultrasound-guided corticosteroid injections in Morton neuroma provide long-term pain relief in more than 75% of patients. • Ultrasound-guided injections in Morton neuroma led to greater long-term pain relief and less disability than blind injections up to 3 years of follow-up. • The presence of an ipsilateral neuroma is associated with worse long-term disability score.

Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data.

The unprecedented availability of optical satellite data in cloud-based computing platforms, such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval models from the local to the planetary scale. Hybrid retrieval models are of interest to run in these platforms as they combine the advantages of physically- based radiative transfer models (RTM) with the flexibility of machine learning regression algorithms. Previous research with GEE primarily relied on processing bottom-of-atmosphere (BOA) reflectance data, which requires atmospheric correction. In the present study, we implemented hybrid models directly into GEE for processing Sentinel-2 (S2) Level-1C (L1C) top-of-atmosphere (TOA) reflectance data into crop traits. To achieve this, a training dataset was generated using the leaf-canopy RTM PROSAIL in combination with the atmospheric model 6SV. Gaussian process regression (GPR) retrieval models were then established for eight essential crop traits namely leaf chlorophyll content, leaf water content, leaf dry matter content, fractional vegetation cover, leaf area index (LAI), and upscaled leaf variables (i.e., canopy chlorophyll content, canopy water content and canopy dry matter content). An important pre-requisite for implementation into GEE is that the models are sufficiently light in order to facilitate efficient and fast processing. Successful reduction of the training dataset by 78% was achieved using the active learning technique Euclidean distance-based diversity (EBD). With the EBD-GPR models, highly accurate validation results of LAI and upscaled leaf variables were obtained against in situ field data from the validation study site Munich-North-Isar (MNI), with normalized root mean square errors (NRMSE) from 6% to 13%. Using an independent validation dataset of similar crop types (Italian Grosseto test site), the retrieval models showed moderate to good performances for canopy-level variables, with NRMSE ranging from 14% to 50%, but failed for the leaf-level estimates. Obtained maps over the MNI site were further compared against Sentinel-2 Level 2 Prototype Processor (SL2P) vegetation estimates generated from the ESA Sentinels' Application Platform (SNAP) Biophysical Processor, proving high consistency of both retrievals (R 2 from 0.80 to 0.94). Finally, thanks to the seamless GEE processing capability, the TOA-based mapping was applied over the entirety of Germany at 20 m spatial resolution including information about prediction uncertainty. The obtained maps provided confidence of the developed EBD-GPR retrieval models for integration in the GEE framework and national scale mapping from S2-L1C imagery. In summary, the proposed retrieval workflow demonstrates the possibility of routine processing of S2 TOA data into crop traits maps at any place on Earth as required for operational agricultural applications.

The cholesterol transfer protein GRAMD1A regulates autophagosome biogenesis.

Autophagy mediates the degradation of damaged proteins, organelles and pathogens, and plays a key role in health and disease. Thus, the identification of new mechanisms involved in the regulation of autophagy is of major interest. In particular, little is known about the role of lipids and lipid-binding proteins in the early steps of autophagosome biogenesis. Using target-agnostic, high-content, image-based identification of indicative phenotypic changes induced by small molecules, we have identified autogramins as a new class of autophagy inhibitor. Autogramins selectively target the recently discovered cholesterol transfer protein GRAM domain-containing protein 1A (GRAMD1A, which had not previously been implicated in autophagy), and directly compete with cholesterol binding to the GRAMD1A StART domain. GRAMD1A accumulates at sites of autophagosome initiation, affects cholesterol distribution in response to starvation and is required for autophagosome biogenesis. These findings identify a new biological function of GRAMD1A and a new role for cholesterol in autophagy.

Mapping landscape canopy nitrogen content from space using PRISMA data.

Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently launched and upcoming science-driven missions, e.g. PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), respectively. Moreover, the high-priority mission candidate Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is expected to globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. Thanks to the provision of contiguous visible-to-shortwave infrared spectral data, hyperspectral missions open enhanced opportunities for the development of new-generation retrieval models of multiple vegetation traits. Among these, canopy nitrogen content (CNC) is one of the most promising variables given its importance for agricultural monitoring applications. This work presents the first hybrid CNC retrieval model for the operational delivery from spaceborne imaging spectroscopy data. To achieve this, physically-based models were combined with machine learning regression algorithms and active learning (AL). The key concepts involve: (1) coupling the radiative transfer models PROSPECT-PRO and SAIL for the generation of a wide range of vegetation states as training data, (2) using dimensionality reduction to deal with collinearity, (3) applying an AL technique in combination with Gaussian process regression (GPR) for fine-tuning the training dataset on in field collected data, and (4) adding non-vegetated spectra to enable the model to deal with spectral heterogeneity in the image. The final CNC model was successfully validated against field data achieving a low root mean square error (RMSE) of 3.4 g/m2 and coefficient of determination (R 2) of 0.7. The model was applied to a PRISMA image acquired over agricultural areas in the North of Munich, Germany. Mapping aboveground CNC yielded reliable estimates over the whole landscape and meaningful associated uncertainties. These promising results demonstrate the feasibility of routinely quantifying CNC from space, such as in an operational context as part of the future CHIME mission.

Collision Avoidance Resource Allocation for LoRaWAN.

The number of connected IoT devices is significantly increasing and it is expected to reach more than two dozens of billions of IoT connections in the coming years. Low Power Wide Area Networks (LPWAN) have become very relevant for this new paradigm due to features such as large coverage and low power consumption. One of the most appealing technologies among these networks is LoRaWAN. Although it may be considered as one of the most mature LPWAN platforms, there are still open gaps such as its capacity limitations. For this reason, this work proposes a collision avoidance resource allocation algorithm named the Collision Avoidance Resource Allocation (CARA) algorithm with the objective of significantly increase system capacity. CARA leverages the multichannel structure and the orthogonality of spreading factors in LoRaWAN networks to avoid collisions among devices. Simulation results show that, assuming ideal radio link conditions, our proposal outperforms in 95.2% the capacity of a standard LoRaWAN network and increases the capacity by almost 40% assuming a realistic propagation model. In addition, it has been verified that CARA devices can coexist with LoRaWAN traditional devices, thus allowing the simultaneous transmissions of both types of devices. Moreover, a proof-of-concept has been implemented using commercial equipment in order to check the feasibility and the correct operation of our solution.

5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0.

Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.

[Clinical dilemmas derived from the need to certify rape for voluntary pregnancy interruption]. / Dilemas clínicos en la constitución de la tercera causal de la interrupción voluntaria del embarazo.

Since 2017, women in Chile are allowed to interrupt voluntarily a pregnancy on three grounds: 1) When a woman's life is at risk due to the pregnancy, 2) When there are fetal anomalies incompatible with life, or 3) When pregnancy is result of rape. Women who qualify for any of these three pregnancy interruption requirements are entitled to a psychosocial accompaniment program to promote an integrative approach. In this article we will discuss the role of the psychosocial team in cases of rape resulting pregnancy. Specifically, the clinical and ethical dilemmas posed by the need to certify the rape in a general hospital such as difficulties in assessment of the story's plausibility, clinician's dual role and the limits to confidentiality, are discussed.

[Chilean consensus on diagnosis and management of pancreatic cystic neoplasms]. / Consenso chileno de diagnóstico y manejo de neoplasias quísticas pancreáticas. Club de páncreas Chile-SCHGE.

Pancreatic cystic neoplasms (PCN) are frequently detected on abdominal images performed for non-pancreatic indications. Their prevalence in asymptomatic population ranges from 2.7 to 24.8%, and increases with age. There are several types of pancreatic cysts. Some may contain cancer or have malignant potential, such as mucinous cystic neoplasms, including mucinous cystadenoma (MCN) and intraductal papillary mucinous neoplasms (IPMN). In contrast, others are benign, such as serous cystadenoma (SCA). However, even those cysts with malignant potential rarely progress to cancer. Currently, the only treatment for pancreatic cysts is surgery, which is associated with high morbidity and occasional mortality. The Board of the Chilean Pancreas Club of the Chilean Gastroenterology Society developed the first Chilean multidisciplinary consensus for diagnosis, management, and surveillance of PCN. Thirty experts were invited and answered 21 statements with five possible alternatives: 1) fully agree; 2) partially agree; 3) undecided; 4) disagree and 5) strongly disagree. A consensus was adopted when at least 80% of the sum of the answers "fully agree" and "partially agree" was reached. The consensus was approved by the Board of Directors of the Chilean Pancreas Club for publication.

[Euthanasia: is this the law we need?] / Eutanasia: ¿es esta la ley que necesitamos?

The Spanish Euthanasia Law introduces a new right that is added to the portfolio of services provided by the Spanish health system and whose application is guaranteed within a period of 40 days. From the perspective of clinical experience, it is argued that without the effective right to quality palliative care and given the current shortcomings in dependant care, this law may send a threatening message to particularly fragile and dependant individuals that will lead to them feeling like a burden to their families and society. It is reasoned that basing the right to die on the dignity of the individual may have unexpected social repercussions. The text of the law presents the flaws of having been written hastily and without the support of advisory entities. There are issues that require clarification with regard to the application of euthanasia within the context of general practice. The conclusion is that this new law will pose more problems of the type it aims to resolve.

Climate-induced changes in the suitable habitat of cold-water corals and commercially important deep-sea fishes in the North Atlantic.

The deep sea plays a critical role in global climate regulation through uptake and storage of heat and carbon dioxide. However, this regulating service causes warming, acidification and deoxygenation of deep waters, leading to decreased food availability at the seafloor. These changes and their projections are likely to affect productivity, biodiversity and distributions of deep-sea fauna, thereby compromising key ecosystem services. Understanding how climate change can lead to shifts in deep-sea species distributions is critically important in developing management measures. We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to project changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean. Our models projected a decrease of 28%-100% in suitable habitat for cold-water corals and a shift in suitable habitat for deep-sea fishes of 2.0°-9.9° towards higher latitudes. The largest reductions in suitable habitat were projected for the scleractinian coral Lophelia pertusa and the octocoral Paragorgia arborea, with declines of at least 79% and 99% respectively. We projected the expansion of suitable habitat by 2100 only for the fishes Helicolenus dactylopterus and Sebastes mentella (20%-30%), mostly through northern latitudinal range expansion. Our results projected limited climate refugia locations in the North Atlantic by 2100 for scleractinian corals (30%-42% of present-day suitable habitat), even smaller refugia locations for the octocorals Acanella arbuscula and Acanthogorgia armata (6%-14%), and almost no refugia for P. arborea. Our results emphasize the need to understand how anticipated climate change will affect the distribution of deep-sea species including commercially important fishes and foundation species, and highlight the importance of identifying and preserving climate refugia for a range of area-based planning and management tools.

Understanding the unorthodox stabilization of liquid phase exfoliated molybdenum disulfide (MoS2) in water medium.

Molybdenum disulfide is a highly esteemed 2D material with interesting applications in nanoelectronics, composites, biotechnology and beyond. Its production through liquid-phase exfoliation in H2O is low-cost and eco-friendly. Herein, we present a detailed experimental and theoretical investigation seeking to explain the peculiar stability of MoS2 in H2O medium. By combining different microscopic (SEM, AFM and OM), spectrometric (Raman, UV-vis and AFM-FTIR), scattering (DLS) and ab initio simulation techniques, an edge-functionalization hypothesis for the excellent solvent properties of water for producing few-layer MoS2 has been demonstrated.

Astaxanthin Counteracts Excitotoxicity and Reduces the Ensuing Increases in Calcium Levels and Mitochondrial Reactive Oxygen Species Generation.

Astaxanthin (ASX) is a carotenoid pigment with strong antioxidant properties. We have reported previously that ASX protects neurons from the noxious effects of amyloid-ß peptide oligomers, which promote excessive mitochondrial reactive oxygen species (mROS) production and induce a sustained increase in cytoplasmic Ca2+ concentration. These properties make ASX a promising therapeutic agent against pathological conditions that entail oxidative and Ca2+ dysregulation. Here, we studied whether ASX protects neurons from N-methyl-D-aspartate (NMDA)-induced excitotoxicity, a noxious process which decreases cellular viability, alters gene expression and promotes excessive mROS production. Incubation of the neuronal cell line SH-SY5Y with NMDA decreased cellular viability and increased mitochondrial superoxide production; pre-incubation with ASX prevented these effects. Additionally, incubation of SH-SY5Y cells with ASX effectively reduced the basal mROS production and prevented hydrogen peroxide-induced cell death. In primary hippocampal neurons, transfected with a genetically encoded cytoplasmic Ca2+ sensor, ASX also prevented the increase in intracellular Ca2+ concentration induced by NMDA. We suggest that, by preventing the noxious mROS and Ca2+ increases that occur under excitotoxic conditions, ASX could be useful as a therapeutic agent in neurodegenerative pathologies that involve alterations in Ca2+ homeostasis and ROS generation.

Artifact expression of polylactic acid/hydroxyapatite/graphene oxide nanocomposite in CBCT: a promising dental material.

OBJECTIVE: To evaluate the artifact expression of a new material-polylactic acid (PLA)/hydroxyapatite (HA)/graphene oxide (GO) nanocomposite-and compare it with that of commonly used dental materials, using cone-beam computed tomography. MATERIALS AND METHODS: Cylinders of amalgam alloy, metal alloy, titanium, gutta-percha, and PLA/HA/GO were individually placed in the center of an acrylic phantom. Three images of each phantom + cylinder set were acquired using a Picasso Trio unit (Vatech, Hwaseong, South Korea) set at 90 kVp, 3.7 mA, 0.2 mm3 voxel size, and 12 × 8.5 cm FOV. Three images of a control group (sound phantom) were also obtained. Eight ROIs were established in each image to evaluate the standard deviation (S.D.) of gray values in the ImageJ Software. The Kruskal-Wallis test with the Student-Newman-Keuls post hoc was employed, considering a significance level of 5%. RESULTS: There were no significant differences in S.D. between the control and PLA/HA/GO images (p = 0.712). Both control and PLA/HA/GO showed fewer image artifacts than the other materials (p < 0.05). The images of the amalgam alloy did not differ from the metal alloy images (p = 0.691), showing more artifacts than the gutta-percha (p = 0.028) and titanium (p = 0.051). CONCLUSIONS: The PLA/HA/GO produced fewer artifacts and a better-quality image than the other tested materials. CLINICAL RELEVANCE: The PLA/HA/GO has physical and biological properties similar to those of dental materials. Since it has produced fewer image artifacts, this new nanocomposite may be employed in the near future, enhancing the diagnosis in CBCT.

Transform-Based Multiresolution Decomposition for Degradation Detection in Cellular Networks.

Anomaly detection in the performance of the huge number of elements that are part of cellular networks (base stations, core entities, and user equipment) is one of the most time consuming and key activities for supporting failure management procedures and ensuring the required performance of the telecommunication services. This activity originally relied on direct human inspection of cellular metrics (counters, key performance indicators, etc.). Currently, degradation detection procedures have experienced an evolution towards the use of automatic mechanisms of statistical analysis and machine learning. However, pre-existent solutions typically rely on the manual definition of the values to be considered abnormal or on large sets of labeled data, highly reducing their performance in the presence of long-term trends in the metrics or previously unknown patterns of degradation. In this field, the present work proposes a novel application of transform-based analysis, using wavelet transform, for the detection and study of network degradations. The proposed system is tested using cell-level metrics obtained from a real-world LTE cellular network, showing its capabilities to detect and characterize anomalies of different patterns and in the presence of varied temporal trends. This is performed without the need for manually establishing normality thresholds and taking advantage of wavelet transform capabilities to separate the metrics in multiple time-frequency components. Our results show how direct statistical analysis of these components allows for a successful detection of anomalies beyond the capabilities of detection of previous methods.