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Adenomyosis is a commonly encountered pathology in women of reproductive age and frequently coexists with infertility. The effect of adenomyosis on fertility, particularly on in vitro fertilisation and intracytoplasmic sperm injection outcomes, is not well understood. Various pretreatment modalities have been used to improve pregnancy rates and live birth outcomes; however, because of a lack of high-quality evidence, there is no clear consensus on the best pretreatment option. This review was conducted through a PubMed search aiming to highlight the relationship between pretreatment and fertility in women with adenomyosis. Medical, ablative surgical, and non-surgical therapies were reviewed. According to the current literature, gonadotropin-releasing hormone agonist therapy and placement of a levonorgestrel intrauterine system are two suitable medical pretreatment strategies that can improve the clinical pregnancy rates of patients with adenomyosis. Surgical ablation of adenomyosis can also be beneficial, although surgical management can be challenging. Non-surgical thermal techniques, including high-intensity focused ultrasound ablation, percutaneous microwave ablation, and radiofrequency ablation, are much less invasive techniques that have shown effectiveness in improving fertility. Although evidence remains limited, all these procedures have demonstrated a favourable safety profile. Further studies are needed to better develop these techniques and demonstrate their effectiveness.

BackgroundSmall-for-gestational-age (SGA) fetuses are at increased risk of mortality and morbidity, and less than 30% will be detected by any ultrasound scan within 4 weeks before delivery. Our aim was to evaluate the relationship between neutrophil/lymphocyte ratio (NLR) in the first trimester of pregnancy and SGA fetuses.MethodWe performed a prospective study between June 2021 and August 2022, to evaluate the relationship between the neutrophil to lymphocyte ratio in maternal blood in the first trimester of pregnancy, with the birth of an SGA fetus. One hundred ninety-four participants with singleton pregnancies between 11 + 1 and 13 + 6 weeks of gestation were recruited. Pregnancies affected with diagnosed fetal chromosomal abnormalities, or chronic pathologies were excluded. SGA was defined as birthweight less than the 10th centile (N = 42) and severe SGA as birthweight less than the 3rd centile for gestation (N = 10) according to a locally derived descriptive charts. The NLR value measured in the first trimester was compared between these two groups and controls.ResultsWe found no statistically significant difference in NLR, (3.5 +/−1.2 vs. 3.4+/−1.2, p-value of 0.78) when comparing the SGA less than the 10th centile group to the control group. NLR was also not different between severe SGA and controls (3.6+/−1.4 vs. 3.4+/−1.2 p-value of 0.78).ConclusionWe found no association between first-trimester NLR ratio and SGA.

Abstract Background the problem in early diagnosis of sporadic cancer is understanding the individual’s risk to develop disease. In response to this need, global scientific research is focusing on developing predictive models based on non-invasive screening tests. A tentative solution to the problem may be a cancer screening blood-based test able to discover those cell requirements triggering subclinical and clinical onset latency, at the stage when the cell disorder, i.e. atypical epithelial hyperplasia, is still in a subclinical stage of proliferative dysregulation. Methods a well-established procedure to identify proliferating circulating tumor cells was deployed to measure the cell proliferation of circulating non-haematological cells which may suggest tumor pathology. Moreover, the data collected were processed by a supervised machine learning model to make the prediction. Results the developed test combining circulating non-haematological cell proliferation data and artificial intelligence shows 98.8% of accuracy, 100% sensitivity, and 95% specificity. Conclusion this proof of concept study demonstrates that integration of innovative non invasive methods and predictive-models can be decisive in assessing the health status of an individual, and achieve cutting-edge results in cancer prevention and management.

Extracorporeal Membrane Oxygenation (ECMO) is a medical device used to support patients with severe cardiac and/or respiratory failure. It is being used more frequently to offer percutaneous mechanical circulatory support, even though the intricate interactions between ECMO and the failing heart, as well as its impact on hemodynamics and perfusion, are not yet fully understood. Within the two main types of ECMO support (the veno-venous ECMO (VV-ECMO), which is used to support only the lungs) and the veno-arterial ECMO (VA-ECMO), which is used to support the lungs and heart), consideration is given solely to the second approach. Indeed, this study focuses on the impact of different ECMO cannulation site and blood perfusion conditions on the aortic hemodynamics and organ perfusion in VA-ECMO. Using computed tomography (CT) images, we reconstructed specific aortic models based on clinical cannula configurations and placements. A detailed cannula-aorta integration model was developed to simulate the VA-ECMO blood supply environment. Employing computational fluid dynamics (CFD), we analyzed how varying ECMO perfusion levels and ECMO cannulation sites affect flow characteristics. This study provides insights into optimizing ECMO therapy by understanding its effects on blood flow and potential damage to blood and organs.

The growing recognition of the public health impact of cognitive impairment and dementia has sparked a global initiative to identify risk factors and develop strategies to prevent or slow the progression of these cognitive disorders. Uric acid, the end product of the metabolism of purine nucleotides, has been reported as a key factor of many conditions potentially involved in cognitive dysfunction/dementia. In addition, some studies support the hypothesis that elevated uric acid levels could reduce the risk of Alzheimer’s disease, slow down the decline of cognition, and delay the progression of Alzheimer’s disease, while other evidence achieves opposite positions. These discrepancies might reflect a biological ambivalence for uric acid depending on a very complex interplay of factors that include its concentrations achieved in biological fluids, the nature, and concentration of free radicals, the presence and concentration of other antioxidant molecules, potentially responsible for bi-directional effects of uric acid on brain health/functioning. In this narrative review, we attempt to elucidate the influential role of uric acid metabolism in cognitive functioning by discussing pathophysiological mechanisms putatively involved, being well aware that none of them can be considered one-sided due to the complexity of the human organism.

Purpose: In recent years, the Electroencephalography (EEG)-based Brain-Computer Interface (BCI) appli-cation has been growing rapidly and has emerged as a technology with high translational potential since it allows disabled people to translate human intentions into control signals and to interact with the external environment without any kinesthetic movement. Individuals with significant health problems can benefit from this technology to improve their independence and facilitate participation in activities, thus improving general well-being and preventing impairments. The rapid advances in technology have led to optimal innovation in the context of wearable health monitoring and remote control solutions. Many wearable devices for capturing EEG signals in daily life have recently been released on the market. Our paper aims to present a wearable de-vice-based system for real-time and remote EEG monitoring, to describe the proposed system modules and the signal processing algorithms, to explore the functionalities of this wearable EEG solution, and to suggest its potential application for daily brain data recordings in the home en-vironment. Materials and Methods: The validity of the Emotiv Epoc+ device in the continuous and real-time EEG signals acquisition and monitoring was demonstrated by means of preliminary test measurements during a resting state paradigm performed by a healthy control subject. Results: Our findings confirmed the Epoc+ reliability for event-related brain potential research and in measuring acceptable spectral EEG data. Conclusion: The described approach, focusing on the emerging area of remote monitoring sensors and wearable device applications, might be leveraged to measure complex health outcomes in non-specialist and remote settings.

Purpose: In this paper, we propose a secure wearable and portable device aiming to (i) monitor physical activity in medical and clinical rehabilitation, (ii) evaluate the subject's movements in sports environments, and (iii) monitor wellness indicators. Materials and Methods: The innovative low-power custom circuit can acquire, pre-process, digitalize, and transmit EMG signals to a Raspberry PI4 device via a low-energy Bluetooth module. The Raspberry PI4 is a hub that sends data to a cloud-based system for remote monitoring and processing. The best cybersecurity practices have been implemented: firewall, anti-DDoS and SELinux. Results: We have assessed the system's vulnerability before and after the system's hardening. SELinux makes the system safer and prevents unauthorized access to patients' data health by tampering with the devices. Conclusion: Adopting IoT systems in telemedicine requires greater attention to cybersecurity. It is necessary to implement security mechanisms to guarantee the privacy of patient's health data.

In the global context, advancements in technology and science have rendered virtual, augmented, and mixed-reality technologies capable of transforming clinical care and medical environments by offering enhanced features and improved healthcare services. This paper aims to present a mixed reality-based system to control a robotic wheelchair for people with limited mobility. The test group comprised 11 healthy subjects (six male, five female, mean age 35.2 ± 11.7 years). A novel platform that integrates a smart wheelchair and an eye-tracking-enabled head-mounted display was proposed to reduce the cognitive requirements needed for wheelchair movement and control. The approach’s effectiveness was demonstrated by evaluating our system in realistic scenarios. The demonstration of the proposed AR head-mounted display user interface for controlling a smart wheelchair and the results provided in this paper could highlight the potential of the HoloLens 2-based innovative solutions and bring focus to emerging research topics, such as remote control, cognitive rehabilitation, the implementation of patient autonomy with severe disabilities, and telemedicine.

The synthesis of nanometer‐thick (≈3 nm) gallium oxynitride (GaOxNy) layers with a variable stoichiometry is reported. The approach primarily exploits the liquid metal chemistry (LMC) technique and promises easier integration of 2D materials onto photonic devices compared to traditional top‐down and bottom‐up methods. The fabrication follows a two‐step process, involving first liquid metal‐based printing of a nanometer‐thick layer of gallium oxide (Ga2O3), followed a plasma‐enhanced nitridation reaction. Control over nitridation parameters (plasma power, exposure time) allows adjustment of the GaOxNy layer's composition, granting access to compounds with distinct optical properties (e.g., a 20% index variation), as demonstrated by ellipsometry and density functional theory (DFT) simulations. DFT provides a microscopic understanding of the effect of the bond polarization and crystallinity on the optical properties of GaOxNy compounds. These findings expand the knowledge of ultrathin GaOxNy alloys, which are poorly studied with respect to their gallium nitride (GaN) and Ga2O3 counterparts. They also represent an essential step toward integrating such 2D materials into photonic chips and offer new opportunities to improve the performance of hybrid optoelectronic devices.

Background Despite longstanding epidemiologic data on the association between increased serum triglycerides and cardiovascular events, the exact level at which risk begins to rise is unclear. The Working Group on Uric Acid and Cardiovascular Risk of the Italian Society of Hypertension has conceived a protocol aimed at searching for the prognostic cutoff value of triglycerides in predicting cardiovascular events in a large regional‐based Italian cohort. Methods and Results Among 14 189 subjects aged 18 to 95 years followed‐up for 11.2 (5.3–13.2) years, the prognostic cutoff value of triglycerides, able to discriminate combined cardiovascular events, was identified by means of receiver operating characteristic curve. The conventional (150 mg/dL) and the prognostic cutoff values of triglycerides were used as independent predictors in separate multivariable Cox regression models adjusted for age, sex, body mass index, total and high‐density lipoprotein cholesterol, serum uric acid, arterial hypertension, diabetes, chronic renal disease, smoking habit, and use of antihypertensive and lipid‐lowering drugs. During 139 375 person‐years of follow‐up, 1601 participants experienced cardiovascular events. Receiver operating characteristic curve showed that 89 mg/dL (95% CI, 75.8–103.3, sensitivity 76.6, specificity 34.1, P

The objective of this study was to investigate the longitudinal association of metabolically healthy overweight/obese adults with major adverse cardiovascular events (MACE) and the effect of LDL-cholesterol levels on this association. This study was conducted with 15,904 participants from the URRAH study grouped according to BMI and metabolic status. Healthy metabolic status was identified with and without including LDL-cholesterol. The risk of MACE during 11.8 years of follow-up was evaluated with multivariable Cox regressions. Among the participants aged p = 0.012). However, when LDL-cholesterol < 130 mg/dL was included in the definition of healthy metabolic status, no increase in risk was found in the overweight/obese adults compared to the normal weight individuals (hazard ratio 0.70 (0.07–6.71, p = 0.75). The present data show that the risk of MACE is increased in metabolically healthy overweight/obese individuals identified according to standard criteria. However, when LDL-cholesterol is included in the definition, metabolically healthy individuals who are overweight/obese have no increase in risk.

Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

Injuries represent a serious concern for football players, with a significant loss in terms of sport participation and long periods of rehabilitation. According to the 2019/20 UEFA Élite Club Injury Report, the average incidence of injuries during training is 2.8 per 1000 h of training, with an average absence from training of 20 days. In addition, injured athletes are 4 to 7 times more likely to relapse than uninjured athletes. High workloads and reduced recovery periods represent two of the most important modifiable risk factors. In this context, prevention and an adequate rehabilitation protocol are vital in managing injuries, reducing their incidence, and improving the return to competition. In recent years, technological development has provided new tools in rehabilitation, and Virtual reality (VR) has shown interesting results in treating neurologic and orthopedic pathologies. Virtual Reality (VR) technology finds application in the sports industry as a tool to examine athletes’ technical movements. The primary objective is to detect the biomechanical risk factors associated with anterior cruciate ligament injury. Additionally, VR can be used to train athletes in field-specific techniques and create safe and controlled therapeutic environments for post-injury recovery. Moreover, VR offers a customizable approach to treatment based on individual player data. It can be employed for both prevention and rehabilitation, tailoring the rehabilitation and training protocols according to the athletes’ specific needs.

High levels of serum uric acid (SUA) and triglycerides (TG) might promote high-cardiovascular-risk phenotypes, including subclinical atherosclerosis. An interaction between plaques xanthine oxidase (XO) expression, SUA, and HDL-C has been recently postulated. Subjects from the URic acid Right for heArt Health (URRAH) study with carotid ultrasound and without previous cardiovascular diseases (CVD) (n = 6209), followed over 20 years, were included in the analysis. Hypertriglyceridemia (hTG) was defined as TG ≥ 150 mg/dL. Higher levels of SUA (hSUA) were defined as ≥5.6 mg/dL in men and 5.1 mg/dL in women. A carotid plaque was identified in 1742 subjects (28%). SUA and TG predicted carotid plaque (HR 1.09 [1.04–1.27], p < 0.001 and HR 1.25 [1.09–1.45], p < 0.001) in the whole population, independently of age, sex, diabetes, systolic blood pressure, HDL and LDL cholesterol and treatment. Four different groups were identified (normal SUA and TG, hSUA and normal TG, normal SUA and hTG, hSUA and hTG). The prevalence of plaque was progressively greater in subjects with normal SUA and TG (23%), hSUA and normal TG (31%), normal SUA and hTG (34%), and hSUA and hTG (38%) (Chi-square, 0.0001). Logistic regression analysis showed that hSUA and normal TG [HR 1.159 (1.002 to 1.341); p = 0.001], normal SUA and hTG [HR 1.305 (1.057 to 1.611); p = 0.001], and the combination of hUA and hTG [HR 1.539 (1.274 to 1.859); p = 0.001] were associated with a higher risk of plaque. Our findings demonstrate that SUA is independently associated with the presence of carotid plaque and suggest that the combination of hyperuricemia and hypertriglyceridemia is a stronger determinant of carotid plaque than hSUA or hTG taken as single risk factors. The association between SUA and CVD events may be explained in part by a direct association of UA with carotid plaques.

4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY)-based molecules have emerged as interesting materials for optoelectronic applications due to the possibility to easily fine-tune their photophysical and optical properties, dominated by two main absorption bands in the visible range. However, no studies have been reported on the nature of these spectral features. By means of ultrafast spectroscopy, we detect intramolecular energy transfer in a spin-coated film of di-thieno-phenyl BODIPY (DTPBDP) dispersed in a polystyrene matrix after pumping the high-energy absorption band. The same effect is not present upon pumping the lowest-energy band, which instead allows the achievement of efficient amplified spontaneous emission. Density functional calculations indicate the different nature of the two main absorption bands, explaining their different photophysical behavior.

Bile acids (BAs) and bilirubin, primarily known for their role in lipid metabolism and as heme catabolite, respectively, have been found to have diverse effects on various physiological processes, including oxidative stress and inflammation. Indeed, accumulating evidence showed that the interplay between BAs and bilirubin in these processes involves intricate regulatory mechanisms mediated by specific receptors and signaling pathways under certain conditions and in specific contexts. Oxidative stress plays a significant role in the development and progression of cardiovascular diseases (CVDs) due to its role in inflammation, endothelial dysfunction, hypertension, and other risk factors. In the cardiovascular (CV) system, recent studies have suggested that BAs and bilirubin have some opposite effects related to oxidative and inflammatory mechanisms, but this area of research is still under investigation. This review aims to introduce BAs and bilirubin from a biochemical and physiological point of view, emphasizing their potential protective or detrimental effects on CVDs. Moreover, clinical studies that have assessed the association between BAs/bilirubin and CVD were examined in depth to better interpret the possible link between them.

This article presents a comprehensive investigation into the functionalization of methoxyphenylazobenzene using electron-directing groups located at the meta position relative to the azo group. Spectroscopic analysis of meta-functionalized azobenzenes reveals that the incorporation of electron-withdrawing units significantly influences the absorption spectra of both E and Z isomers, while electron-donating functionalities lead to more subtle changes. The thermal relaxation process from Z to E result in almost twice as prolonged for electron-withdrawing functionalized azobenzenes compared to their electron-rich counterparts. Computational analysis contributes a theoretical understanding of the electronic structure and properties of meta-substituted azobenzenes. This combined approach, integrating experimental and computational techniques, yields significant insights into the structure–property relationship of meta-substituted asymmetrical phenolazobenzenes.

Several studies have detected a direct association between serum uric acid (SUA) and cardiovascular (CV) risk. In consideration that SUA largely depends on kidney function, some studies explored the role of the serum creatinine (sCr)-normalized SUA (SUA/sCr) ratio in different settings. Previously, the URRAH (URic acid Right for heArt Health) Study has identified a cut-off value of this index to predict CV mortality at 5.35 Units. Therefore, given that no SUA/sCr ratio threshold for CV risk has been identified for patients with diabetes, we aimed to assess the relationship between this index and CV mortality and to validate this threshold in the URRAH subpopulation with diabetes; the URRAH participants with diabetes were studied (n = 2230). The risk of CV mortality was evaluated by the Kaplan–Meier estimator and Cox multivariate analysis. During a median follow-up of 9.2 years, 380 CV deaths occurred. A non-linear inverse association between baseline SUA/sCr ratio and risk of CV mortality was detected. In the whole sample, SUA/sCr ratio > 5.35 Units was not a significant predictor of CV mortality in diabetic patients. However, after stratification by kidney function, values > 5.35 Units were associated with a significantly higher mortality rate only in normal kidney function, while, in participants with overt kidney dysfunction, values of SUA/sCr ratio > 7.50 Units were associated with higher CV mortality. The SUA/sCr ratio threshold, previously proposed by the URRAH Study Group, is predictive of an increased risk of CV mortality in people with diabetes and preserved kidney function. While, in consideration of the strong association among kidney function, SUA, and CV mortality, a different cut-point was detected for diabetics with impaired kidney function. These data highlight the different predictive roles of SUA (and its interaction with kidney function) in CV risk, pointing out the difference in metabolic- and kidney-dependent SUA levels also in diabetic individuals.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies’ exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony’s health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project’s data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.