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Fertility-Sparing Treatments in Endometrial Cancer: A Comprehensive Review on Efficacy, Oncological Outcomes, and Reproductive Potential
Full text linkEndometrial cancer (EC) affects 3–14% of women under 40 who wish to preserve their fertility. The standard treatment for EC is a hysterectomy with salpingo-oophorectomy. However, for those desiring fertility preservation, oral progestogens such as medroxy-progesterone acetate (MPA) or megestrol acetate (MA) are the most common therapies in Fertility-Sparing Treatment (FST). Other treatments include gonadotropin-releasing hormone agonist (GnRHa), levonorgestrel-releasing intrauterine system (LNG-IUS), and metformin plus progestin. This comprehensive review evaluates the best FST options for women with reproductive potential. PubMed, EMBASE, and Scopus were searched in June 2023 using specific keywords. Studies included in the review focused on patients with EC undergoing FST, with outcomes such as complete response rate (CRR), recurrence rate (RR), pregnancy rate (PR), and live birth rate. Eighteen studies met the inclusion criteria, involving 23,976 patients. In only-oral progestin trials, CRR ranged from 18% to 100%; RR ranged from 0% to 81.8%; Death Rate ranged from 0% to 3.6%. In studies combining oral progestin with LNG-IUS, CRR ranged from 55% to 87.5%; RR ranged from 0% to 41.7%; Death Rate was 0%. Most patients with Stage IA EC received MPA or MA. Fertility-related outcomes were reported in 15 studies. PR ranged from 4 to 44 patients in trials involving only oral progestins. When combining oral progestin with LNG-IUS, PR ranged from 1 to 46 patients. Progestin therapy, including oral MPA and MA, is considered safe and effective, with limited evidence supporting the use of LNG-IUS
A Deep Learning Model Integrating Clinical and MRI Features Improves Risk Stratification and Reduces Unnecessary Biopsies in Men with Suspected Prostate Cancer
No full textBackground: Accurate upfront risk stratification in suspected clinically significant prostate cancer (csPCa) may reduce unnecessary prostate biopsies. Integrating clinical and Magnetic Resonance Imaging (MRI) variables using deep learning could improve prediction. Methods: We retrospectively analysed 538 men who underwent MRI and biopsy between April 2019-September 2024. A fully connected neural network was trained using 5-fold cross-validation. Model 1 included clinical features (age, prostate-specific antigen [PSA], PSA density, digital rectal examination, family history, prior negative biopsy, and ongoing therapy). Model 2 used MRI-derived Prostate Imaging Reporting and Data System (PI-RADS) categories. Model 3 used all previous variables as well as lesion size, location, and prostate volume as determined on MRI. Results: Model 3 achieved the highest area under the receiver operating characteristic curve (AUC = 0.822), followed by Model 2 (AUC = 0.778) and Model 1 (AUC = 0.716). Sensitivities for detecting clinically significant prostate cancer (csPCa) were 87.4%, 91.6%, and 86.8% for Models 1, 2, and 3, respectively. Although Model 3 had slightly lower sensitivity than Model 2, it showed higher specificity, reducing false positives and avoiding 43.4% and 21.2% more biopsies compared to Models 1 and 2. Decision curve analysis showed M2 had the highest net benefit at risk thresholds ≤ 20%, while M3 was superior above 20%. Conclusions: Model 3 improved csPCa risk stratification, particularly in biopsy-averse settings, while Model 2 was more effective in cancer-averse scenarios. These models support personalized, context-sensitive biopsy decisions
High-content microscopy quantification of mitochondrial membrane potential
No full textIn nearly all pathophysiological processes, mitochondrial membrane potential serves as a crucial indicator of mitochondrial function and activity. However, there remains a need for high-content imaging techniques that incorporate multiparametric measurements for comprehensive mitochondrial assessment. This paper introduces a novel unbiased approach for quantifying mitochondrial membrane potential in vitro, applicable to both two-dimensional and three-dimensional experimental systems. Furthermore, the incorporation of automated image analysis with machine learning algorithms enabled precise identification and segregation of distinct cell types within complex co-culture systems, allowing for targeted evaluation of individual subpopulations. Here, we provide a protocol for large-scale profiling of mitochondrial activity across various experimental contexts
Combination of searches for singly produced vectorlike top quarks in (Formula presented) collisions at (Formula presented) with the ATLAS detector
No full textA combination of searches for the single production of vectorlike top quarks ((Formula presented)) is presented. These analyses are based on proton-proton collisions at (Formula presented) recorded in 2015-2018 with the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of (Formula presented). The (Formula presented) decay modes considered in this combination are into a top quark and either a Standard Model Higgs boson or a (Formula presented) boson ((Formula presented) and (Formula presented)). The individual searches used in the combination are differentiated by the number of leptons ((Formula presented), (Formula presented)) in the final state. The observed data are found to be in good agreement with the Standard Model background prediction. Interpretations are provided for a range of masses and couplings of the vectorlike top quark for benchmark models and generalized representations in terms of 95% confidence level limits. For a benchmark signal prediction of a vectorlike top quark SU(2) singlet with electroweak coupling, (Formula presented), of 0.5, masses below 2.1 TeV are excluded, resulting in the most restrictive limits to date
Coping with the New: Resilience in Cultural Identity Between the Late Bronze and the Iron Age in Northern Mesopotamia
No full textMicrowave irradiation for airborne virus inactivation: Evidence and future perspectives
Full text linkNon-thermal microwave (MW) irradiation has emerged as a promising approach for inactivating airborne viruses by exploiting their vibrational properties through selective resonant energy transfer (SRET). In this narrative review, we synthesize current evidence on the antiviral efficacy of non-thermal microwave (MW) technologies, evaluate their feasibility for indoor infection control, and highlight existing limitations as well as future research directions. A literature search was conducted across PubMed, Scopus, Google Scholar, and ScienceDirect for studies published between January 1, 2015, and March 7, 2025, using keywords related to MW irradiation, SRET, and airborne viruses. The evidence was organized into three key themes: mechanistic foundations of the technology, effectiveness against airborne viruses, and regulatory and safety considerations. The available data indicate that MW irradiation disrupts viral structures through vibrational resonance mechanisms, with effectiveness varying by viral type and depending on optimized frequency and exposure duration. Regulatory authorities recently acknowledged its potential to reduce airborne transmission, contingent on meeting stringent safety standards for electromagnetic compatibility, specific absorption rates, and power density. In summary, non-thermal MW irradiation offers a scalable solution for reducing airborne respiratory virus transmission. Pending further real-world validation, integrating this technology into public health strategies offers a promising approach to strengthen infection prevention and control in both healthcare settings and indoor environments, effectively targeting both human and zoonotic infections
PERFORMANCE AND EFFICIENCY PF A HYBRID SELF-PROPELLED CABLE LOGGING CARRIAGE: AN EXPERIMENTAL STUDY
No full textGlobal warming and the dependance on expensive fossil fuels in uncertain times are two main drivers for the development of alternative drivetrains. The alpine logging sector is no exception. Indeed, electrification has demonstrated significant potential for fuel savings in cable logging applications, particularly due to the high capacity for energy recovery in cyclic operations involving variations in potential energy. This work presents results of a study involving several key sub-systems as well as the roundtrip efficiency of a hybrid self-propelled carriage called HULK. In addition to performance and efficiency studies of the engine-generator unit, energy dissipation unit and battery system, its two main drive systems, i.e., the dropline winch and the propulsion module, have been evaluated. The tests enabled the performance mapping of key components, identification of optimal operating points, and confirmation of the substantial energy recovery potential. Furthermore, the results highlight the feasibility of energy-autarkic operation in real-world transport applications
Search for triple Higgs boson production in the (Formula presented) final state using (Formula presented) collisions at (Formula presented) with the ATLAS detector
No full textA search for the production of three Higgs bosons ((Formula presented)) in the (Formula presented) final state is presented. The search uses (Formula presented) of proton-proton collision data at (Formula presented) collected with the ATLAS detector at the Large Hadron Collider. The analysis targets both nonresonant and resonant production of (Formula presented). The resonant interpretations primarily consider a cascade decay topology of (Formula presented) with masses of the new scalars (Formula presented) and (Formula presented) up to 1.5 and 1 TeV, respectively. In addition to scenarios where (Formula presented) is off-shell, the nonresonant interpretation includes a search for Standard Model (Formula presented) production, with limits on the trilinear and quartic Higgs self-coupling set. No evidence for (Formula presented) production is observed. An upper limit of 59 fb is set, at the 95% confidence level, on the cross section for Standard Model (Formula presented) production
Daily deal distribution and local destination characteristics: Data-driven analysis of upmarket Italian hotel online sales practices
Full text linkThis paper examines hotels’ use of niche daily deal websites (flash sales) through the lens of external, destination characteristics, aiming to establish relationships between the two. Extant research indicates that both internal and external factors influence the decision-making processes of hotel businesses, yet, to date, this popular practice has been examined only from an internal business perspective. Using web scraping techniques, spatial and census data combined with quantitative analysis, the paper analyses 2741 niche daily deal offerings of 4-and 5-star Italian hotels against destination characteristics. The paper evidences the destination market structure impact on the conduct of hotels related to daily deal use. It shows that destination seasonality, economic tourist reliance, local competition and tourism demand are correlated with the volume and/or depth of discount of hotel offers featured via daily deal websites. This study contributes to the pricing research by empirically evidencing and comprehensively mapping a relationship between localised destination characteristics and hotel discounting behaviour
Amyloid β1-40 Predicts Long-Term Mortality Rate in Patients With Acute Myocardial Infarction
Full text linkBACKGROUND: Amyloid β1-40 (Aβ1-40) contributes to atherosclerosis, being involved in plaque formation and destabilization. The prognostic role of Aβ1-40 in patients with acute myocardial infarction is currently limited to non–ST-segment–elevation myocardial infarction (NSTEMI). We examined the prognostic value of Aβ1-40 in a real-world cohort of patients with acute myocardial infarction (both ST-segment–elevation myocardial infarction [STEMI] and NSTEMI) and identified predictors for its elevated levels. METHODS AND RESULTS: Our population included 1119 consecutive patients (mean age, 67 years; 72% men; and STEMI, 68%). The median Aβ1-40 concentration on admission was 86.9 (interquartile range, 54.5–128.9) pg/mL, and there was no difference in Aβ1-40 levels between NSTEMI and STEMI (P=0.1). Higher Aβ1-40 levels were predicted by older age, lower left ventricular ejection fraction, glycated hemoglobin >39 mmol/mol and glomerular filtration rate <60 mL/min per m2. From the final multivariable model, a nomogram was computed to determine probability of high Aβ1-40. During the median follow-up of 57 months, 193 patients (17.2%) died. Kaplan–Meier analysis revealed higher mortality risk in patients with Aβ1-40 levels above the median (P<0.01), consistent across STEMI (P<0.01) and NSTEMI (P=0.01) subgroups. At Cox multivariable analysis including the entire cohort, Aβ1-40 levels were predictive of death (hazard ratio, 1.03; P=0.01), together with older age, higher high-sensitivity C-reactive protein levels, smoking, glomerular filtration rate <60 mL/min per m2, worse left ventricular ejection fraction, and previous ischemic events. In the STEMI subcohort, Aβ1-40 remained a significant predictor, along with advanced age, worse left ventricular ejection fraction, smoking, and elevated high-sensitivity C-reactive protein. No such association was found in patients with NSTEMI (P=0.17), likely due to the smaller cohort size and low event rate. CONCLUSIONS: Aβ1-40 is an independent predictor of death and improves risk stratification in patients with acute myocardial infarction