Azerbaijan International University

Heart failure (HF) is one of the most complex, dynamic, and resourceintensive cardiovascular syndromes worldwide.It is associated with high morbidity, frequent hospitalizations, and substantial healthcare expenditures. 1Despite major advances in pharmacological and device-based therapies, HF management remains largely reactive and symptom-driven rather than proactive.Moreover, adherence to guideline-directed therapy by both physicians and patients remains suboptimal.

Heart failure (HF) is a progressive, multisystem syndrome characterized by recurrent decompensation, high hospitalization rates, and substantial mortality. Conventional HF management is mainly episodic and often fails to detect worsening conditions in advanced disease. Digital medicine and remote patient monitoring (RPM) hold promise for advancing HF care by enabling earlier detection, proactive action, and personalized care. We conduct a narrative review to summarize evidence from randomized clinical trials, real-world registries, and emerging digital health technologies regarding the present and future utility of digital medicine in HF care. There is greater emphasis on pathophysiology-based surveillance, personalized care models, and integration into planned health care pathways. Integrated digital interventions, such as implantable hemodynamic monitoring, organized telemedicine programs, or device-based diagnostic technologies, can minimize HF hospitalizations, prolong life, improve quality of life, and optimize resource utilization in health care systems when incorporated into coordinated care. Crucially, trials emphasize that clinical benefit depends not on technology but on a prompt clinical response, multidisciplinary cooperation, and ongoing interaction between the patient and the doctor. New technologies-including voice-based biomarkers, smartphone-derived photoplethysmography, ballistocardiography, and artificial intelligence-driven data integration-may help transition RPM from a hardware-based system to a scalable, "deviceless" approach. Digital medicine is a game-changer for reimagining HF care, involving not only continuous monitoring of physiological changes but also personalized, proactive clinical decision-making. To implement truly patient-centered, predictive HF management in the years to come, technological innovation must be combined with human connection, ethical governance, and health-system readiness.

The stability of underground excavations is a critical factor in the safety and efficiency of mining operations, particularly in structurally complex and geomechanically variable rock mass. This study presents a comparative evaluation of empirical and numerical methods for the design of tunnel support systems in the Gilar underground mine, located in the Gedabek Contract Area of Azerbaijan. To validate and optimize the empirical Q-system-based support designs, Finite Element Method (FEM) simulations were conducted using RS2 software. These simulations enabled the modeling of stress distribution, deformation, and support–rock interaction under in situ conditions. Critical sections along the main ramp were analyzed in detail to determine safety factors during excavation and post-support installation. The study reveals that, although the Q-system provides a practical and time-efficient method for support selection, it may underestimate the reinforcement required in highly fractured or low-strength zones. Numerical modeling proved to be essential in identifying zones with low strength factors and in optimizing support configurations by adjusting rockbolt spacing and shotcrete thickness. The hybrid approach adopted in this study—empirical classification followed by numerical verification and optimization—demonstrated significant improvements in long-term tunnel stability. This research highlights the importance of integrating empirical and numerical approaches for robust ground support design in underground mining. The proposed methodology not only enhances the accuracy of support recommendations but also provides a more reliable basis for decision-making in complex geological settings. The results are particularly relevant for deep and geologically active mines requiring long-term stability of access tunnels.

Abstract Objective To evaluate the technical feasibility of isolating fetal trophoblasts and detecting fetal chromosomal anomalies (trisomy 21 and XY chromosomes) using cervical smear samples obtained during routine prenatal care, and to explore the potential of this approach as a preliminary step towards a cost-effective alternative to current non-invasive prenatal testing methods. Study design Prospective cohort study with fluorescence in situ hybridization (FISH) analysis of cervical smear samples for chromosomal screening. Place and duration Department of Obstetrics and Gynecology, Caspian International Hospital, Azerbaijan, conducted in 2024. Methods Fifty pregnant women between 5 and 15 gestational weeks underwent cervical smear collection via cytobrush during routine prenatal visits. Samples were processed for the isolation of extravillous trophoblasts (EVTs). Successful isolation of EVTs was confirmed by morphological assessment and the presence of HLA-G markers. Samples were then analyzed using FISH methodology with probes specific for chromosomes 21, X, and Y. Ultrasound confirmation of fetal sex and nuchal translucency measurements was performed for initial correlation (Interim Correlation Standard). Automated scanning systems and manual verification were employed for accurate chromosomal analysis. Results Extravillous trophoblasts were successfully isolated in all 50 samples (100% success rate (95% CI: 92.9%-100%)). XY chromosomes were detected in 17 cases (34%), with ultrasound confirming male sex in 6 of 7 eligible cases (85.7% concordance). XX chromosomes were identified in 33 cases (66%), with ultrasound confirming female sex in 12 of 14 cases (85.7% concordance). No trisomy 21 cases were detected in this cohort, precluding the calculation of sensitivity for Trisomy 21 detection. One case presented with nuchal translucency ≥ 3 mm and was referred for amniocentesis, with subsequent normal karyotype confirmed by amniocentesis. FISH analysis demonstrated 100% specificity for chromosomal detection with no false-positive results for the sex chromosomes when correlated with the interim ultrasound standard. Conclusion Cervical smear-based FISH analysis represents a promising non-invasive, cost-effective approach for early fetal chromosomal screening that leverages existing clinical infrastructure. While demonstrating excellent specificity for sex chromosome determination, and technical feasibility of EVT isolation, the absence of Trisomy 21 cases in this pilot cohort limits the assessment of sensitivity for aneuploidy detection. A key limitation of this feasibility study is the use of ultrasound as an interim standard for sex determination; we lacked definitive postnatal follow-up data. Definitive validation will require a subsequent publication with full newborn follow-up data. Larger multicenter studies with known aneuploidy cases are essential to validate sensitivity for trisomy 21 detection and establish clinical implementation protocols. This methodology offers potential advantages in resource-limited settings and could complement current prenatal screening strategies as a preliminary screening tool.

Our findings indicate that the use of a lipodermal flap in one-stage pre-pectoral implant-based breast reconstruction was associated with relatively complication and revision rates in this cohort. However, complications such as skin flap necrosis, capsular contracture, and implant exposure remain concerns. The lipodermal flap technique has been proposed to enhance soft tissue coverage and has been explored as a possible means of reducing these complications. This study aimed to evaluate the impact of lipodermal flaps on reducing postoperative complications and the need for secondary surgical interventions. A retrospective study was conducted on 147 women (294 breasts) aged 18 to 65 years who underwent bilateral one-stage pre-pectoral implant-based reconstruction either with a lipodermal flap or without a lipodermal flap (control group) following mastectomy. The surgical technique involved elevating a well-vascularized lipodermal flap, repositioning it over the implant, and performing closure using an inverted-T scar pattern. Demographic characteristics, tumor features, surgical details, and postoperative complications were analyzed. The primary endpoint was the incidence of complications, and the secondary endpoint was the rate of secondary procedures. The mean age of the patient group was 45.60±10.10 years, whereas that of the control group was 42.39±11.09 years. Skin-sparing mastectomy was performed in 54.5% of the patients and nipple-sparing mastectomy in 45.5%, whereas in the control group the proportions were 45.7% and 54.3%, respectively. Of the 147 implants, 14 (18.2%) were associated with complications in the patient group, whereas 21 patients (30.0%) in the control group were affected with seroma, infection and wound dehiscence being the most common. Revisional surgical interventions were required in 16 patients (20.7%) in the patient cohort and in 12 patients (17.1%) in the control cohort. In both groups, lipodermal flap revision represented the most frequent indication for reoperation (n=3 in each group). Other procedures included capsulotomy combined with autologous fat injection, nipple-areola complex reconstruction, and implant explantation. The findings of this study suggest that one-stage pre-pectoral implant-based breast reconstruction with a lipodermal flap may contribute to a reduction in complication rates and the frequency of revisional surgery. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Abstract Engagement with research has long been recognized as a key driver of improved language teaching practices and teachers’ professional growth. Yet, language teaching practitioners often remain distanced from research activities, thus perpetuating a well‐documented gap between research and practice. While much of the existing scholarship has centered on English language teaching, this study shifts the focus on the rapidly growing field of Spanish language teaching (SLT). Drawing on data from 738 SLT professionals in Spain and the United States, we explore their research engagement and demographic profiles through the lens of communities of practice. Furthermore, we argue that combining these demographic insights with the concept of life capital—the accumulated wealth of one's personal and professional experiences—may uncover the human dimensions that shape a community of practice, thereby opening new avenues for promoting deeper research engagement. Finally, and equally important, by broadening the conversation to include languages other than English and adopting a comparative perspective, this study reveals overlooked factors that shape the research–practice divide, ultimately offering fresh insights and targeted initiatives to reconcile this longstanding research–practice gap.

The article presents one of the concrete examples of building multi-level forecasting models — a two-level hybrid model aimed at predicting natural disasters. The criteria for selecting models are described, including the use of precursory signs, the integration of statistical and expert data, as well as the methodology for analyzing parallel data obtained from different fields. An algorithm for establishing connections between models and events is presented, which is based on both existing statistics and expert assessments in cases where the corresponding statistical data are unavailable. The network structure is considered as a model of similar extended semantic networks, where each vertex represents a hybrid model, and the edges reflect the probabilities of one event leading to another. This approach provides high accuracy of forecasts, multi-level risk assessment, and effective decisions based on spatio-temporal analysis.

Abstract The emergence of Generative Artificial Intelligence (GenAI) is reshaping academic writing and publishing practices. As knowledge curators, applied linguistics journal editors need to respond to GenAI developments. Yet, little is known about their perspectives on GenAI in academic writing and publishing. These perspectives could influence their editorial decisions and journal policies – potentially defining how scholars write for publication. Through in-depth semi-structured interviews, this study explored the perceptions of ten applied linguistics journal editors towards GenAI in academic writing for publication. Analysis shows that the development of GenAI is putting additional strain on the editorial process, which is already struggling. It highlights that current publisher and journal policies on GenAI are ambiguous, leading to confusing and questionable research practices. Editors are cautious about the use of GenAI in applied linguistics research and writing, with only the use of these tools to improve writing quality universally acceptable. Transparency is seen as essential. The findings highlight a pressing need for discipline-specific guidance on the acceptable uses of GenAI in academic publishing and the development of methodological models that detail ways GenAI can be integrated into the field’s rich and diverse research traditions.