Autonomic nervous system dysfunction has been reported in up to 76% of stroke patients 7 days after an acute stroke. Heart rate variability (HRV) is one of the important indicators reflecting the balance of sympathetic and parasympathetic nerves. Therefore, we performed a systematic literature review of existing literature on the association between heart rate variability and the different types of stroke. We included studies published in the last 32 years (1990–2022). The electronic databases MEDLINE and Pubmed were searched. We selected the research which met the inclusion or exclusion criteria. A narrative synthesis was performed. This review aimed to summarize evidence regarding the potential mechanism of heart rate variability among patients after stroke. In addition, the association of clinical characteristics of heart rate variability and stroke has been depicted. The review further discussed the relationship between post-stroke infection and heart rate variability, which could assist in curbing clinical infection in patients with stroke. HRV as a non-invasive clinical monitoring tool can quantitatively assess the changes in autonomic nervous system activity, and further predict the outcome of stroke. HRV could play an important role in guiding clinical practice for autonomic nervous system disorder after stroke.

The Tibeto-Himalayan Region is famous for its geography, climatic influence, and exceptional and immense biodiversity. The “mountain-geobiodiversity hypothesis (MGH)” explores the interaction of topography, climate, and biology in the evolution of mountain biodiversity. We tested this hypothesis in the Himalayas and the Hengduan Mountains on a group of caddisflies that are endemic to this region. We investigated one caddisfly species pair from each mountain respectively, each pair containing one species inhabiting high elevation and one inhabiting low elevation. We incorporated genomic and ecological evidence to reveal population structure, demographic history, and potential habitat range dating back to the last glacial maximum (LGM) of each species. The results indicated that in both mountains, the high-elevation species showed strong local differentiation, while the low-elevation species were shaped by hydro-morphology indicating greater regional dispersal activity. Results of demographic history and species distribution modelling supported demographic expansions for all species during the LGM linked to an increase in potential habitats. Caddisfly species in the Himalayas generally exhibited an East-West oriented dispersal. Species from the Hengduan Mountains showed greater connectivity on the North-South orientation, suggesting that species have a higher chance to survive in the Hengduan Mountains by both in-situ displacement (along the elevational gradients) and long-distance dispersal (along the latitudinal gradients) during glaciation. Our study demonstrates that historical geodiversity and climate fluctuations interact and influence the diversification of caddisflies in the Tibeto-Himalayan Region, thus supporting the MGH.

This paper investigates the finite-time preview saturated control problem for linear parameter-varying systems with input saturation. The external disturbances and input saturation, previewable reference signals, and parameter variations are considered simultaneously. First, using the error system method, we construct an augmented error system with previewed information. This transforms the finite-time preview saturated control problem into a finite-time stabilization problem. Next, static output-feedback controllers are used to guarantee the finite-time boundedness of the closed-loop system. Sufficient conditions guarantee the existence of the desired controllers are obtained using linear matrix inequalities. At last, we use a numerical simulation to show the proposed design method's effectiveness.

Next-Generation sequencing technology has enabled accurate insights into the diet of wildlife species. The protocols for faecal sample collection and extraction of DNA for diet analysis have been different from those focusing on focal species DNA, even in studies combining questions on a focal species and its diet. We designed an experiment to evaluate two protocols and select a single one that will generate both focal species (Asiatic wild ass, Equus hemionus, in Israel) and diet DNA, as an effective strategy to minimize time, efforts, and cost without hampering efficiency. In Protocol A, we swabbed the outer surface of faecal boluses and extracted DNA using a Stool Kit, while for Protocol B, we homogenised faecal matter from inside the bolus followed by extraction using a Powersoil Kit. Protocol A performed significantly better for most of the measures, which included, for the focal species, microsatellite amplification success and the quantity of the GAPDH gene; and for its diet, amplification success of a chloroplast barcoding marker, trnL, number of reads, and plant genus richness and diversity. However, there was no significant difference for the amplification success of a sex-linked marker and plant genus composition. Both protocols yielded results for the focal species and its diet, demonstrating that one single protocol can be used for both purposes; although, a pilot study is recommended to optimise the protocol for specific systems. This strategy may also be useful for studies combining focal species and their gut microbiome and parasitic load.

Title pageTitle: Rust-colored patches of the lower extremity in a COVID-19 patientAuthrors: Jacem Rouatbi1, Mouna Korbi1*, Nouha Ben Abdeljalil2, Hichem Belhadjali1*, Jameleddine Zili1*

Root hemiparasitic Pedicularis kansuensis is an invasive native species in China and has been expanding in the Bayanbulak Grassland of Xinjiang Uygur Autonomous Region over the past decade, threatening the local livestock industry. To understand why this damaging species expands in some areas but not in others, we compared soil water content, soil nutrient status, and plant community structures between heavily infected and non-infected sites. We hypothesized that soil nutrient levels and plant species composition would be more beneficial to the spatial expansion of P. kansuensis in heavily infected areas than in non-infected ones. Quadrat (1 m × 1 m) surveys were carried out in the Bayanbulak Grassland. Species number, percent vegetation cover, aboveground plant biomass, plant height, and relative frequency were recorded. Three topsoil samples were taken at 0–10 cm depth from each quadrat and their nutrient statuses were determined. The results showed that (1) P. kansuensis invasion reduces the species richness of the community compared to the uninvaded area (3.07%), but increases the canopy cover overall (16.99%); (2) soil water content (SW) and soil nutrient content are the main factors that determine invasion by P. kansuensis, and SW plays the more important role; (3) SW controls P. kansuensis leaf stoichiometry, decreases the Ratio of leaf nitrogen (LN) to leaf phosphorus (LP), and affects LP (P < 0.005). Finally, after combining the results, we found that the soil factor accounted for 46.50% and plants accounted for 22.50% of P. kansuensis invasions in the Bayanbulak Grassland.

Leishmania is the causative agent of the tropical neglected disease leishmaniasis and infects macrophages as its definitive host cell . In order to sustain and propagate infections, Leishmania parasites have to complete cycles of exit and re-infection. Yet, the mechanism driving the parasite spread to other cells remains unclear. Recent studies reported pro-inflammatory monocytes as replicative niche of L. major and showed prolonged expression of IL-1β at the site of infection, indicating an activation of the NLRP3 inflammasome and pointing towards pyroptosis as a possible mechanism of parasite spread. To address the species-specific inflammasome activation of human cells we characterized the BLaER1 macrophages as a model for L. major infection. We found that Leishmania can infect, activate and develop in BLaER1 macrophages similar as they can do in primary human macrophages. Harnessing the possibilities of this infection model, we first showed that BLaER1 GSDMD-/- cells, which carry a deletion of the pore-forming protein gasdermin D, are more resistant to pyroptotic cell death and, concomitantly, display a strongly delayed release of intracellular parasite. Using that knockout in a co-incubation assay in comparison with wild type BLaER1 cells, we demonstrate that impairment of the pyroptosis pathway leads to lower rates of parasite spread to new host cells, thus, implicating pyroptotic cell death as a possible exit mechanism of L. major in pro-inflammatory microenvironments.

One of the most serious problems worldwide is heavy metal (HM) pollution. HMs can have a toxic effect on human health and thus cause serious diseases. To date, several methods have been used to clean environments contaminated by HMs, but most of them are expensive, and it is difficult to achieve the desired result. Phytoremediation is currently an effective and affordable processing solution used to clean and remove HMs from the environment. This review article discusses in detail the technology of phytoremediation and mechanisms of HM absorption. In addition, methods are described using genetic engineering of various plants to enhance the resistance and accumulation of HMs. Thus, phytoremediation technology can become an additional aid to traditional methods of purification.

As self-driving cars perform more tasks, new challenges arise. One of these challenging tasks is autonomous driving decision-making due to the uncertainty of the vehicle’s complex environment. This paper provides an overview of decision-making technology and trajectory control for autonomous vehicles. The main common goal in decision-making is to consider uncertainties, unpredictable situations, and driving tasks to propose a global and robust solution adapted to each situation. The main concern is safety. Decision-making falls into three categories. The first is the traditional approach, which often consists of building a rule system and deriving optimal operations. The advantages of such an approach are well known for being easy to understand and applicable to small problems. The second category of decision-making is based on a probabilistic process and, due to its efficiency, has several applications in this area. The third category is learning-based approaches. Once a decision has been made, manipulate the steering angle or accelerator/brake pedals to perform the appropriate action. Two approaches are existing to designing autonomous driving controllers. Either based on imitating human drivers that includes approaches based on the use of driver models such as AI, or the use of approach-based models

Electronic bio-implanted medical devices are essential due to their effectiveness in monitoring, disease diagnosis, patient comfort, and safety. Recently, significant efforts have been undertaken to develop implantable and wireless telemetric biomedical systems. Topics such as appropriate near-field wireless communication design, power use, monitoring devices, high-efficiency energy transfer from external to internal parts (implanted), high communication rates, and the need for low energy consumption all significantly influence the advancement of implantable systems. This study reviews various topics related to near-field wireless power transfer (WPT)-based biomedical applications, including WPT types, comparison of WPT types and methods for medical devices, data transmission for WPT-based modulation techniques, and biomedical implantable systems-based WPT. In addition, it extracts research on WPT topologies with related mathematical models—such as power transfer, transfer efficiency, mutual inductance, quality factor, and coupling coefficient—from the literature. The article discusses the effect of specific absorption rate on patient tissue and highlights challenges and solutions for WPT in biomedical implants. Finally, it presents current issues and future developments.

A Case of TAFRO syndrome after COVID-19 vaccinationHitomi Hirosea, Hitoshi Suzukia,c*, Yukako Umezawaa, Masako Iwasakia, Hiromitsu Fukudaa, Hisatsugu Takaharaa, Shigeki Tomitab, Yusuke Suzukica. Department of Nephrology, b. Department of Pathology, Juntendo University Urayasu Hospital, Chiba, Japan. c. Department of Nephrology, Juntendo University Faculty of Medicine, Tokyo, Japan.Correspondence to:Hitoshi Suzuki, M.D., Ph.DDepartment of Nephrology, Juntendo University Urayasu Hospital2-1-1 Tomioka, Urayasu-shi, Chiba 279-0021, JapanEmail: shitoshi@juntendo.ac.jpKey words: COVID-19, mRNA vaccine, TAFRO syndrome, renal dysfunction

Earthquake ruptures are complex physical processes that may vary with the structure and tectonics of the region in which they occur. Characterizing the factors controlling this variability would provide fundamental constraints on the physics of earthquakes and faults. We investigate this by determining finite source properties from second moments of the stress glut for a global dataset of large strike-slip earthquakes. Our approach uses a Bayesian inverse formulation with teleseismic body and surface waves, which yields a low-dimensional probabilistic description of rupture properties including spatial extent, directivity, and duration. This technique is useful for comparing events because it makes only minor geometric constraints, avoids bias due to rupture velocity parameterization, and yields a full ensemble of possible solutions given the uncertainties of the data. We apply this framework to all great strike-slip earthquakes of the past three decades, and we use the resultant second moments to compare source quantities like directivity ratio, rectilinearity, stress drop, and depth extent. We find that most strike-slip earthquakes have a large component of unilateral directivity, and many of these earthquakes show a mixture of unilateral and bilateral behavior. We also notice that oceanic intraplate earthquakes usually rupture a much larger width of the seismogenic zone than other strike-slip earthquakes, suggesting these earthquakes consistently breach the expected thermal boundary for oceanic ruptures. We also use these second moments to resolve nodal plane ambiguity for the large oceanic intraplate earthquakes and find that the rupture orientation is usually unaligned with encompassing fossil fracture zones.

The overwhelming amount of seismic, geodesic and in-situ observations accumulated over the last 30 years clearly indicate that, from a mechanical point of view, faults should be considered as both damageable elastic solids in which highly localized features emerge as a result of very short-term brittle processes and materials experiencing ductile strains distributed in large volumes and over long time scales. The interplay of both deformation mechanisms, brittle and ductile, give rise to transient phenomena associating slow slip and tremors, known as slow earthquakes, which dissipate a significant amount of stress in the fault system. The physically-based numerical models developed to improve our comprehension of the mechanical and dynamical behaviour of faults must therefore have the capacity to treat simultaneously both deformation mechanisms and to cover a wide range of time scales in a numerically efficient manner. This capability is essential, both for simulating accurately their deformation cycles and for improving our interpretation of the available observations. In this paper, we present a numerically efficient visco-elasto-brittle numerical framework that can simulate transient deformations akin to that observed in the context of subduction zones, over the wide range of time scales relevant for slow earthquakes. We implement the model in idealized simple shear simulations and explore the sensitivity of its behavior to the value of its main mechanical parameters.

Iron (Fe) is an essential micronutrient for phytoplankton, particularly diazotrophs, which are abundant in the Western Tropical South Pacific Ocean (WTSP). Their success depends on the numerous trace metals, particularly iron, released from shallow hydrothermal vents along the Tonga Arc. This study aimed to explore the impact of hydrothermal fluids on particulate trace metal concentrations and biological activity. To identify the composition of sinking particles across a wide area of the WTSP, we deployed sediment traps at various depths, both close and further west of the Tonga Arc. Seafloor sediments were cored at these deployment sites, including at a remote location in the South Pacific Gyre. The sinking particles were composed of a large amount of biological material, indicative of the high productivity of the Lau Basin. A significant portion of this material was lithogenic of hydrothermal origin, as revealed through Al-Fe-Mn tracing. The sinking material showed similar patterns between lithogenic and biogenic fractions, indicating that hydrothermal input within the photic layer triggered surface production. A hydrothermal fingerprint was suggested in the sediments due to the high sedimentation rates and the presence of large, heterogeneous, trace metal-rich particles. The presence of nearby active deep hydrothermal sources was suspected near the Lau Ridge due to the large particle size and the significant enrichment of Fe and Mn. Overall, this study revealed that deep and shallow hydrothermal sources along with submarine volcanism have a significant influence on the biogeochemical signature of particles in the Lau Basin at large spatial and temporal scales.

Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regionally LULCC projections by integrated assessment models. The uncertainty associated with different spatial downscaling methods and its impacts on subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on the impacts on the carbon cycle over ABoVE domain. Specifically, we used the Future Land Use Simulation model (FLUS) and Demeter model to generate 0.25-degree gridded LULCC data with the same input of regional LULCC projections from Global Change Analysis Model, under SSP126 and SSP585. The two sets of downscaled LULCC were used to drive CLM5 to prognostically simulate terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between two LULCC datasets under both SSP126 and SSP585. The LULCC differences further lead to large discrepancies in the spatial patterns of projected carbon cycle variables, which are more than 79% of the contributions of LULCC in 2100. Besides, the difference for LULCC and carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by spatial downscaling process in future LULCC projections and carbon cycle simulations.

The Sustainable Development Goals (SDGs) provide targets for humanity to achieve sustainable development by 2030. A monitoring framework of 248 environmental, social, and economic indicators, reported nationally by 193 UN Member States, tracks progress. The framework includes 92 environmental indicators, most of which refer to environmental policies. The SDG monitoring framework provides data to assess whether, across countries, environmental policies are: 1. Addressing environmental pressures, 2. Linked to environmental improvements, and 3. Linked with societal benefits delivered by healthy environments. We use statistical analysis and a generalized linear modeling approach to test for correlations between SDG indicators related to environmental policies, environmental pressures, the state of the environment, and social impacts delivered by healthy environments. Our results show that environmental policies, particularly protected areas and sustainable forest certification, are linked with environmental improvements, mainly in forest and water ecosystems. However, we find no evidence that environmental improvements are linked with positive social impacts. Finally, environmental pressures, including freshwater withdrawal, domestic material consumption, and tourism, are linked with environmental degradation. Environmental policy responses are generally increasing across countries. Despite this, the state of the environment globally continues to decline. Governments must focus on understanding why environmental policies have not been sufficient to reverse environmental decline, particularly concerning the pressures that continue to degrade the environment. To better track progress towards sustainable development, we recommend that the SDG monitoring framework is supplemented with additional indicators on the state of the environment.

Fire is a crucial factor in terrestrial ecosystems playing a role in disturbance for vegetation dynamics. Process-based fire models quantify fire disturbance effects in stand-alone dynamic global vegetation models (DGVMs) and their advances have incorporated both descriptions of natural processes and anthropogenic drivers. Nevertheless, these models show limited skill in modeling fire events at the global scale, due to stochastic characteristics of fire occurrence and behavior as well as the limits in empirical parameterizations in process-based models. As an alternative, machine learning has shown the capability of providing robust diagnostics of fire regimes. Here, we develop a deep-learning-based fire model (DL-fire) to estimate daily burnt area fraction at the global scale and couple it within JSBACH4, the land surface model used in the ICON ESM. The stand-alone DL-fire model forced with meteorological, terrestrial and socio-economic variables is able to simulate global total burnt area, showing 0.8 of monthly correlation (rm) with GFED4 during the evaluation period (2011-15). The performance remains similar with the hybrid modeling approach JSB4-DL-fire (rm=0.79) outperforming the currently used uncalibrated standard fire model in JSBACH4 (rm=-0.07). We further quantify the importance of each predictor by applying layer-wise relevance propagation (LRP). Overall, land properties, such as fuel amount and water content in soil layers, stand out as the major factors determining burnt fraction in DL-fire, paralleled by meteorological conditions over tropical and high latitude regions. Our study demonstrates the potential of hybrid modeling in advancing fire prediction in ESMs by integrating deep learning approaches in physics-based dynamical models.

InSight’s seismometers recorded more than 1300 events. Ninety-eight of these, named the low-frequency family, show energy predominantly below 1 Hz down to ∼0.125 Hz. The Marsquake Service identified seismic phases and computed distances for 42 of these marsquakes, 26 of which have backazimuths. Hence, the locations of the majority of low-frequency family events remain undetermined. Here, we use an envelope shape similarity approach to determine event classes and distances, and introduce an alternative method to estimate the backazimuth. In our similarity approach, we use the highest quality marsquakes with well-constrained distance estimates as templates, including the largest event S1222a, and assign distances to marsquakes with relatively high signal-to-noise ratio based on their similarities to the template events. The resulting enhanced catalog allows us to re-evaluate the seismicity of Mars. We find the Valles Marineris region to be more active than initially perceived, where only a single marsquake (S0976a) had previously been located. We relocated two marsquakes using new backazimuth estimates, which had reported distances of ∼90o, in the SW of the Tharsis region, possibly at Olympus Mons. In addition, two marsquakes with little or no S-wave energy have been located in the NE of the Elysium Bulge. Event epicenters in Cerberus Fossae follow a North-South trend due to uncertainties in location, while the fault system is in the NW-SE direction; therefore, these events are re-projected along the observed fault system.

Using a three-dimensional coupled physical-biological model, this paper explores the creation of phytoplankton blooms around tropical islands in the presence of ambient currents and short-lived (~4 days) wind events. The ambient flow creates a retention zone of weak flows in the lee of the island, which is a typical feature of island wakes. Findings reveal that wind-induced upwelling effects are essential for the initial nutrient enrichment and phytoplankton growth that occur mainly in this retention zone. Oscillating flow, typical of island wakes, occasionally releases mesoscale patches of upwelled water and its phytoplankton load into the ambient ocean. The phytoplankton continues to grow within floating structures that are of up to 20 km in diameter. This mechanism complements the plankton growth associated with the formation of mesoscale eddies.

Dynamical models used in climate prediction often have systematic errors that can deteriorate predictions. In this study, we work in a twin experiment framework with a reduced-order coupled ocean-atmosphere model and aim to demonstrate the benefit of machine learning for climate prediction. Machine learning is applied to learn the model error and thus build a data-driven model to emulate the dynamical model error. Then we build a hybrid model by combining the data-driven and dynamical models. The prediction skill of the hybrid model is compared to that of the standalone dynamical model. We applied this approach to the ocean-atmosphere coupled model. The results show that the hybrid model outperforms the dynamical model alone for both atmospheric and oceanic variables. Also, we build two other hybrid models only correcting either atmospheric errors or oceanic errors. It was found that correcting both atmospheric and oceanic errors leads to the best performance.

Mechanical properties of living cells play an important role in helping to understand cell physiology and pathology. However, to ensure reliability, it is important to precisely define the experimental conditions of these mechanical test. In this study, viscoelastic properties of the outer layer (cytoplasm and membrane) were extracted using standard linear solid model. Finite element modeling of the two-layer cell was performed and the model was validated by experimental data. In the two-layer model, the effect of the radius of the nucleus and the location of the nucleus on the whole cell behavior were investigated. By increasing nucleus size, the whole cell properties follow the nucleus properties and the role of the nucleus becomes more dominant. By dislocating nucleus inside the cytoplasm, the cell behavior changes significantly and becomes more similar to that of nucleus properties. Similarly, changing the aspiration pressure and rate, impacts the observed behavior drastically. The results demonstrate that the location of the nucleus and the ratio of the radius of the cytoplasm to the radius of the nucleus can effectively influence the viscoelastic properties and mechanical behavior of the cell.

Purpose: With the expansion of research utilizing electronic healthcare data to identify transgender (TG) population health trends, the validity of computational phenotype algorithms to identify TG patients is not well understood. We aim to identify the current state of the literature that has utilized CPs to identify TG people within electronic healthcare data and their validity, potential gaps, and a synthesis of future recommendations based on past studies. Methods: Authors searched the National Library of Medicine’s PubMed, Scopus, and the American Psychological Association Psyc Info’s databases to identify studies published in the United States that applied CPs to identify TG people within electronic health care data. Results: Twelve studies were able to validate or enhance the positive predictive value (PPV) of their CP through manual chart reviews (n=5), hierarchy of code mechanisms (n=4), key text-strings (n=2), or self-surveys (n=1). CPs with the highest PPV to identify TG patients within their study population contained diagnosis codes and other components such as key text-strings. However, if key text-strings were not available, researchers have been able to find most TG patients within their electronic healthcare databases through diagnosis codes alone. Conclusion: CPs with the highest accuracy to identify TG patients contained diagnosis codes along with components such as procedural codes or key text-strings. CPs with high validity are essential to identifying TG patients when self-reported gender identity is not available. Still, self-reported gender identity information should be collected within electronic healthcare data as it is the gold standard method to better understand TG population health patterns.

Evaluating Serum HE4: Some Serious ConsiderationsAimen Waqar Khana, Hussain Haider Shahba: Department of Medicine, Jinnah Sindh Medical University, Karachi, Pakistan.b: Department of Medicine, Dow University of Health Sciences, Karachi, Pakistan.Dear Dr Papageorghiou,We have perused with great interest the scholarly article ”Serum HE4 predicts progestin treatment response in endometrial cancer and atypical hyperplasia: A prognostic study” by Chloe Barr et al. [1]. We applaud the authors’ diligent efforts in investigating a biomarker that could independently predict the response to conservative therapy. However, we wish to draw attention to certain noteworthy aspects upon a comprehensive evaluation.Firstly, it is noteworthy that all the women who participated in the study underwent a preliminary endometrial biopsy before the initiation of progestin. However, there is no mention of whether women with relative contraindications such as cervical stenosis, coagulopathy or obstructive cervical lesions were sampled if they were included in the study. It is essential to consider these factors as they can significantly affect the accuracy and reliability of the biopsy results. Furthermore, it is necessary to note that insufficient tissue sampling is a common complication of endometrial biopsy, with an average of 31% of tissues obtained requiring improvement [2]. Considering that this is typically more prevalent in postmenopausal women, and 61% of the participants were 50 years or older, it is crucial to standardize the volume of tissue obtained to ensure fair and precise results. As outlined in the study, the primary form of progestin therapy was levonorgestrel-releasing intrauterine system (LNG-IUS). Still, for women whose devices had been misplaced more than once, an alternative treatment of oral medroxyprogesterone acetate 500mg was administered twice daily. This raises a concern regarding whether these women were closely monitored for compliance with the prescribed treatment regimen. This is particularly important as non-compliance, particularly with extended oral therapies, is a common issue that, if present, could skew the study’s findings. The prognostic potential of pretreatment serum HE4 in predicting therapeutic response has been extensively researched; however, studies have also reported elevated serum HE4 levels in various other cancers, including ovarian, pancreatic, breast, lung, and stomach [3]. Therefore, it is crucial to exclude such patients thoroughly, as their inclusion could lead to inaccurate results by falsely accounting for the non-responder count.Moreover, serum HE4 levels are also known to be influenced by renal function and status, necessitating adjustment [4]. It is, therefore, essential to consider and standardize these factors when analyzing the serum HE4 levels to obtain reliable and valid results. Lastly, it should be noted that a CLEIA technique was employed for analysis, which has been reported to significantly overestimate serum HE4 as compared to EIA [5]. This may raise concerns regarding the validity of the reported findings, and hence, caution must be exercised when interpreting the results.The study focused on endometrial biopsy in women receiving progestin therapy, but potential complications such as insufficient tissue sampling and the inclusion of women with contraindications were not addressed. The study primarily used LNG-IUS but also administered oral medroxyprogesterone acetate, and compliance monitoring was not discussed. Serum HE4 levels were examined, but patients with other cancers or renal issues were not excluded, and the CLEIA technique used for analysis may have overestimated results. Therefore, caution is necessary when interpreting the findings of this study.

A fast ventricular tachycardia was apparently induced in a patient with a CRT-D device by the delivery of a pacemaker stimulus whose timing corresponded with the timing of the QRS complex in the far-field electrogram. Appropriate programming of the device might have prevented this complication.