High-risk Scenarios Research Articles

U-Space Contingency Management Based on Enhanced Mission Description

Loss of communication, low battery, or bad weather conditions (like high-speed wind) are currently managed by performing a return to launch (RTL) point maneuver. However, the execution of this procedure can pose a safety threat since it has not been considered within the mission planning process. This work proposes an advanced management of contingency events based on the integration of a new U-space service that enhances mission description. The proposed new service, deeply linked to demand capacity balance and strategic deconfliction services, assigns alternative safe landing spots by analyzing the planned mission. Two potential solutions are characterized (distinguished primarily by the number of contingency vertiports assigned): contingency management based on the assignment of a single alternative vertiport to each mission (static) or the allocation of a set of different contingency vertiports that are valid during certain time intervals. It is proven that this enhanced mission planning could ensure that U-space volumes operate in an ultra-safe system conditions while facing these unforeseen events, highlighting its importance in high-risk scenarios like urban air mobility deployments.

Estimating best nanomaterial for energy harvesting through reinforcement learning DQN coupled with fuzzy PROMETHEE under road-based conditions

Energy harvesters based on nanomaterials are getting more and more popular, but on their way to commercial availability, some crucial issues still need to be solved. The objective of the study is to select an appropriate nanomaterial. Using features of the Reinforcement Deep Q-Network (DQN) in conjunction with Fuzzy PROMETHEE, the proposed model, we present in this work a hybrid fuzzy approach to selecting appropriate materials for a vehicle-environmental-hazardous substance (EHS) combination that operates in roadways and under traffic conditions. The DQN is able to accumulate useful experience of operating in a dynamic traffic environment, accordingly selecting materials that deliver the highest energy output but at the same time bring consideration to factors such as durability, cost, and environmental impact. Fuzzy PROMETHEE allows the participation of human experts during the decision-making process, going beyond the quantitative data typically learned by DQN through the inclusion of qualitative preferences. Instead, this hybrid method unites the strength of individual approaches, as a result providing highly resistant and adjustable material selection to real EHS. The result of the study pointed out materials that can give high energy efficiency with reference to years of service, price, and environmental effects. The proposed model provides 95% accuracy with a computational efficiency of 300 s, and the application of hypothesis and practical testing on the chosen materials showed the high efficiency of the selected materials to harvest energy under fluctuating traffic conditions and proved the concept of a hybrid approach in True Vehicle Environmental High-risk Substance scenarios.

Comparative Diagnostic Efficacy of Abbreviated and Full Protocol Breast MRI: A Systematic Review and a Meta-Analysis.

This meta-analysis aims to compare the efficacy, limitations, and clinical implications of Abbreviated Breast MRI (AB-MRI) and Full Protocol MRI (FP-MRI). It focuses on diagnostic accuracy across various populations and settings, extending the scope of prior meta-analyses by including studies conducted after 2019 in both screening and diagnostic contexts. We conducted a systematic review (from 11/2019 to 12/2022). A bivariate model was used to calculate the summary estimates of sensitivity and specificity. Random effect models were used to calculate summary AUC and probability distributions for negative and positive predictive values were obtained. Subgroup analyses were conducted to investigate the differences between the AB-MRI and FP-MRI in terms of sensitivity, specificity, and AUC. The search across multiple databases yielded 11 eligible studies, including one prospective and ten retrospective studies. Statistical analysis revealed a significant difference in sensitivity between FP-MRI (95%) and AB-MRI (86%, p = 0.005), but not in specificity (p = 0.50). AB-MRI demonstrated a shorter acquisition time, suggesting potential for increased patient throughput. However, challenges remain in detecting small lesions and non-mass enhancements, with some studies suggesting the inclusion of additional sequences such as DWI with ADC mapping to enhance diagnostic performance. While FP-MRI remains the gold standard in breast cancer detection, AB-MRI presents as a viable, quicker alternative, especially useful in high-risk screening scenarios. Its lower sensitivity compared to FP-MRI, however, limits its utility as a standalone diagnostic tool. Future research should focus on optimizing AB-MRI protocols and investigating patient-specific factors to refine breast cancer screening and diagnostic strategies.

Enhancing Planning for Autonomous Driving via an Iterative Optimization Framework Incorporating Safety-Critical Trajectory Generation

Ensuring the safety of autonomous vehicles (AVs) in complex and high-risk traffic scenarios remains a critical unresolved challenge. Current AV planning methods exhibit limitations in generating robust driving trajectories that effectively avoid collisions, highlighting the urgent need for improved planning strategies to address these issues. This paper introduces a novel iterative optimization framework that incorporates safety-critical trajectory generation to enhance AV planning. The use of the HighD dataset, which is collected using the wide-area remote sensing capabilities of unmanned aerial vehicles (UAVs), is fundamental to the framework. Remote sensing enables large-scale real-time observation of traffic conditions, providing precise data on vehicle dynamics, road structures, and surrounding environments. To generate safety-critical trajectories, the decoder within the conditional variational auto-encoder (CVAE) is innovatively designed through a data-mechanism integration method, ensuring that these trajectories strictly adhere to vehicle kinematic constraints. Furthermore, two parallel CVAEs (Dual-CVAE) are trained collaboratively by a shared objective function to implicitly model the multi-vehicle interactions. Inspired by the concept of “learning to collide”, adversarial optimization is integrated into the Dual-CVAE (Adv. Dual-CVAE), facilitating efficient generation from normal to safety-critical trajectories. Building upon this, these generated trajectories are then incorporated into an iterative optimization framework, significantly enhancing the AV’s planning ability to avoid collisions. This framework decomposes the optimization process into stages, initially addressing normal trajectories and progressively tackling more safety-critical and collision trajectories. Finally, comparative case studies of enhancing AV planning are conducted and the simulation results demonstrate that the proposed method can efficiently enhance AV planning by generating safety-critical trajectories.

Drone-Based Localization of Hazardous Chemicals by Passive Smart Dust

The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as smart dust. Several efforts focused primarily on computing and networking capabilities, but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data were processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios.

Anxiety in Pregnancy: Comparing High-Risk and Normal Pregnant Women through the Beck Anxiety Inventory

Aim: Pregnancy is a critical life event that necessitates adaptation to numerous physical and psychological changes. While it often brings positive emotions, it can also induce significant stress and anxiety, especially in high-risk scenarios with potential maternal and fetal health concerns. This study aims to investigate whether there is a difference in anxiety levels between pregnant women under routine obstetric care and those under perinatology care for high-risk pregnancies. Material and Method: This cross-sectional survey was conducted at the Giresun Training and Research Hospital Obstetrics and Gynecology Hospital. Ninety pregnant women aged 18-40 were divided into two groups: 45 women receiving routine obstetric care (Group I) and 45 women receiving perinatology care for high-risk pregnancies (Group II). Data were collected using a 20-question socio-demographic and medical characteristics questionnaire, along with the Beck Anxiety Inventory. Results: The study found no significant difference in socio-demographic characteristics such as education, employment, and income status between the two groups (p>0.05). The Beck Anxiety Inventory scores indicated that both groups predominantly experienced low-level anxiety: 82.2% in Group I and 86.7% in Group II. Moderate anxiety was reported by 15.6% of Group I and 11.1% of Group II. Only 2.2% of participants in each group experienced severe anxiety. There was no significant difference in the overall anxiety levels between the two groups (p>0.05), although Group I reported higher heart palpitations (p

Leading Through Noise: Operating Room Noise Challenges for Staff and Leadership Techniques to Ensure Optimal Operational Performance.

Noise and distractions in the operating room (OR) critically impact surgical performance and patient outcomes, particularly in high-stakes environments such as trauma surgery. While historical hospital environments prioritized quiet to facilitate recovery and reduce stress, contemporary ORs, especially those handling trauma cases, face increasing noise challenges due to advanced surgical instruments, alarms, and staff conversations, often surpassing federal exposure limits. This review investigates OR noise sources, including staff activities and equipment, analyzing their effects on cognitive load, communication, and error rates among healthcare workers. It identifies high-risk scenarios and vulnerable groups, highlighting the necessity for targeted interventions. Key strategies include implementing strict noise control policies, using noise-reducing materials in OR design, and educating staff on noise impacts. Additionally, structured communication protocols and continuous monitoring systems are advocated to enhance operational efficiency and safety. Surgeon leadership is pivotal in balancing assertiveness and empathy to maintain a productive team dynamic. Furthermore, surgeons significantly boost OR efficiency and safety by adopting these protocols, promoting inclusive team dynamics, and applying noise-reduction strategies. These practices safeguard patient care and foster a more collaborative work atmosphere, aligning all team efforts toward optimal patient outcomes. This holistic approach emphasizes the need for continuous improvement and adaptability in surgical practices to meet modern healthcare demands, particularly in trauma surgery's fast-paced, unpredictable realm. Collectively, these measures can enhance patient safety and improve conditions for surgical teams, providing a framework for quieter, more focused OR environments that ultimately elevate surgical outcomes and healthcare quality.

High-risk powered two-wheelers scenarios generation for autonomous vehicle testing using WGAN

Objective Autonomous vehicles (AVs) have the potential to revolutionize the future of mobility by significantly improving traffic safety. This study presents a novel method for validating the safety performance of AVs in high-risk scenarios involving powered 2-wheelers (PTWs). By generating high-risk scenarios using in-depth crash data, this study is devoted to addressing the challenge of public road scenarios in testing, which often lack the necessary complexity and risk to effectively evaluate the capabilities of AVs in high-risk situations. Method Our approach employs a Wasserstein generative adversarial network (WGAN) to generate high-risk scenes, particularly focusing on PTW scenarios. By extracting 314 car-to-PTW crashes from the China In-depth Mobility Safety Study–Traffic Accident database, we simulate outcomes using PC-Crash software. The data are divided into scenes at 0.1-s intervals, with WGAN generating numerous high-risk scenes. By using a cumulative distribution function (CDF), we sampled and analyzed the vehicle’s dynamic information to generate complete scenarios applicable to the test. The validation process involves using the SVL Simulator and the Baidu Apollo joint simulation platform to evaluate the AV’s driving behavior and interactions with PTWs. Results This study evaluates model generation results by comparing distributions using Wasserstein distance as an indicator. The generator converges after approximately 200 epochs, with the iterator converging quickly. Subsequently, 10,000 new scenes are then generated. The distribution of several key parameters in the generated scenes can be found to approximate that of the original scenes. After sampling, the usability of generated scenarios is 64.76%. Virtual simulations confirm the effectiveness of the scenario generation method, with a generated scenario crash rate of 16.50% closely reflecting the original rate of 15.0%, showcasing the method’s capacity to produce realistic and hazardous scenarios. Conclusions The experimental results suggest that these scenarios exhibit a level of risk similar to the original crashes and are effective for testing AVs. Consequently, the generated scenarios enhance the diversity of the scenario library and accelerate the overall testing process of AVs.

Support Vector Machine based Data Hacking Prediction using PMU Data

As global reliance on power systems grows due to increasing energy demands and modern consumption patterns, maintaining the stability and reliability of the power grid has become crucial. Power systems are complex and nonlinear, and their operations are continuously evolving, making it difficult and expensive to ensure stability. Traditionally, power systems are designed to handle a single outage at a time. However, recent years have seen several significant blackouts, each originating from a single failure, which have been extensively reported. These reports are vital for mitigating operational risks by strengthening systems against identified high-risk scenarios. While extensive research has been conducted on these blackouts, cyber- attacks introduce a new dimension of risk. The advent of Phasor Measurement Units (PMUs) has enabled centralized monitoring of power system data, allowing for more effective fault and cyber-attack detection.This paper proposes a machine learning-based approach to detecting cyber-attacks using PMU data. Given the complexity and volume of power system data, traditional mathematical and statistical methods are challenging to implement. Instead, a Support Vector Classification (SVC) algorithm is used for binary classification, distinguishing between 'attack' and 'normal' states. The algorithm is trained on PMU data and evaluated using metrics such as the AUC-ROC curve and confusion matrix, achieving an 82% AUC- ROC score, demonstrating its effectiveness in identifying cyber- attacks.

Robotic mitral surgery: recent advances and outcomes.

This review explores recent advancements in robotic cardiac surgery, specifically focusing on its application in diverse mitral valve surgeries. The aim is to provide an overview of current clinical practices and supporting evidence in this evolving field. A literature review indicates a 30% surge in robotic mitral valve repair from 2015 to 2021, paralleled by a decline in sternotomy-based repair per the STS database. Robotic mitral valve repair consistently shows effective and safe outcomes, with comparable mortality but lower morbidity risks than sternotomy and thoracotomy. The robotic approach exhibits lower conversion to valve replacement, shorter ICU stays, and reduced 30-day readmissions. For experienced programs, robotic techniques prove versatile in various pathologies, including rheumatic heart valve disease, infective endocarditis, ischemic cardiomyopathy, and mitral annular calcification necessitating valve replacement. Literature supports their selective use in high-risk scenarios, including redo surgeries and elderly patients. Recent evidence supports the growing use of robotic approaches in mitral valve surgery, highlighting their efficacy with comparable mortality rates but lower morbidity risks. Robotic techniques consistently yield positive outcomes across various pathologies and patient profiles, signaling a potential paradigm shift in mitral valve interventions.

Advancing Allogeneic Hematopoietic Stem Cell Transplantation Outcomes through Immunotherapy: A Comprehensive Review of Optimizing Non-CAR Donor T-Lymphocyte Infusion Strategies.

Optimized use of prophylactic or therapeutic donor lymphocyte infusions (DLI) is aimed at improving clinical outcomes in patients with malignant and non-malignant hematological diseases who have undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). Memory T-lymphocytes (CD45RA-/CD45RO+) play a crucial role in immune reconstitution post-HSCT. The infusion of memory T cells is proven to be safe and effective in improving outcomes due to the enhanced reconstitution of immunity and increased protection against viremia, without exacerbating graft-versus-host disease (GVHD) risks. Studies indicate their persistence and efficacy in combating viral pathogens, suggesting a viable therapeutic avenue for patients. Conversely, using virus-specific T cells for viremia control presents challenges, such as regulatory hurdles, cost, and production time compared to CD45RA-memory T lymphocytes. Additionally, the modulation of regulatory T cells (Tregs) for therapeutic use has become an important area of investigation in GVHD, playing a pivotal role in immune tolerance modulation, potentially mitigating GVHD and reducing pharmacological immunosuppression requirements. Finally, donor T cell-mediated graft-versus-leukemia immune responses hold promise in curbing relapse rates post-HSCT, providing a multifaceted approach to therapeutic intervention in high-risk disease scenarios. This comprehensive review underscores the multifaceted roles of T lymphocytes in HSCT outcomes and identifies avenues for further research and clinical application.

Utilizing Leadless Pacemakers in Extremely Elderly Patients With a Conventional Pacemaker System: A Two-Year Follow-Up Case Series Without Generator Extraction in High-Risk Scenarios.

Background and objectives Leadless pacemakers, known for their safer clinical profile, offer significant advantages for elderly patients at a higher risk of complications associated with transvenous pacemaker procedures, particularly those susceptible to high-risk bleeding and infections related to cardiac implantable electronic device interventions. This study explores an alternative use of leadless pacemakers without removing existing transvenous systems, deviating from conventional generator replacement and lead re-interventions. Methods This study was conducted with full approval from the Institutional Review Board, Medical Ethical Committee, Centro Hospitalar Conde São Januário, Macau. Between January 2018 and December 2021, we conducted a retrospective case series involving extremely elderly individuals (aged 85 years or older) at a high risk of complications, necessitating either generator replacement or lead re-implantation. The study considered implanting a leadless pacemaker (Micra; Medtronic,Minneapolis, MN, USA) without removing the transvenous generator. For the primary endpoints, we evaluated procedure-related complications and clinical outcomes during hospitalization. Secondary endpoints included the stability of parameters and any unexpected interference or interactions between the two systems during the two-year follow-up. Results Eleven patients (aged 86-101) were enrolled, most receiving antiplatelet or anticoagulation therapy. Leadless pacemaker implantation proceeded without major complications or adverse clinical outcomes during hospitalization. Regular follow-up was conducted every three to six months for adjusting pacemaker parameters and interrogating each patient. Over two years, three patients died from non-cardiac causes: two from infection and one from spontaneous intracranial hemorrhage, while eight completed regular follow-ups. We didn't detect any episodes of ventricular arrhythmias or intracardiac capture from the transvenous pacemaker system. We observed the stability in both the longevity and the voltage of the conventional generator battery, maintaining similar parameters without significant depletion (mean voltage decline: -0.07V/year). Parameters of the leadless pacemaker remained consistently normal without interference with existing pacing systems. Conclusion Implanting leadless pacemakers without removing transvenous pacemaker generators appears safe and effective for extremely elderly patients who are at high risk of complications. Comprehensive two-year follow-up supports the safety and viability of this approach. Opting for this approach instead of conventional generator replacement, with or without additional lead implantation, may be reasonable in this population. However, further research within this patient cohort, such as exploring long-term outcomes beyond two years or comparing clinical outcomes with conventional strategies, may be necessary.

Evolution of Treatment Strategies for Gestational Trophoblastic Neoplasia: Chemotherapy, Immunotherapy, and Molecular Targeted Therapy.

In addressing Gestational Trophoblastic Neoplasia (GTN), it is imperative to acknowledge the evolving landscape of treatment options, especially in light of the challenges posed by traditional methods. While historically, surgical interventions, radiation therapy, and chemotherapeutic agents have been the mainstays, the emergence of resistance and high-risk scenarios necessitates a reevaluation of our therapeutic approaches. Our review highlights the promising advancements in immunotherapy and molecular targeted therapy as viable alternatives for GTN management. The introduction of immune checkpoint inhibitors and kinase inhibitors offers a paradigm shift, particularly for patients resistant to conventional chemotherapy regimens. These novel therapies not only exhibit efficacy but also demonstrate manageable toxicity profiles, particularly in high-risk cases. However, integrating these innovative treatments into established international guidelines presents a formidable task. As we move forward, it is imperative that future research not only prioritizes fertility preservation but also rigorously evaluates long-term toxicity implications. International collaboration becomes pivotal in addressing the nuances of this rare and complex disease. In conclusion, our review underscores the need for a nuanced approach to GTN treatment, one that prioritizes reduced toxicity and improved quality of life. By embracing the advancements in immunotherapy and molecular targeted therapy, we can pave the way for more effective and patient-centered care in the management of GTN.

Strain-Temperature Dual Sensor Based on Deep Learning Strategy for Human-Computer Interaction Systems.

Thermoelectric (TE) hydrogels, mimicking human skin, possessing temperature and strain sensing capabilities, are well-suited for human-machine interaction interfaces and wearable devices. In this study, a TE hydrogel with high toughness and temperature responsiveness was created using the Hofmeister effect and TE current effect, achieved through the cross-linking of PVA/PAA/carboxymethyl cellulose triple networks. The Hofmeister effect, facilitated by Na+ and SO42- ions coordination, notably increased the hydrogel's tensile strength (800 kPa). Introduction of Fe2+/Fe3+ as redox pairs conferred a high Seebeck coefficient (2.3 mV K-1), thereby enhancing temperature responsiveness. Using this dual-responsive sensor, successful demonstration of a feedback mechanism combining deep learning with a robotic hand was accomplished (with a recognition accuracy of 95.30%), alongside temperature warnings at various levels. It is expected to replace manual work through the control of the manipulator in some high-temperature and high-risk scenarios, thereby improving the safety factor, underscoring the vast potential of TE hydrogel sensors in motion monitoring and human-machine interaction applications.

Effect of spatial relationship between curves on crash severity at horizontal curves in a mountainous terrain

The study aimed to model the effect of spatial relationship between adjacent curves on the severity of curve-based crashes along with driver and crash causal characteristics, reflecting driver’s short-term expectancy. The crash and other associated data was retrieved from the web-based Road Accident Data Management System available in Himachal Pradesh, India, and curvature attributes were extracted using GIS. Overall, the study included 1113 curve based crashes. The driver’s perception of the sharpness of a curve was quantified as a single representative categorical factor based simultaneously on its length and radius using K-Medoid Clustering. Separate crash severity models catering to the two possible approach directions of the subject curve were developed reflecting its independent interaction with its corresponding adjacent curve in each direction. Partial Proportional Odds models were developed to overcome the predictive limitations of Ordinal and Multinomial logit models. Indicators of spatial relationship and the intensity of sharpness of the subject curve were found to be statistically significant. A sharp approach curve (radius:40–60 m) increased the risk of fatality by 2.16 times with a similar increase (2.5 times) observed for a short (length:30–60 m) adjacent curve. Adjacent curves turning in the same direction were 2.34 times more prone to fatalities. A very sharp subject curve with radius ≤ 40 m increased the risk of fatal crashes by 2.5 times, as did the short subject curves (30–60 m) (at least 3 times). Subject curves characterized by a short length and a very sharp curvature contributed relatively 3–4 times more to fatal crashes. The identified risk factors and their impact can help the relevant stakeholders to take appropriate actions and can further assist them in identifying high risk scenarios.

Surgical Strategies in Reoperation of the Proximal Aorta and Arch for Patients with Previous Frozen Elephant Trunk.

Background: The frozen elephant trunk (FET) technique is increasingly utilized for aortic arch replacement in cases of aortic dissections and aneurysms. This rise in usage has led to more patients needing redo aortic surgeries due to progression of existing conditions, FET-related complications, or new valvular/coronary diseases. This article aims to evaluate surgical techniques to minimize risks during these reoperations, including a case study of a complex redo surgery. Methods: A comprehensive examination of surgical strategies was conducted, focusing on preoperative preparation, cannulation site identification, cerebral and cardiac protective measures, and pitfalls to avoid. The importance of adapting to the modified anatomical landscape post-FET is emphasized. A detailed case study of a patient undergoing complex redo FET surgery is included. Results: The article identified key surgical strategies for reoperation in patients with prior FET, highlighting the importance of meticulous preoperative planning and execution. Techniques to minimize risks include detailed imaging for planning, strategic cannulation for optimal perfusion, multidisciplinary approaches as well as careful fail-safe measures. The case study demonstrates the practical application of these strategies in a high-risk scenario. The evidence underscores the necessity for individualized patient management and the development of standardized protocols. Conclusions: The FET technique, while effective for initial aortic arch repairs, often necessitates complex reoperations. Adopting advanced surgical strategies and multidisciplinary planning can significantly mitigate risks associated with these procedures. Future research should focus on refining these techniques and establishing standardized protocols to improve patient outcomes.

Development of Salmonella enterica serovar Typhimurium, Listeria monocytogenes, and Pseudomonas aeruginosa multi-species in vitro dry surface biofilm models: Insights into resilience and persistence in low-moisture environments

Salmonella enterica serovar Typhimurium, Listeria monocytogenes, and Pseudomonas aeruginosa can persist as dry surface biofilms (DSB) and survive desiccation for prolonged periods of time. This could serve as potential sources of contamination in low-moisture food (LMF) processing environments. The objectives of this study were to develop in vitro mono-and mix-culture DSB models to better understand pathogen survival under dehydrated conditions as DSB. Mono-and mix-culture wet surface biofilms (WSB) of S. enterica ser. Typhimurium ATCC 14028, L. monocytogenes FSL R8-5318, and P. aeruginosa ATCC 15442 were developed following EPA MLB SOP MB-19 protocol on borosilicate glass coupons using a CDC® biofilm reactor. WSB were harvested and dried for 24, 48, and 72 h at 21 °C to form DSB. Mean log10 CFU/cm2 were calculated at each desiccation time point and compared to control (WSB) using LSM of PROC GLM to fit linear models (P = 0.05). Approximately 8.8 ± 1.7, 7.1 ± 1.1, 6.9 ± 0.6, and 6.3 ± 0.8 mean log10 CFU/coupon were recovered from mono-culture Salmonella DSB at 0, 24, 48, and 72 h, respectively. Overall, Salmonella mean log10 densities were limited when co-cultured with P. aeruginosa although there were no significant differences in Salmonella density over desiccation time points. Mean log10 CFU/coupon for L. monocytogenes monoculture DSB were comparatively lower i.e., 5.7 ± 0.4 (0 h), 3.8 ± 0.1 (24 h), and 3.4 ± 0.6 (48 h), and 2.6 ± 0.3 (72 h). However, when co-cultured with P. aeruginosa, L. monocytogenes exhibited consistently higher cell densities 6.7 ± 0.4, 6.0 ± 0.9, 5.6 ± 0.04, and 4.9 ± 0.6, at 0, 24, 48, and 72 h, respectively. On average, P. aeruginosa consistently exceeded six log10 at each desiccation time point in co-culture. Confocal laser scanning microscopy (CLSM) images confirmed biofilm development and persistence over time in mono and mixed cultures. This work provides foundational evidence toward better understanding pathogen survival under dehydrated conditions, interactions between different pathogens within desiccated biofilms, and their respective survival rates. Additionally, these data provide quantitative assessment of bacterial load within DSB under high-risk scenarios for LMFs. These models provide opportunities to explore targeted mitigation strategies, including efficacy of dry sanitation practices, to prevent the formation or remove DSB in LMF processing environments.

Cardiogenic shock and infection: A lethal combination

BackgroundCardiogenic shock and sepsis are severe haemodynamic states that are frequently present concomitantly, leading to substantial mortality. Despite its frequency and clinical significance, there is a striking lack of literature on the outcomes of combined sepsis and cardiogenic shock. MethodsFRENSHOCK was a prospective registry including 772 patients with cardiogenic shock from 49 centres. The primary endpoint was 1-month all-cause mortality. Secondary endpoints included heart transplantation, ventricular assistance device and all-cause death rate at 1year. ResultsAmong the 772 patients with cardiogenic shock included, 92 cases were triggered by sepsis (11.9%), displaying more frequent renal and hepatic acute injuries, with lower mean arterial pressure. Patients in the sepsis group required broader use of dobutamine (90.1% vs. 81.2%; P=0.16), norepinephrine (72.5% vs. 50.8%; P<0.01), renal replacement therapy (29.7% vs. 14%; P<0.01), non-invasive ventilation (36.3% vs. 24.4%; P=0.09) and invasive ventilation (52.7% vs. 35.9%; P=0.02). Sepsis-triggered cardiogenic shock resulted in higher 1-month (41.3% vs. 24.0%; adjusted hazard ratio: 1.94, 95% confidence interval: 1.36–2.76; P<0.01) and 1-year (62.0% vs. 42.9%; adjusted hazard ratio 1.75, 95% confidence interval 1.32–2.33; P<0.01) all-cause death rates. No significant difference was found at 1year for heart transplantation or ventricular assistance device (8.7% vs. 10.3%; adjusted odds ratio 0.72, 95% confidence interval 0.32–1.64; P=0.43). In patients with sepsis-triggered cardiogenic shock, neither the presence of a preexisting cardiomyopathy nor the co-occurrence of other cardiogenic shock triggers had any additional impact on death. ConclusionsThe association between sepsis and cardiogenic shock represents a common high-risk scenario, leading to higher short- and long-term death rates, regardless of the association with other cardiogenic shock triggers or the presence of preexisting cardiomyopathy.

Bleomycin-induced pulmonary hypertension: an underrated phenomenon with important implications in the setting of high-risk clinical scenarios.

Bleomycin-induced pulmonary hypertension: an underrated phenomenon with important implications in the setting of high-risk clinical scenarios.

Physicians' perceptions and awareness of adverse effects of proton pump inhibitors and impact on prescribing patterns.

Background: Heightened scrutiny surrounds the inappropriate use of proton pump inhibitors (PPIs) due to concerns regarding potential serious adverse effects (AEs). Understanding the impact of these AEs on real-world practice is crucial. This study aimed to assess physicians' perceptions, experiences, awareness, and beliefs regarding published data on potential AEs associated with PPIs. Additionally, it sought to determine alterations in PPI prescribing patterns resulting from these AEs, explore attitudes towards PPI use, and ascertain recommendations for PPI use in clinical scenarios with varying levels of risk for upper gastrointestinal bleeding (UGIB). Method: A quantitative, cross-sectional study utilized a self-administered questionnaire, inviting 282 physicians from 55 primary healthcare centers and 334 internal medicine physicians from seven governmental hospitals to participate. Results: With a response rate of 87.8% (541/616), 74% (95% CI: 70.2-77.7) of respondents were somewhat or very familiar with published data on PPI AEs. Among the familiar, 69.5% (CI: 65.2-73.5) had somewhat or very much changed their PPI prescribing patterns. General concerns about AEs when prescribing PPIs were reported by 62% (CI: 56.7-65.1). Respondents displayed awareness of a median (IQR) of 15 (9) different AEs associated with long-term PPI use, including osteoporosis or osteopenia (90.2%), hypomagnesemia (81.5%), vitamin B12 deficiency (80.6%), and bone fracture (80.0%). Respondents believed that PPIs elevate the risk for a median (IQR) of 7 (6) different AEs, with osteoporosis or osteopenia (81.8%) being the most common, followed by hypomagnesemia (67.1%), and vitamin B12 deficiency (62.3%). The most common strategies for PPI de-escalation were PPI discontinuation (61%) and using PPI on-demand/as-needed (57.9%). The majority (87.4%) agreed or strongly agreed that PPI overuse is prevalent in Kuwait and 78.2% emphasized the necessity for large-scale education on rational PPI use for medical staff and the public. In the UGIB prevention scenarios, 43.6% recommended appropriately the PPI discontinuation in the minimal-risk scenario, while 56% recommended appropriately the PPI continuation in the high-risk scenario. Associations and comparative analyses revealed predictors influencing physicians' practices and attitudes toward PPI usage. Conclusion: These findings lay the foundation for future research and targeted interventions aimed at optimizing PPI prescribing practices and ensuring patient safety.