In the fast-evolving telecommunications landscape, efficiency, innovation, and customer satisfaction are key to maintaining a competitive edge. ATGHANA, like its global competitors, faces challenges in optimizing processes, reducing waste, and delivering consistent value to customers. This article explores how Lean management principles can provide ATGHANA with the strategic advantage it needs to outperform its competitors by boosting operational efficiency, minimizing costs, and enhancing service delivery.

In the context of learning and inference over non-Gaussian additive noise processes encountered in modern circuits and systems, several non-Bussgang learning criteria have emerged, such as, the maximum correntropy, minimum error entropy, and the maximum Versoria criterion. However, these existing learning criteria are known to depend on hyperparameters, such as, the shape and the spread parameters. Besides, some of these learning methods are known to depend on suitable informationpotential (IP) choices for general non-Gaussian noisestatistics. This work proposes an online hyperparameterfree criterion learning algorithm that comprehensively alleviates dependence on hyperparameter choices and learns the IP by self-adapting to underlying noise distributions. For the proposed hyperparameter-free criterion learning, analytical results are derived, and case-studies are presented for its validation.

Background Anabolic-androgenic steroids (AAS), synthetic testosterone derivatives, are widely used to enhance athletic performance and muscle mass. However, misuse of AAS is associated with severe cardiovascular complications, including AAS-induced cardiomyopathy. This study presents a case of AAS-induced cardiomyopathy and systematically reviews the existing literature on the condition. Methods A systematic search was conducted across PubMed, Web of Science, Cochrane, and Google Scholar using relevant terms related to AAS and cardiomyopathy. Studies were reviewed to assess clinical presentations, patient demographics, AAS regimens, diagnostic methods, and treatment strategies. The JBI critical appraisal tool was used to evaluate risk of bias. Results The review included 32 cases of AAS-induced cardiomyopathy, predominantly in males (97%), with a mean age of 38.3 years. Most patients exhibited left ventricular dilation, reduced ejection fraction, and mitral regurgitation. Most cases showed improvement in heart function after discontinuation of AAS and heart failure treatment. Conclusion AAS misuse poses significant cardiovascular risks, particularly cardiomyopathy. While some patients recover after cessation, others may require lifelong management. Greater awareness and research are needed to better understand and manage AAS-induced cardiomyopathy.

73-year-old female who developed new-onset atrial fibrillation (AF) with rapid ventricular response (RVR) further complicated by an unresolving left atrial appendage (LAA) thrombus and tachycardia-induced cardiomyopathy leading to Heart Failure with reduced Ejection Fraction (HFrEF). This report discusses the management strategies employed and the patient’s clinical progression over 11 months. We highlight the role, limitations, and possible alternatives of Direct oral anticoagulants (DOACs) in patients with LAA thrombus and the absence of clear consensus on what constitutes treatment failure with DOACs in such patients.

Many languages lack the vast datasets needed to develop high-performing language models, resulting in significant disparities in performance across various linguistic tasks. The novel recursive instruction tuning approach proposed in this research addresses this challenge through an iterative feedback mechanism that enhances task-specific performance for lowresource languages. By applying recursive instructions to Mistral, an open-source language model, the study demonstrates substantial improvements in translation accuracy, syntactic parsing, and other complex linguistic tasks where traditional methods often falter. The recursive framework's ability to iteratively refine instructions based on model output is shown to be highly effective, enabling more robust learning even in data-constrained environments. Through rigorous experimentation, the findings reveal that this technique leads to more adaptable and fluent models, particularly in handling the diverse grammatical and syntactic constructs found in low-resource languages. The research demonstrates the practical benefits of recursive instruction tuning, highlighting its scalability and efficacy across a variety of linguistic tasks and language groups.

En los últimos años la densitometría ósea se ha convertido en una técnica diagnóstica esencial para la valoración indirecta de la resistencia de los huesos y el análisis del riesgo de fractura individual. Desde las fases más precoces de su desarrollo, esta fascinante técnica ha combinado aspectos relacionados con la física, el análisis cuantitativo, la estadística y la imagen.

Los quirófanos se clasifican en función de varios factores, incluyendo el tipo de procedimientos que se llevan a cabo, la complejidad de las intervenciones quirúrgicas realizadas, y los requisitos de bioseguridad necesarios. Según su función, los quirófanos se clasifican de la siguiente manera: Quirófano general: Se utiliza para llevar a cabo una amplia gama de procedimientos quirúrgicos. Quirófano especializado: Está dedicado a un tipo específico de cirugía, como cardiovascular, ortopédica, urológica, entre otros. Quirófano híbrido: Integra características de un quirófano tradicional con tecnología de imagen avanzada, como resonancia magnética o tomografía computarizada, permitiendo la realización de procedimientos mínimamente invasivos y complejos.

Carro de Anestesia Generalidades Descripción general. La anestesia es una condición intrínsecamente peligrosa: la depresión del sistema nervioso producida por los anestésicos puede acompañarse de alteraciones importantes de las

Una de las principales preocupaciones durante el embarazo es la salud y el bienestar del feto, por lo que se han creado diversas formas para monitorear el estado y desarrollo fetal desde finales del siglo XIX. Los primeros intentos se enfocaban a tratar de reducir la tasa de mortalidad y monitorear los embarazos de alto riesgo por medio del uso del estetoscopio de Pinard, con el cual se llevaba a cabo el monitoreo intermitente mediante la auscultación de la frecuencia cardiaca fetal (FCF) durante 60 segundos (como mínimo), cada 15 minutos en el periodo de dilatación y cada 5 minutos en el periodo expulsivo.

In science and academia, success is often shaped by both knowledge and networking. Reflecting on nearly two decades in academic research, I recount my experience as a postdoctoral immunologist returning to Australia with limited local connections and support. Upon re-establishing myself in Australia, I initially faced barriers that restricted my visibility and collaborations. A turning point came when personal challenges motivated me to actively network, leading to valuable collaborations and career opportunities. By initiating conversations with academic leaders and peers, I expanded my network and established numerous leadership roles, even as a ‘junior’ postdoc through founding a symposium, engaging with an immunology society, volunteering on various academic and advocacy committees, contributing to public outreach and nationally advocating for gender equity in science. These experiences reinforced that networking is about fostering meaningful relationships and creating opportunities to grow professionally. I provide advice on how to increase your networks by volunteering at work, when attending conferences, through contributing to societies and building social media presence. My journey highlights the importance of being proactive in building networks, which can open doors, amplify one’s voice, and drive career advancement in science and academia.

not-yet-known not-yet-known not-yet-known unknown In this work, the effect of aging variables of a proposed heat treatment and their combined impact on the fatigue life of an Al6061-T6 were evaluated. Al 6061-T6 specimens were prepared according to the ASTM E466 and then heat-treated, followed by fatigue tests in a rotating beam testing machine. The results showed an increase in the fatigue life of Al6061-T6 up to 4.47 times and up to 4.69 regarding the aging temperature and the aging time, respectively. Three empirical models to estimate the fatigue life in function of the aging time, aging temperature, and both aging time and temperature were obtained by fitting the experimental, showing a correlation of R 2 =90%, R 2 =79.2%, and R 2 =80.1%, respectively. The proposed heat treatment also decreased the energy consumed by the process by 67.8% than that consumed by the T6 heat treatment of the raw material as a consequence of reducing the time of the process.

Aluminum alloy fiber reinforcing material has several advantages; however, its bonding interface is weak, limiting the mechanical qualities of the multilayer board. We may evaluate this strategy against acid washing by designing different interface surface textures, such as tooth shapes and contact regions. Research is conducted on the mechanics of the interface between CARALL layer plates using short-beam strength trial and limited element analysis (FEA). Unique texture attempts under compressed loads are the emphasis. Results show that teeth experiments change the cutting stress and positive stress distribution near the interface and in the collaboration of the two brackets, shifting the mode of destruction from interfaces in teethless experiments to internal destruction in teethed experiments. Up to 110% more bearing power results from this adjustment. As the number of teeth rises, their exposure to deeper buckle scratches increases, increasing tooth load under the same shape.

Aim: Approximately 10% of all COVID-19 cases experience persistent symptoms after the acute infection phase, a condition known as long COVID or post-acute sequelae of COVID-19. Approved prevention and treatment options for long COVID are currently lacking. Given the heterogeneous nature of long COVID, a personalized medicine approach is essential for effective disease management. This study aimed to describe trends in pharmacotherapy from pre-COVID to post-COVID phases to gain insights into COVID-19 treatment strategies and assess whether pre-COVID pharmacotherapy can predict long COVID symptoms as a health status indicator. Methods: In the Precision Medicine for more Oxygen (P4O2) – COVID-19 study, 95 long COVID patients were comprehensively evaluated through post-COVID outpatient clinics and study visits. The study focused on descriptive analysis of the pharmacotherapy patterns across different phases: pre-COVID-19, acute COVID, and post-COVID. Furthermore, associations between pre-COVID medication and long COVID outcomes were analyzed with regression analyses. Results: We observed peaks in the use of certain medications during the acute infection phase, including corticosteroids and antithrombotic agents, with a decrease in the use of renin-angiotensin inhibitors. Consistent high use of alimentary tract medications was noted across all phases. Notably, pre-COVID respiratory medications were associated with fatigue symptoms, while antiinfectives and cardiovascular drugs were linked to fewer persisting long COVID symptom categories. Conclusion: Our findings provide longitudinal descriptive pharmacotherapy insights and suggest that medication history can be a valuable health status indicator in characterizing patients for personalized disease management strategies, addressing the heterogeneous nature of long COVID.

Background and purpose. Traumatic brain injury (TBI) is an acute brain lesion considered as one of the leading causes of mortality and disability worldwide. After TBI, innate immunity is rapidly activated in response to damage-associated molecular patterns, such as ATP release, recognized by P2X7 purinergic receptors (P2X7R). The P2X7R-NLRP3 inflammasome axis has been identified as one of the main actors in neuroinflammation. Therefore, this study aimed to validate P2X7R as therapeutic target in TBI. Experimental approach. P2X7R was validated through genetic and pharmacological approaches. Six non-nucleotide purine derivatives were evaluated as P2X7R antagonists. Compounds that prevented LPS+ATP-induced IL-1β release from primary glial cultures were investigated in the closed-head injury TBI model in vivo. Finally, we evaluated sP2X7R plasmatic levels in a cohort of TBI patients. Key results. p2x7 -/- mice showed an exaggerated inflammatory response 24 h post-TBI compared to control mice. However, animals treated with the selective P2X7R antagonist JNJ-47965567 (30 mg/kg i.p.) 30 min post-TBI showed improved neurological and inflammatory parameters. The purine derivative ITH15004 was the most potent compound reducing IL-1β production in vitro. When administered in vivo 30 min post-TBI, ITH15004 (1 mg/kg i.p.) improved both neurobehavioral and inflammatory markers at 24 h. In TBI patients, enhanced levels of circulating sP2X7R correlated with the lesion severity 72 h post-TBI and with unfavourable outcomes 24 h post-TBI. Conclusion and implications. These results highlight the importance of P2X7R in the acute phase of TBI and present ITH15004 as a new pharmacological tool to counteract P2X7R-dependent neuroinflammation in vivo.

Ocean surface waves have been demonstrated to be an important component of coupled Earth System Models (ESMs), influencing atmosphere-ocean momentum transfer, ice floe breakage, CFC, carbon and energy uptake, and mixed-layer depth. Modest errors in sea state properties do not strongly affect the impacts of these parameterizations. The minimal data and accuracy needed contrast sharply with the computational costs of spectral wave models in next-generation ESMs. We establish an alternative, cost-efficient wave modeling framework for air-sea and ice-ocean interactions that enables the routine use of sea state-dependent air-sea coupling in ESMs. In contrast to spectral models, the Particle-in-Cell for Efficient Swell (PiCLES) wave model is constructed for coupled atmosphere-ocean-sea ice modeling. Combining Lagrangian wave growth solutions with the Particle-In-Cell method leads to a model that periodically projects onto any convenient grid and scales in an embarrassingly parallel manner. The set of equations solves for the growth and propagation of a parametric wave spectrum’s peak wavenumber and total wave energy, which reduces the state vector size by a factor of 50-200 compared to spectral models. We estimate PiCLES’s computational costs about 1-4 orders of magnitude faster than established wave models with sufficient accuracy for ESMs – rivaling that of spectral models in the open ocean. We evaluate PiCLES against WAVEWATCH III in efficiency and accuracy and discuss the advantages of future performance and planned extensions of its capability in ESMs.

The megaflood in the Jing-Jin-Ji region of China at the end of July 2023, driven by two typhoons and orographic precipitation, was a major disaster. In this study we show that the extreme rainfall event is well reproduced using the 3.25 km and 800 m Regionally Refined Mesh (RRM) configuration of the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). A projected 5.8\%/degC increase in Jing-Jin-Ji precipitation under 2.16 degC warming by 2050 for this event is related to markedly increases in condensation rate and vertical velocity. Free-running simulations further show that the response of the mesoscale circulation to warming results in more pronounced local precipitation changes and shifts in rainfall patterns. The value of SCREAM for assessing the impact of climate change on extreme events and the importance of high-resolution climate modeling are emphasized.

Mediterranean inland saline lakes may play an important role in the carbon cycle due to the metabolic capacities of their prokaryotic communities. However, these lakes are not homogeneous and have different environmental characteristics. In this work, the structure and function of the prokaryotic communities inhabiting water and sediments of 15 Mediterranean inland saline shallow lakes have been studied. These lakes are grouped in categories according to their salinity, conservation statuses and alterations, which determine the structuration of the prokaryotic communities and their carbon-related metabolisms. Each salinity category and conservation status showed characteristic prokaryotic taxa. Relative abundance of methanogenic archaea tended to increase along the salinity gradient, but this did not result into increased methane emissions. The relationship between metabolic rates and the predicted abundance of their marker genes depended on the type of metabolism. Archaea played a relevant role in the organisation of interactions between community members and were markers of good conservation status. Water communities were shaped by the salinity gradient, conservation status and seasonality, while sediment communities were mostly determined by the salinity gradient. This work highlights the importance of combining molecular studies with in situ metabolic measurements to better understand carbon fluxes in inland saline aquatic ecosystems.

IntroductionImmune checkpoint inhibitors (ICIs) are human-derived monoclonal antibodies that enhance the anti-tumor immune response of T cells by inhibiting the the programmed cell death-1(PD-1)/programmed death-ligand-1 (PD-L1) pathway, thus producing anti-tumor immune effects. Tirelizumab is a PD-1 antibody inhibitor that has been shown to be effective in combination with chemotherapy for the treatment of squamous cell lung cancer, however, the subsequent immunotherapy-related adverse events (irAEs) have also been widely observed. It has been reported that among patients receiving anti-PD-1 / PD-L1 therapy, about 70 % had at least one irAE, 10 % had severe irAEs, and 0. 5 % had fatal irAEs [1].Stevens-Johnson syndrome (SJS) /toxic epidermal necrolysis(TEN) is a severe type of pleomorphic erythema and a rare adverse mucocutaneous reaction with a mortality rate of up to 50%[2-3]. The body surface area of the skin (BSA) is the main criterion to distinguish SJS and TEN: BSA<10% is classified as SJS, BSA>30% is classified as TEN, and BSA in between is classified as overlapping type SJS/TEN[4]. The main clinical manifestations of this disease are skin blisters, bullae, epidermal exfoliation, mucosal erosion, etc., and in severe cases, there are systemic poisoning symptoms and different degrees of involvement of internal organs[5]. Because of the difficulty in conducting randomized controlled trials in patients with such critical diseases, the standardized treatment of SJS/TEN is a major clinical challenge. The mainstream treatment measures include immediate discontinuation of suspected allergenic drugs, wound care and drug therapy. Although systemic application of glucocorticoids is currently the most common treatment method, some studies have shown that the use of high-dose glucocorticoids increases the risk of complications[6]. Other treatments such as intravenous immunoglobulin (IVIG), immunosuppressants, plasma exchange, etc., although clinically found to improve the condition to a certain extent, but there is no definite study to prove that it can effectively reduce the mortality of the disease [7].Therefore, there is an urgent need for new and effective treatments to improve the prognosis of the disease. In this report, we described the case of a patient with lung squamous cell carcinoma in whom multiple immune-related adverse events were induced by Tirelizumab.

Peripherin is a class III intermediate filament protein that has recently gained attention as a potential biomarker for axonal damage in the peripheral nervous system. This review examines peripherin gene expression, protein structure, and its functions in both healthy and diseased states. Peripherin is predominantly expressed in the peripheral nervous system, especially in motor and sensory neurons, and plays a critical role in neurite growth, stability, and axonal transport during myelination. Its expression is regulated by various cytokines and undergoes several post-transcriptional modifications. Peripherin interacts with multiple proteins, including neurofilaments and kinases, influencing cytoskeletal dynamics and neuronal functions. The review also explores peripherin involvement in several neurological disorders, such as Amyotrophic Lateral Sclerosis, where its abnormal expression and aggregation contribute to disease pathology. Additionally, peripherin has been linked to polyneuropathies, traumatic axonal injury, and diabetic neuropathy, suggesting its broader relevance as a biomarker in these conditions. The potential of peripherin as a biomarker is further supported by recent studies using ultrasensitive detection methods, which have identified elevated peripherin levels in the serum of patients with neurological diseases. Despite the promising findings, the application of peripherin as a biomarker in clinical settings remains limited, primarily due to challenges in its detection and the need for further validation in diverse patient populations. Future research directions include the development of more sensitive assays and the exploration of peripherin's role in non-neuronal tissues, which may expand its diagnostic and therapeutic potential.

Objective Epilepsy is a brain condition that causes recurring seizures affecting millions of people worldwide. Accumulating evidences show that hypertension is one causative factor of epilepsy. In present study, we try to reveal the causal relationship between hypertension & epilepsy and the potential mediating role of diabetic retinopathy in epilepsy pathogenesis by performing Mendelian randomization (MR) analysis. Methods Based on Genome-wide association studies (GWAS) data of hypertension(finn-b-I9_HYPTENS), epilepsy(finn-b-G6_EPLEPSY) and diabetic retinopathy (finn-b-DM_RETINOPATHY_EXMORE), we performed a two-step MR analysis to investigate the association between hypertension and epilepsy, as well as the role of diabetic retinopathy traits as mediators. The primary approach utilized for causal analysis is inverse variance weighting (IVW), with the addition of multiple sensitivity analyses to assess the reliability of MR outcomes. Subsequently, the causal association between hypertension and epilepsy was further confirmed by analyzing another epilepsy GWAS database (ebi-a-GCST90018840). Results IVW analysis showed that hypertension was one etiological factor of epilepsy which increased its incidence (IVW odds ratio (OR) = 1.14, 95% confidence interval (CI) = 1.06 to 1.22, P=0.0003). The proportion of genetically predicted hypertension mediated by diabetic retinopathy was 11.5%. Subsequent validation analysis further confirmed correlation between hypertension and epilepsy onset (IVW OR =1.12, 95% CI = 1.04 to 1.20, P= 0.0027). Conclusion Our results for the first time revealed causal effect between hypertension and epilepsy through MR analysis, of which diabetic retinopathy served as one key mediator. This insight broadens our understanding about etiology of epilepsy, and it provides clues for better intervention of epilepsy.

Vascular complications (VC) are a common issue during Transcatheter Aortic Valve Replacement (TAVR). Although preoperative assessment of the vascular approach using computed tomography angiography (CTA) can reduce the incidence of VC, CTA has its limitations, such as the potential for intraoperative vasospasm and other factors, which may lead to unexpected vascular

Hailey- Hailey Disease:- insights from a clinical casePrashant Bhatta1,Pramod  kumar Kafle2, Ramesh Khadayat1, Utsav Dulal3, Amrit Bhattarai2, Gaurab Khadka2,Sagar Rana Magar11. Patan Academy of Health Sciences, Patan Hospital, Lalitpur2. Madhyabindu District Hospital3. B.P. Koirala Institute of Health Sciences, DharanCorresponding author:- Ramesh KhadayatEmail:- rameshkhadayat123@gmail.com

Reverse Takotsubo and prolonged cardiac arrest after inadvertent epinephrine injection

Machine learning models trained on vast amounts of data often face challenges related to privacy, particularly when exposed to sensitive information that could be unintentionally retrieved through adversarial methods. A novel approach is explored in this work, introducing machine unlearning as an effective mechanism to mitigate privacy leakage by selectively removing the influence of specific sensitive data points from a trained model. Unlike traditional methods that rely on retraining from scratch or incorporating broad noise injection, machine unlearning focuses on targeted weight modifications that do not significantly degrade model utility while enhancing privacy protections. Extensive experiments on the Llama model demonstrated that the application of machine unlearning techniques successfully reduced privacy risks, as evidenced through a significant drop in the retrieval of sensitive data. The findings showed a balanced reduction in privacy leakage while preserving performance on non-sensitive tasks, positioning unlearning as a viable method to address privacy concerns in machine learning systems. Moreover, the work provides critical insights into the trade-offs between privacy and utility, emphasizing the importance of optimizing for both aspects in practical applications where data security and performance must coexist. Through this contribution, the study adds to the evolving understanding of how privacy can be embedded within AI systems while minimizing the adverse impacts on functionality.