An unusual presentation of Takotsubo Syndrome in a young female of Middle Eastern origin

ANGIOEDEMA AS THE PRESENTING SYMPTOM OF SYSTEMIC LUPUS ERYTHEMATOSUSEmily Petrinec, MD1, Ansaam Daoud, MD1,2, Omer Pamuk, MD2University Hospitals Cleveland Medical Center1Department of Medicine, 2Department of RheumatologyContact information:Emily Petrinec: Emily.Petrinec2@uhhospitals.orgAnsaam Daoud: Ansaam.Daoud@uhhospitals.orgOmer Pamuk: Omer.Pamuk@uhhospitals.orgCorresponding Author: Emily PetrinecContact: Emily.Petrinec2@uhhospitals.orgMailing: Department of Medicine, University Hospitals Cleveland Medical Center 11100 Euclid Ave Cleveland, OH 44106Funding/Disclosure:This research received no specific grant or monetary funds from any agency. There are no conflicts of interest for any authors to disclose.Patient Consent:I confirm that the patient(s) detailed in this submission: ANGIOEDEMA AS THE PRESENTING SYMPTOM OF SYSTEMIC LUPUS ERYTHEMATOSUS, CCR3-2024-08-2570 has reviewed and agreed to all conditions of the patient consent form provided by Clinical Case Reports. If the consent form was provided by a different institution, I confirm that consent form meets all specifications as outlined by COPE guidelines. I confirm that I have received the signed consent form from the patient/family member and will be able to produce that signed consent form if requested by the journal.

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Title: BJOG -24-0687.R1 Postpartum haemorrhage care in Ghana and Uganda: grounds for hope and concern.

Rotary Friction Welding (RFW) is essential in manufacturing automotive and marine components, yet the low-cycle fatigue life of dissimilar carbon steel joints (C35 and C45) remains underexplored. This study investigates the influence of RFW parameters on fatigue life through experimental and modeling approaches. Axial low-cycle fatigue tests on base metals and RFW specimens at varying friction pressures show a direct correlation between friction pressure and fatigue strength coefficient. The fatigue life was modeled using the Coffin-Manson equation and refined with an Adaptive Neuro-Fuzzy Inference System (ANFIS) for enhanced prediction accuracy. Results demonstrated that higher friction pressure improves fatigue life and weld strength. This research provides insights into optimizing RFW parameters for better fatigue performance of carbon steel joints. The integration of empirical, experimental and ANFIS-based modeling offers practical guidelines for selecting welding conditions, improving durability and reducing fatigue testing costs in industrial applications.

In this paper, the damage mechanisms and residual strength prediction models of unidirectional glass-fiber reinforced polymers are investigated by acoustic emission(AE) technique. The material exhibits three damage modes: matrix cracking, fiber fracture, and interface damage. A novel AE descriptor, amplitude/centroid frequency (ACF), is introduced to differentiate interface damage from other damage modes. Moreover, three signal types exhibit a strong clustering effect when correlated with ACF and average frequency. Microscopic damage mechanisms of the samples are observed using scanning electron microscopy and correlated with AE signals. The AE signals are analyzed using machine learning, and the clustering analysis results are used as a training set to obtain classification models using support vector machine (SVM) and K-nearest neighbor (KNN) methods. Leveraging the traditional mechanical regression analysis prediction model, the study achieves prediction of the material’s residual strength post-fatigue through improvement in AE cumulative counting. Additionally, optimization of prediction results can be achieved by a certain kind of signal after clustering. The combination of supervised learning and residual strength prediction models can realize the real-time classification of AE signals and apply them to the prediction of residual strength, which has a significant application value in real-time monitoring.

Posttraumatic stress disorder (PTSD) may develop following trauma exposure; however, not all trauma-exposed individuals develop PTSD, suggesting the presence of susceptibility and resilience factors. The gut microbiome and host genome, which are interconnected, have been implicated in the aetiology of PTSD. However, their interaction has yet to be investigated in a South African population. Using genome-wide genotype data and 16S rRNA gene V4 sequencing data from 53 trauma-exposed controls and 74 PTSD cases, we observed no significant association between the host genome and summed abundance of Mitsuokella, Odoribacter, Catenibacterium, and Olsenella, previously reported as associated with PTSD status in this cohort. However, PROM2 rs2278067 was found to interact with PTSD status to influence the summed abundance of these genera ( p < 0.014). Polygenic risk scores generated using genome-wide association study summary statistics from the PGC-PTSD Overall Freeze 2 were not predictive of gut microbial composition in this cohort. These preliminary results suggest a potential role for the interaction between genetic variation and gut microbial composition in the context of PTSD, underscoring the need for further investigation.

Ransomware has become a significant cybersecurity threat, targeting users and organizations through the encryption of critical files and demanding ransom payments for their recovery. Traditional detection methods, relying heavily on static signatures, often fail to identify novel ransomware variants, necessitating more adaptive and behavior-based approaches. In this work, a hybrid detection system combining Isolation Forest for anomaly detection and XGBoost for classification is proposed, enabling real-time monitoring of file system activities to detect ransomware with high precision. This method leverages the unique behaviors of ransomware, such as abnormal file modifications and encryption, allowing it to identify threats before significant damage occurs. The results demonstrate the system's ability to detect a wide range of ransomware variants, even those previously unseen, while maintaining low false positive rates, making it suitable for deployment in both enterprise and smaller-scale environments. Additionally, the system's architecture ensures scalability and efficient performance, enabling its integration into diverse operational settings where real-time detection is critical.

Background: There is very little information available about the health status of young stallions from the German Warmblood population that will, once licensed, shape the future of the equestrian sport and horse-breeding. Objectives: To evaluate the prevalence of clinical findings at licensing examinations of candidate stallions and the influences of season of birth, age at licensing, year of licensing, and the evaluator on the distribution of recorded findings. Study design: Retrospective observational study Methods: Clinical records of 1655 candidate stallions presented for licensing in 2018–2020 were reviewed. Data were provided by all German Warmblood horse-breeding associations and their official veterinarians. Storage and processing of the records was performed using the German equine health database. Generalised linear models were used to determine the influences of fixed effects (season of birth, age at licensing, year of licensing, evaluator) on main clinical findings. Significance level was set at p < 0.05. Results: No remarks were documented on the clinical examination protocol in 777 of the 1655 horses (47.0 %). Furthermore, 51.9% of those stallions with remarks had only one finding documented. Main abnormalities recorded were skin lesions, enlargements on the limbs, and testicular findings. The distributions of several clinical findings differed significantly between the evaluators. Main limitations: Homogenous study population and retrospective data Conclusion: The clinical part of the licensing examination of German Warmblood candidate stallions presented in 2018–2020 revealed mostly no or only very few findings. Furthermore, the majority of the clinical findings recorded are considered to be of minor clinical relevance, implying an overall favourable clinical health status of the stallions presented.

Resources, such as nitrogen, are widely hypothesized to underlie the expression and evolution of plant defenses to herbivory. However, resource availability can affect selection on plant defense traits in contrasting ways: resource availability can 1) weaken selection on defense traits by reducing the costs of herbivory, or 2) strengthen selection on defense traits by increasing herbivore pressure. Previous studies have compared herbivore resistance in populations across natural resource gradients to infer how resource availability affects the microevolution of plant defenses. However, because these studies do not manipulate resource availability, they are unable to directly test the effects of resources of plant defense trait evolution. We used a three-decade-long nitrogen fertilization field experiment to test how nitrogen availability affects the evolution of an architectural plant defense trait: stem nodding in Solidago altissima. Stem nodding is a genetic dimorphism that helps plants to evade apex-galling herbivores. By comparing the frequency of defensive nodding versus erect morphs in experimentally fertilized or unfertilized plots, we assessed how nitrogen addition affects the evolution of this defense trait. We found that the defensive nodding morph was 3-4 times more common in plots that evolved under nitrogen fertilization compared to those that evolved in unfertilized control plots. This study provides empirical evidence for resource availability driving plant defense evolution and demonstrates that this evolution can occur on time-scales conducive to study at many long-term nutrient fertilization experiments.

Impact of high indoor CO2 exposure has not been studied in detail in an academic occupational setting, especially in Qatar, albeit the existence of a clear cause and effect between high CO2 concentration and declining global health. In comparison to the outdoor CO2 concentration, the average indoor CO2 concentration in occupational environment (offices and schools), typically ranges from 600 to 1,000 ppm. This indoor concentration can exceed 2,000 ppm with increase in room occupancies and reduction in building ventilation rates, and can result in a multitude of public health issues. In here we studied the variability in CO2 concentration and try to model its change as a function of population density mimicking the global changes in climate and population. Results indicated that in places where population density crosses a threshold value, the indoor CO2 concentration can increase as much as ~9 ppm/min and can have enormous health impact even in short durations of acute exposure.

Sub-low temperatures in spring often cause stress to the apple root system, inhibiting nitrogen uptake due to lower soil temperatures and reducing root function. Despite research on the function of sugar in regulating plant nitrogen metabolism, the mechanism through which sucrose regulates nitrogen uptake in apple roots at sub-low root-zone temperatures remains unknown. In this study, 1% sucrose was applied at sub-low temperatures in the root zone of Malus baccata Borkh, a widely used apple rootstock, to elucidate the physiological, transcriptional, and metabolic mechanisms of plant nitrogen uptake regulation by sugar. The results showed that adding sucrose promoted root development, accelerated carbon metabolism, provided more carbon skeletons and energy for nitrogen assimilation, and increased the activity of enzymes related to nitrogen metabolism, facilitating nitrogen uptake and utilization. This, in turn, increased the photosynthetic capacity of leaves and facilitated plant growth and development. In contrast, the sub-low root-zone temperature treatment significantly inhibited root development, nitrogen uptake, photosynthesis rate, and plant growth and development. The majority of the genes encoding enzymes associated with carbon and nitrogen metabolism (amylase, sucrose synthase, ATP-dependent 6-phosphofructokinase, pyruvate kinase, nitrate transporter, glutamine synthase, and glutamate dehydrogenase) were upregulated upon exposure to sucrose, as confirmed by transcriptomic data. Furthermore, the metabolomic results suggested that sucrose might enhance nitrogen uptake by modulating flavonoid metabolism. Taken together, these results provide new insights into the role of sucrose in modulating root system nitrogen uptake in the root zone at sub-low temperatures.

Objective Our study aimed to develop a simple-to-use nomogram for predicting the occurrence of HELLP and factors that may make HELLP progression within 3 days. Design The unpredictability of HELLP syndrome and the severe adverse outcomes for both mother and child make it especially important for us to seek predictive model. Setting We used electronic data from Women’s Hospital, Zhejiang University School of Medicine, between January 1,2014 and December 31,2023. Population or Sample A total of 808 patients were included in this study, including 607 patients in non-HELLP syndrome group and 201 patients in the HELLP syndrome group. methods Single and multiple-factor logistic regression analyses were applied to screen for independent factor affecting both the occurrence of HELLP syndrome and within-3-day HELLP syndrome by R software. A nomogram of HELLP syndrome and its efficacy were developed by ROC curves. Results We developed a nomogram displayed very high discrimination (C index 0.979, CI: 0.971-0.987). In the multivariate regression analysis, blood urine nitrogen and the ratio of creatinine over blood urea nitrogen were in a good significant in predicting within-3-day HELLP syndrome. The sensitivity was found to be 68% and 65%, specificity to be 74% and 68.6% respectively. Conclusions We established a great nomogram to evaluate the occurrence of HELLP syndrome. And we found blood urine nitrogen and the ratio of creatinine over blood urea nitrogen could be efficient predictors of HELLP syndrome occurring within 3 days.

TITLE Letter to the editor BJOG “Necessity the mother of invention”- wider significance of novel mid-urethral rectus fascial sling.1 Professor PEP Petros DSc DS (UWA) PhD (Uppsala) MB BS MD (Syd) FRCOG (Lond) FRANZCOG CU.31/93 Elizabeth Bay Rd Elizabeth Bay NSW 2011 AUSTRALIAPelvic Floor Surgeon (retired)1Single and corresponding author.1Affiliation None. Retired pelvic surgeonEmail pp@kvinno.comTel+61 411 181 731

Unmanned Aerial Vehicles (UAVs) are expected to fully exploit their maneuvering capabilities to conduct aggressive maneuvers to complete tasks such as racing and aerobatics even in harsh environments. However, most of related works often focus on slow movements only suitable for regular tasks in well-structured environments. This motivates us to propose a highly robust control scheme designed specifically for UAV aggressive maneuvers, encoded by rapid and large changes in either position or attitude. The core of our approach is the data informed incremental dynamics and the quaternion facilitated control scheme. The former facilitates the model-free control that eliminates the requirement to model the complex dynamics at high velocities and accelerations accurately; While the latter avoids potential singularities during large angular changes. In particular, we first utilize one-step-backward data to construct incremental dynamics, a model-free representation of the UAV dynamics. Then, the constructed incremental dynamics serves as the basis for the development of both position-priority and attitude-priority control schemes, wherein the novel quaternion based aggressive maneuver tracking controllers are designed with complete theoretical analysis. The aggressive maneuvers such as roulette, barrel roll, multiple-flip and cobra maneuvers are chosen for tri/quad/hexa/octocopter platforms to evaluate the performance of our proposed position-priority and attitude-priority control schemes, during which the linear velocity up to 20 m/s, the angular changes up to 360 ◦.

Onchocerciasis also known as River Blindness, is a vector-borne disease caused by Onchocerca volvulus and transmitted by infected female blackflies. It affects millions of people globally, with the greatest impact in sub-Saharan Africa. In this study, we develop a deterministic mathematical model that integrates multiple control measures, including Sterile Insect Technique (SIT), mechanical control, chemical control, public health education and ivermectin treatment, to manage the transmission of onchocerciasis. We employ the next-generation matrix method to calculate the blackfly offspring reproduction number N 0 and the basic reproduction number R 0 . Sensitivity analysis, conducted using the normalized forward sensitivity index, highlights the biting rate as the most positive influence on driving onchocerciasis dynamics, while the mortality rate of female blackflies has a significant negative impact on disease containment. To identify the optimal control strategy, we apply optimal control theory, considering five time-dependent controls which are public health education, treatment, mechanical control, SIT and chemical control. Using Pontryagin’s maximum principle, we derive the optimality system for controlling onchocerciasis. By implementing forward-backward Runge-Kutta method in Matlab, we identify the most optimal strategy for controlling, preventing and treating onchocerciasis in both human and blackfly populations. The results suggest that a combined strategy focusing on public health education, treatment and SIT offers the most effective approach for combating onchocerciasis.

This research through a systematic review highlights studies that have delved into analytics for Industry 4.0 with the aim of discussing and reflecting on the manner in which applications of Artificial Intelligence such as Machine Learning and Deep Learning have helped in forecasting and facilitated informed decision-making.

A great deal of effort has been devoted to discovering a particular genetic disorder, but its classification across a broad spectrum of disorder classes and types remains elusive. Early diagnosis of genetic disorders enables timely interventions and improves outcomes. This study implements machine learning models using basic clinical indicators measurable at birth or infancy to enable diagnosis in preliminary life stages. Supervised learning algorithms were implemented on a dataset of 22083 instances with 42 features like family history, newborn metrics, and basic lab tests. Extensive hyperparameter tuning, feature engineering, and selection were undertaken. Two multi-class classifiers were developed: one for predicting disorder classes (mitochondrial, multifactorial, and single-gene) and one for subtypes (9 disorders). Performance was evaluated using accuracy, precision, recall, and the F1-score. The CatBoost classifier achieved the highest accuracy of 77% for predicting genetic disorder classes. For subtypes, SVM attained a maximum accuracy of 80%. The study demonstrates the feasibility of using basic clinical data in machine learning models for early categorization and diagnosis across various genetic disorders. Applying ML with basic clinical indicators can enable timely interventions once validated on larger datasets. It is necessary to conduct further studies to improve model performance on this dataset.

Today, we talk about the topic of Basic Networking & Static Routing!Let’s take a look at the network scenario as an example showing the concept of Networking and Routing!For this example, Our goal is : We need to send some digital files like PDF documents from laptop A to laptop B or in the reverse direction!This is the most common things we always do everyday!It is similar to send a message from the APPS of smartphone A to another smartphone B!Do you know how the technology behind it helps us to make it happen!We are going to demonstrate all the technical steps how to achieve this goal!—————————————————————————In order to transfer data between 2 user terminals, we need to make a connection between them first. There are 2 Scenarios of connection between 2 end points!

A corner stone of Physics is the Energy Conservation principle which states that the Energy is always conserved and that the Energy, embedded in the whole Universe, cannot disappear or be created from nothing. This should imply that the Total amount of the Energy, which is embedded in the whole Universe, must be a constant value. However, Humans are not able to devise means or experiments which will provide the exact amount of the Energy embedded in the whole Universe, which implies that Humans are not able to devise means or experiments which will conclude, with complete validity, that the amount of the Energy embedded in the whole Universe, can be indeed represented by a constant value. The above implies that Humans are not able to provide a proof for the Energy Conservation Principle, which means, that the Energy Conservation Principle is presented only as an axiom, even though, it is a corner stone of the nowadays Science of Physics. Thus, in view of the above, this paper tries to examine the extent of the validity that Humans can attribute, to the Energy Conservation Principle. Initially, this paper tries to explore, if the evaluation of the amount of Energy, only in certain specific Energy components, in the Universe, will result in the evaluations of the same Energy amounts, by any Human evaluator, or, if separate Human evaluators might arrive at different results, relating to the Total Energy Content, of these certain several specific Energy components, which they evaluated. Thus, in view of the above, this paper provides significant arguments that two separate Humans, evaluating the Total Energy Content of certain several specific Energy components, in the Universe, might arrive at different results, relating to this Total Energy Content, of these several specific Energy components, which they evaluated.

The link between fatigue and operational readiness is crucial within high stress (i.e., High Pressure/High Demand) professions, particularly in the field of paramedicine. Paramedics often work demanding rotational shifts that disrupt sleep-wake cycles, increasing psychophysiological fatigue and contributes to a fatigue debt accumulation, negatively impacting the ability to recover. Such fatigue, coupled with the high cognitive load inherent in some of their duties, significantly compromises operational readiness. Paramedics must rapidly process, prioritize, and interpret diverse stimuli, increasing cognitive demands, especially in high stress situations. These stimuli include rapidly changing occupant behaviours (patients, bystanders) and environmental conditions (hazardous locations, weather risks), as well as time pressures, all requiring simultaneous processing within finite cognitive resources. Additionally, frequent manual manoeuvres in confined spaces, such as homes and vehicles, can further challenge paramedics operational readiness. Effective and practical methods of monitoring fatigue is vital within paramedicine; however, traditional long-term subjective fatigue monitoring may create responder bias and lacks objective measures. The emergence of non-invasive wearable technology, measured in real-time such as heart rate variability (HRV), reflecting physiological demand and recovery; and technological advancements of eye-tracking devices, allowing assessment of cognitive demand via pupillary responses, provides precise analysis of autonomic nervous system dominance within paramedicine allowing for objective psychophysiological insight. The aim of this review is to (1) identify effective strategies for monitoring operational load among paramedics; and (2) present a conceptual model framework utilising novel integration of psychophysiological biometrics through wearable technology to assess and monitor physical and cognitive load in high-pressure occupations.

Next-generation sequencing (NGS) has the potential to transform mosquito-borne disease surveillance but remains under-utilized. This study introduces a comprehensive multi-loci metabarcoding-based MX (molecular xenomonitoring) approach to mosquito and arbovirus surveillance, enabling parallel identification of mosquito vectors, circulating arboviruses, and vertebrate hosts from bulk mosquito collections. The feasibility of this approach was demonstrated through its application to a large set (n=134) of bulk field collections. This set was complemented by a number (n=28) of single-species mosquito pools that had previously been screened for viruses using quantitative reverse transcription PCR (RT-qPCR) and metatranscriptomics. Universal alphavirus and flavivirus primer sets were used to screen for arboviruses in the resulting metabarcoding library. Viral amplicons were then indexed and combined with mosquito-specific (ITS2), universal invertebrate (COI), and vertebrate (Cyt b) barcode amplicons prior to sequencing. This approach confirmed the presence of all previously identified mosquito species, as well as those commonly misidentified morphologically, and enabled a degree of quantification regarding their relative physical abundance in each collection. Additionally, the developed approach identified a diverse vertebrate host community (18 species), demonstrating its potential for defining host preferences and, in tandem with the viral screens and associated vector data, understanding disease transmission pathways. Importantly, metabarcoding detected a diversity of regionally prevalent arboviruses and insect-specific viruses, with all three viral diagnostics demonstrating a similar sensitivity and specificity in detecting Ross River virus and Barmah Forest virus, Australia’s commonest arboviruses. In summary, multi-loci metabarcoding is an affordable and efficient MX tool that enables complete mosquito-borne disease surveillance.

Environmental RNA (eRNA) is emerging as a non-invasive tool for assessing the health of macro-organisms, but key information on its origin and particle sizes remains unclear. In this study, we performed comprehensive RNA-sequencing of eRNA (> 13 Gb/sample) collected from tank water containing Japanese medaka (Oryzias latipes), using sequential filtration through filters with pore sizes of 10, 3, and 0.4 μm. Fish skin RNA was also sequenced to reveal the origin of eRNA. Our results showed that the 3−10 μm fraction contained the lowest relative abundance of microbial RNA, the highest amount of medaka eRNA, and the largest number of detected medaka genes (5398 genes), while the 0.4−3 μm fraction had the fewest (972 genes). Only a small number of genes (42 genes) were unique to the 0.4−3 μm fraction. These findings suggest that a 3 μm filter is optimal for eRNA analysis, as it allows for larger filtration volumes while maintaining the relative abundance of macro-organism eRNA. Furthermore, 81% of the genes detected in eRNA overlapped with skin RNA, indicating skin is a major source of fish eRNA.

Faecal metabarcoding is widely used for mammalian diet analysis. However, most extraction protocols are designed to target high molecular weight genomic DNA, making short sequences of digested DNA challenging to extract. Here, we evaluate prey DNA metrics in baleen whale scat from a phosphate buffer DNA extraction method along with two commercial extraction kits (the QIAamp Fast DNA Stool Mini Kit and the PowerSoil kit) with the following variations: 1) different durations of incubation in a phosphate buffer (1 hour and 24 hours), 2) processing of both pellet and supernatant from phosphate buffer incubation, and 3) two different concentrations of DNA binding buffer to examine prey DNA. We found that the choice of extraction protocol influenced richness, diversity and composition of eukaryotes (18S rDNA) and crustaceans (Crust16S mtDNA) detected in SRW faecal samples. The PowerSoil protocol performed well for both markers, delivering the highest target richness for 18S rDNA and highest diversity for Crust16S mtDNA, while the pellet of the phosphate buffer yielded the highest richness for Crust16S mtDNA. The phosphate buffer supernatant protocols produced the lowest results for richness and diversity. Taxonomic composition in the supernatant alone was influenced by the duration of incubation and the concentration of binding buffer and was also distinct from the corresponding pellet. Our results reinforce the importance of having clear targets prior to selecting a method for faecal metabarcoding, as the specific aims (e.g. identifying richness versus diversity) will inform the choice of extraction protocol.