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Background and objectives: Ewing’s sarcoma (EWS) is a malignant round-cell tumor arising from the bone and soft tissue. It is a disease of children and young adults. EWS affecting the central nervous system (cranial and spinal column) is relatively rare with an annual incidence of approximately one case per million in the Western population. Due to their rarity, very few studies are available in the literature. We present our experience of managing 21 such cases, highlighting their clinical, and radiological findings, treatment strategy, and surgical outcomes in patients with primary EWS affecting the central nervous system. Materials and methods: We retrospectively collected hospital records of patients with primary EWS affecting the CNS (cranial and spinal column), who had been surgically treated in our Neuroscience Center between 2015 and 2023. Patients’ demographics, presentation, radiological findings, treatment strategy including surgery and biopsy followed by adjuvant therapy, and outcome at discharge, and the latest follow-up were analyzed from our database. Results: There were sixteen male and five female patients with a mean age of 18.22 ± 12.73 years (ranging from 6 months to 59 years). The commonest presentation was headache and vomiting in cranial lesions (5/13 patients, 38.46%), and back pain in spinal lesions (4/8 patients, 50%). The site of lesions was cranial in thirteen patients (61.9%) and spinal column in eight patients (38.1%). The commonest site was the frontal region in the cranial group (6 patients, 46.15%) and the lumbar region in the spinal group (4 patients, 50%). All patients underwent surgical intervention [tumor resection (18) and biopsy (3)]. Tumor resection was achieved in 18 patients (85.71%). The extent of resection was gross-total excision in 9 patients (42.86%), near-total excision in 5 patients (23.8%), and tumor decompression in 4 patients (19%). Four patients underwent spinal instrumentation. Fifteen patients (71.42%) received multiagent chemo-radiotherapy according to institute protocol. Five patients (23.8%) with poor KPS expired within 6 months of surgery and could not receive adjuvant therapy. Two patients (9.52%) improved symptomatically, and nine patients (42.86%) remained asymptomatic at a mean follow-up of 25.1 ± 29 months. One patient (4.76%) after receiving 2 cycles of adjuvant therapy had initial improvement but expired later due to disease progression. Four patients after adjuvant chemo-radiotherapy (19%) expired due to systemic spread. Conclusion: Primary EWS affecting the central nervous system is a rare variety. A detailed radiological assessment can aid in adequate planning for safe maximal resection. Timely tissue diagnosis is essential for initiating early treatment. Radical excision followed by adjuvant therapy offers a favorable outcome. Postoperative adjuvant chemo-radiotherapy aids in optimal disease control and surgical outcome. With the current treatment strategy, good surgical outcomes can be achieved. However, metastasis is not uncommon and should be evaluated regularly. [ABSTRACT FROM AUTHOR]

Background/Objectives: This study develops machine learning (ML) models to predict hypoxemia severity during emergency triage, particularly in Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) scenarios, using physiological data from medical-grade sensors. Methods: Tree-based models (TBMs) such as XGBoost, LightGBM, CatBoost, Random Forests (RFs), Voting Classifier ensembles, and sequential models (LSTM, GRU) were trained on the MIMIC-III and IV datasets. A preprocessing pipeline addressed missing data, class imbalances, and synthetic data flagged with masks. Models were evaluated using a 5-min prediction window with minute-level interpolations for timely interventions. Results: TBMs outperformed sequential models in speed, interpretability, and reliability, making them better suited for real-time decision-making. Feature importance analysis identified six key physiological variables from the enhanced NEWS2+ score and emphasized the value of mask and score features for transparency. Voting Classifier ensembles showed slight metric gains but did not outperform individually optimized models, facing a precision-sensitivity tradeoff and slightly lower F1-scores for key severity levels. Conclusions: TBMs were effective for real-time hypoxemia prediction, while sequential models, though better at temporal handling, were computationally costly. This study highlights ML's potential to improve triage systems and reduce alarm fatigue, with future plans to incorporate multi-hospital datasets for broader applicability. [ABSTRACT FROM AUTHOR]

The rapid growth of the vehicle population is a major factor in heavy air pollution and public health issues. Traffic-related air pollutants (TRAPs) on roads are often much higher than ambient values, leading to high exposure levels in vehicles. This research proposes a hybrid forecasting model for early detection and early warning systems (EWS) of road networks during real-world travels. Data is collected from Kannur, Calicut, Palakkad, and Coimbatore using real-time sensors, including surrounding discussion information, activity information, vehicle speed, and stopping events. The study predicts ambient air quality (AAQ) levels on the road network using the Gaussian Dispersion model (GDM) and measures the risk sensitivity of PM10 and PM2.5 in selected regions. This helps formulate powerful prevention strategies and prevent negative health impacts. The air pollution module for predicting concentration has an innovative hybridization model that combines an improved cuckoo search (CS) and differential evolution (DE) algorithm with a stacked LSTM model to increase forecasting accuracy of six major environmental pollution levels. This model predicts the AAQ level and is effective and robust for warning one day before the pollutant event occurs based on the risk level of an ambient air pollutant from the RN. [ABSTRACT FROM AUTHOR]

Early warning systems (EWSs) for landslides are becoming a pivotal tool to safeguard assets and stakeholders. With this mission, an EWS should be capable of reliably forecasting the failure time when the ground accelerates. There are analytical methods developed to this end that use time-series kinematics: inverse velocity (INV), minimum inverse velocity (MINV), slope gradient (SLO), and velocity over acceleration (VOA). Although an abundant number of studies applied these methods, they have been majorly examined in a back-analysis context where all the measurements are incorporated into the forecasting process. A successful operation of EWSs in raising meaningful alarms calls for an examination in which the forecasting method is evaluated synchronously. This study evaluates the ability of the four mentioned methods to provide reliable forecasts in real time using a comprehensive database including 75 historical failures. For the first time, the methods are evaluated using a quantitative metric called reliability fitness index (RFI) that measures the portion of forecasts meeting an accuracy threshold. For accuracy thresholds of 50, 75 and 90%, INV showed the highest RFI values of 16, 7, and 4% followed by SLO values of 12, 5, and 2%, respectively. Opposing reliability values for SLO and INV suggest EWSs should take advantage of hybrid models that consider both methods. [ABSTRACT FROM AUTHOR]

Few reports have described the treatment of eosinophilic pneumonia (EP) complicated by refractory pneumothorax. A 62‐year‐old man with a medical history of ulcerative colitis who was undergoing maintenance treatment presented with fever, cough, and diffuse bilateral consolidation on chest radiography. Laboratory findings showed peripheral eosinophilia, and he was hospitalized with a diagnosis of drug‐induced EP and started on corticosteroid therapy. During the course, he developed refractory pneumothorax, and it was difficult to control the air leakage. As it was necessary to control the eosinophilic inflammation and air leakage, mepolizumab, a humanized anti‐interleukin‐5 monoclonal antibody, and an endobronchial Watanabe spigot (EWS), were introduced. After EWS insertion, the leakage of the refractory pneumothorax disappeared. The patient continued to have no recurrence of EP or pneumothorax after the removal of the EWS. The combination of mepolizumab and an EWS may be effective in cases of EP complicated by refractory pneumothorax. [ABSTRACT FROM AUTHOR]

Background: Intensive care unit (ICU) functions as a structured environment dedicated to providing intensive medical attention to patients in critical condition, monitoring, and organ support to treat life-threatening organ failure. Sepsis occurs when the immune system reacts severely to infection, leading to damage to the body’s tissues and organs. Data from The Global Burden of Disease Sepsis Report estimates 48.9 million sepsis cases annually, with 11 million cases leading to death. Therefore, the early warning score (EWS) and sequential organ failure assessment (SOFA) score systems have the potential to estimate the follow-up of patients treated in the ICU. Evaluation of prognosis based on SOFA and EWS scores is not yet confirmed for the medical state of individuals with sepsis. Objective: To determine the correlation of SOFA score and EWS by the duration of ICU stays for sepsis patients at Rumah Sakit Umum Imelda Pekerja Indonesia Medan. Methods: This study used an analytical observational approach employing cross-sectional design. The method of gathering data relies on medical records and samples are collected through total sampling. Result: On 64 patients diagnosed with sepsis and treated in the ICU of Rumah Sakit Umum Imelda Pekerja Indonesia Medan are obtained employing the Spearman correlation test revealed a significant correlation between EWS length of time sepsis patients spend in the ICU (p=0.001). However, a lack of notable correlation was found between the SOFA score and length of time sepsis patients spend in the ICU (p=0.719). Conclusion: No correlation exists between the SOFA score and the duration of stay among sepsis patients, whereas a correlation exists between EWS and duration of stay among sepsis patients.

The rapid growth of the vehicle population is a major factor in heavy air pollution and public health issues. Traffic-related air pollutants (TRAPs) on roads are often much higher than ambient values, leading to high exposure levels in vehicles. This research proposes a hybrid forecasting model for early detection and early warning systems (EWS) of road networks during real-world travels. Data is collected from Kannur, Calicut, Palakkad, and Coimbatore using real-time sensors, including surrounding discussion information, activity information, vehicle speed, and stopping events. The study predicts ambient air quality (AAQ) levels on the road network using the Gaussian Dispersion model (GDM) and measures the risk sensitivity of PM10 and PM2.5 in selected regions. This helps formulate powerful prevention strategies and prevent negative health impacts. The air pollution module for predicting concentration has an innovative hybridization model that combines an improved cuckoo search (CS) and differential evolution (DE) algorithm with a stacked LSTM model to increase forecasting accuracy of six major environmental pollution levels. This model predicts the AAQ level and is effective and robust for warning one day before the pollutant event occurs based on the risk level of an ambient air pollutant from the RN.

It is generally accepted that attempts at coup d'état have decreased since the end of the Cold War. But this does not mean that coup attempts will not occur in the future. With the recent two military coups in Thailand and Myanmar, all the continental states in Southeast Asia have entered authoritarian rules. This article explores when coups possibly occurred in the cases of Thailand in 2014 and Myanmar in 2021 that experienced overthrowing the civilian governments and the rise of the military in power. The Early Warning Signals (EWS) recently endorsed to investigation of the likelihood of military coups and qualitative analysis of collected data on factors affecting such incidents were combined to better explain the situations. From this approach, this article found that Group Grievance and Security Apparatus indicators in the Fragile States Index are important factors leading to the occurrence of military coups in the two countries. Also, from the qualitative analysis, a political culture relying on on iconic political leaders in the two countries has been a negative influence that deludes democratization and challenges civilian rule.

Ewing's sarcoma (ES) is a bone and soft tissue tumor that mainly occurs at a young age. The underlying cause of Ewing's sarcoma is the formation of fusion proteins between FET family genes and ETS family genes. Tumors with FET/ETS fusion genes can have defects in the DNA damage response and are sensitive to PARP inhibitors (PARPi). However, several studies have shown that PARPi alone is not sufficient to induce a meaningful antitumor response and that combinations of DNA-damaging agents with PARPi are required to achieve efficacy. Accordingly, preclinical studies have reported dramatic responses to PARPi treatment in combination with DNA-damaging agents such as temozolomide or irinotecan. Similarly, it has been previously reported that by generating reactive oxygen species, high-dose intravenous vitamin C (IVC) can induce DNA damage. This suggests that the combination of IVC with PARPi may increase genotoxic stress and enhance the antitumor response. In addition, unlike chemotherapeutic agents, IVC induces DNA damage selectively in cancer cells, and the side effects are significantly milder than those of chemotherapy. As ETS fusion-positive ES is deficient in faithful DNA repair, partly due to the interaction between ETS fusion products and PARP1, a PARPi plus IVC seems to be a logical and effective combination for the treatment of ETS fusion-positive ES. This paper reports significant responses to IVC (1–1.5 g/kg) in combination with PARPi (olaparib 300 mg BID or talazoparib 1 mg/day) in two patients with metastatic Ewing's sarcoma. The observations highlight an unmet therapeutic need for patients with advanced metastatic ES. The combination of PARPi with a selective DNA-damaging agent was effective in these cases. This case experience suggests that IVC may be incorporated into PARPi-based therapeutic strategies. Further studies are needed to confirm the efficacy of this combination in the treatment of Ewing sarcoma with ETS fusions. Plain language summary: Combining vitamin C with PARP inhibitors for Ewing sarcoma treatment: mechanistic insights and 2 case studies Ewing's sarcoma is a type of bone and soft tissue tumor that commonly affects young people and it is often resistant to conventional therapy. In this study, clinical cancer scientists and oncologists investigated a new approach to treating this cancer by combining high-dose vitamin C with PARP inhibitors. High-dose vitamin C can damage the DNA of cancer cells and PARP inhibitors block the damaged DNA sites so they can't be repaired and eventually this leads to cancer cells dying. The researchers found that when these two treatments were used together, there were significant improvements in two patients with advanced Ewing's sarcoma. Importantly, the combination led to fewer side effects compared to standard chemotherapy, suggesting it might be a more tolerable treatment option. These findings suggest that combining high-dose intravenous vitamin C with PARP inhibitors could be a promising treatment for Ewing's sarcoma. More research is needed to confirm these results, but this approach shows potential for helping patients with advanced forms of this type of cancer. This is the first clinical report demonstrating the benefits of using high-dose vitamin C with PARP inhibitors and the study emphasizes the importance of exploring more treatment options for this aggressive type of cancer and suggests that further investigations into this combined approach could lead to more effective and tolerable treatments for Ewing's sarcoma. [ABSTRACT FROM AUTHOR]

It is generally accepted that attempts at coup d'état have decreased since the end of the Cold War. But this does not mean that coup attempts will not occur in the future. With the recent two military coups in Thailand and Myanmar, all the continental states in Southeast Asia have entered authoritarian rules. This article explores when coups possibly occurred in the cases of Thailand in 2014 and Myanmar in 2021 that experienced overthrowing the civilian governments and the rise of the military in power. The Early Warning Signals (EWS) recently endorsed to investigation of the likelihood of military coups and qualitative analysis of collected data on factors affecting such incidents were combined to better explain the situations. From this approach, this article found that Group Grievance and Security Apparatus indicators in the Fragile States Index are important factors leading to the occurrence of military coups in the two countries. Also, from the qualitative analysis, a political culture relying on on iconic political leaders in the two countries has been a negative influence that deludes democratization and challenges civilian rule. [ABSTRACT FROM AUTHOR]

Background & objectives: Early warning systems (EWS) involve serial observations (track) with criteria (trigger) to timely identify patients at risk of complications. Carle designed a statistically based clinically modified obstetric early warning score (Carle's OEWS). This study evaluated Carle's OEWS and its individual components for predicting admission to the obstetric critical care unit (OCCU). Maternal near-miss and maternal mortality were the secondary outcomes. Methods: A prospective observational study was conducted among 1250 pregnant women with a period of gestation ≥28 week admitted in the labour wards of a tertiary centre over 18 months. The physiological parameters of OEWS were recorded and aggregate score was calculated at admission and at regular intervals thereafter, till discharge or OCCU admission. Results: The area under receiver operating characteristic (ROC) curve of OEWS was 0.975 for predicting OCCU admission, 0.971 for near-miss, and 0.996 for predicting maternal mortality and was significant for all outcomes. All individual parameters, except diastolic blood pressure, had a significant relative risk for predicting OCCU requirement. Interpretation & conclusions: Carle's OEWS is a useful screening tool for predicting obstetric OCCU admission and can be routinely used in labour wards to ensure timely intervention. [ABSTRACT FROM AUTHOR]

The impact of disasters on the population and environment is an important research area. Multiple criteria need to be analyzed while making policy decisions in order to control the effect of a disaster. Researchers have used many variants of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a Multi-Criteria Decision-Making (MCDM) method for prioritizing the alternatives. Additionally, the detrimental effects of disasters have compelled stakeholders to proactively prepare by strengthening crucial key elements of an Early Warning System (EWS) so that timely alerts can be produced. In this paper, a Disaster Information Provider (DIP) framework is proposed, which employs a TOPSIS variant to bolster weak elements of a people-centric EWS. Governments may utilize delivered rankings to strengthen the weak elements of the EWS in an affected area. Extensive experimentation proves the usability of the DIP framework for strengthening EWS. [ABSTRACT FROM AUTHOR]

Disaster early warning information, if it reaches the communities at-risk with enough lead time, allows individuals to evacuate and subsequently save their lives and livelihoods. However, in many areas of Asia, early warning information does not reach the communities at-risk. Even if it does reach them, the warning information is unclear, distorted, or delayed. This paper aims to understand the underlying factors affecting the dissemination of early warning information, and how it hinders community evacuation in the event of a disaster. It specifically looks into the tools and procedures that are adopted in early warning systems (EWS) as well as the challenges that the communities experienced in receiving the warning information. The paper presents three case studies, including the coastal communities in Bangladesh, the Himalayan communities in Bhutan, and the herder communities in Mongolia to investigate the challenges in EWS. In these communities, the ground-based telecommunication systems, internet and cellular network, have limited coverage. Additionally, the communication infrastructures in these areas are vulnerable to disruptions during extreme disaster events. Using satellites to transmit the warning information to communities at-risk will not only augment the existing ground-based EWS but will also improve evacuation procedures. While this paper builds the case for using the Quasi-Zenith Satellite System (QZSS) to enhance the effectiveness of disseminating early warning information, such effort alone is not enough. Subsequent policy and practical actions must be also undertaken to improve the early warning systems to facilitate effective evacuation.

EWS is a member of the FET family of RNA/DNA binding proteins that regulate crucial phases of nucleic acid metabolism. EWS comprises an N‐terminal low‐complexity domain (LCD) and a C‐terminal RNA‐binding domain (RBD). The RBD is further divided into three RG‐rich regions, which flank an RNA‐recognition motif (RRM) and a zinc finger (ZnF) domain. Recently, EWS was shown to regulate R‐loops in Ewing sarcoma, a pediatric bone and soft‐tissue cancer in which a chromosomal translocation fuses the N‐terminal LCD of EWS to the C‐terminal DNA binding domain of the transcription factor FLI1. Though EWS was shown to directly bind R‐loops, the binding mechanism was not elucidated. In the current study, the RBD of EWS was divided into several constructs, which were subsequently assayed for binding to various nucleic acid structures expected to form at R‐loops, including RNA stem‐loops, DNA G‐quadruplexes, and RNA:DNA hybrids. EWS interacted with all three nucleic acid structures with varying affinities and multiple domains contributed to binding each substrate. The RRM and RG2 region appear to bind nucleic acids promiscuously while the ZnF displayed more selectivity for single‐stranded structures. With these results, the structural underpinnings of EWS recognition and binding of R‐loops and other nucleic acid structures is better understood. [ABSTRACT FROM AUTHOR]

Between June 2018 and April 2019, a sampling campaign was carried out to collect PM2.5, monitoring meteorological parameters and anthropogenic events in the Sartenejas Valley, Venezuela. We develop a logistic model for PM2.5 exceedances (≥ 12.5 µg m−3). Source appointment was done using elemental composition and morphology of PM by scanning electron microscopy coupled with energy dispersive spectroscopy (SEM–EDS). A proposal of an early warning system (EWS) for PM pollution episodes is presented. The logistic model has a holistic success rate of 94%, with forest fires and motor vehicle flows as significant variables. Source appointment analysis by occurrence of events showed that samples with higher concentrations of PM had carbon-rich particles and traces of K associated with biomass burning, as well as aluminosilicates and metallic elements associated with resuspension of soil dust by motor-vehicles. Quantitative source appointment analysis showed that soil dust, garbage burning/marine aerosols and wildfires are three majority sources of PM. An EWS for PM pollution episodes around the Sartenejas Valley is proposed considering the variables and elements mentioned. [ABSTRACT FROM AUTHOR]

Continuous monitoring of vital parameters after bariatric surgery can detect postoperative bleeding or anastomotic leakage. This report describes the development of a continuous remote early warning score (CREWS). This is an EWS-based notification protocol for deterioration detection in bariatric patients. Catharina Hospital, the Netherlands. Several CREWS protocols were developed by combining thresholds indicative of tachycardia and tachypnea using literature insights and expert sessions. These protocols were tested retrospectively using continuously measured vital signs in a cohort of 185 patients who underwent primary bariatric surgery. A wearable remote monitoring device (Healthdot, Philips) was used in hospital and at home up to 14 days after surgery. The outcomes included were demographics, use of beta-blockers, and complications necessitating reintervention. Thresholds of 110 beats per minute (bpm) and 20 breaths per minute (rpm) for heart rate and respiration rate, respectively, detected postoperative bleeding and anastomotic leakage with 75% (3/4 patients) sensitivity. The protocol was silent (no alarms/day) in 69.5% of patients and produced more than 1 alarm/day in 1.6% of patients. The average postoperative heart rate was unaffected by the use of beta-blockers. A description of the steps in the development of an EWS protocol in bariatric patients based on continuous vital sign monitoring is useful. The most sensitive and silent protocol measured heart rate and respiratory rate with thresholds of 110 bpm and 20 rpm and appeared to be feasible for clinical use. There seemed to be no clinically relevant impact of beta-blockers. This CREWS protocol could be a starting point for future studies. [ABSTRACT FROM AUTHOR]

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The purpose of an effective liquidity risk assessment policy is to ensure that any given credit institution can meet its cash flow obligations, even factoring in the uncertainty caused by external factors. As part of the Supervisory Review and Evaluation Process (SREP), the European Central Bank (ECB) has determined this assessment should take into consideration both the institution's ability to meet its short-term obligations and its long-term funding strategy. Due to the fast pace of financial markets and more demanding regulations, there is a structural need for a precise and widely accepted risk assessment methodology. Furthermore, the ability to foresee alternative scenarios by stressing the involved key risk indicators is of the utmost importance. This work investigates whether machine learning techniques can successfully model liquidity risk, thus providing insights for stress-testing scenarios. We have applied the Risk Assessment System (RAS) methodology to classify credit institutions from the Portuguese banking sector according to their liquidity risk, using real supervisory data (from 2014 until March 2021). We then studied the ability to model this risk classification, by comparing a series of well-established machine learning algorithms to a traditional statistical model for benchmarking. The results show that extreme gradient boosting (XGBoost) outperforms other methods for this classification problem. The resulting model can be set up for a production environment and provide scenarios for stress-testing, or as an early warning system (EWS), thus supporting the overall SREP exercise. [ABSTRACT FROM AUTHOR]

Risk analysis and scenario testing are two of the core activities carried out by economists at central banks. With the increasing adoption of machine learning to enhance decision-support systems, and the amount of collected data spiking, institutions provide countless use-cases for the application of these innovative technologies. Consequently, in recent years, the term sup-tech has entered the financial jargon and is here to stay. In this paper, we address risk assessment from a central bank's perspective. The uptrending number of involved banks and institutions raises the necessity of a standardised risk methodology. For that reason, we adopted the Risk Assessment Methodology (RAS), the quantitative pillar from the Supervisory Review and Evaluation Process (SREP). Based on real-world supervisory data from the Portuguese banking sector, from March 2014 until August 2021, we successfully model the supervisory risk assessment process, in its quantitative approach by the RAS. Our findings and the resulting model are proposed as an Early Warning System that can support supervisors in their day-to-day tasks, as well as within the SREP process. [ABSTRACT FROM AUTHOR]

Recent advances in wireless communication technologies are having a great impact on people’s life, especially in the field of healthcare industry that provides a remote monitoring enabling medical staff to follow up the patient and diagnose his disease. LoRa wireless technology is becoming one of the most energetic effective solutions for Wireless Body Area Networks (WBANs) communications. In this work, we propose a LoRa-based low power healthcare WBAN platform called HeaLoRa for an adaptive patient monitoring process. Physicians can remotely monitor patient’s temperature, oxygen saturation level, blood pressure and heart rate to prevent any abnormality. Moreover, data acquisition and transmission are controlled based on a power consumption optimization strategy aiming to reduce redundant data. Based on the Early Warning Score (EWS), the system configuration is dynamically adapted, using a Fuzzy logic controller that makes the decision about the system sleep mode duration and the sent data rate. Furthermore, an analytical model of the energy consumption for acknowledged LoRa transmission is presented in this paper. The graphical abstract of the paper illustrates a medical application of a wireless body area network system where LoRa technology is used to transmit the data to a gateway then the data is transmitted to the doctor using IP based technology. By comparing with a reference system, the simulation results indicate that our system consumes 3 to 10 times less of energy depending on the studied scenario. [ABSTRACT FROM AUTHOR]

Abstract Background Pneumothorax is defined as the presence of air or gas in the pleural cavity. Secondary pneumothorax usually occurs in patients with overt underlying lung disease, most commonly chronic obstructive pulmonary disease (COPD). Patients with poor lung function often suffer from pneumothorax with a persistent air leak. Various strategies have been employed in the treatment of such refractory pneumothorax. Bronchial occlusion with an Endobronchial Watanabe Spigot (EWS) (Novatech, Grasse, France) has been shown to be useful in treating prolonged bronchopleural fistulas. Although the effects of bronchial occlusion with EWS are known, refractory pneumothorax often involves multiple affected bronchi, and in some cases the affected bronchi cannot be easily identified. In addition, secondary pneumothorax associated with advanced lung cancer often prolongs the treatment of pneumothorax, which can significantly reduce patients’ quality of life and prognosis. Case presentation We report a case of refractory pneumothorax where collateral ventilation was successfully treated by bronchial occlusion of the affected bronchi using multiple methods. In August 2019, an 80-year-old Japanese man with asthma and COPD overlap was admitted for exacerbation triggered by respiratory tract infection. During hospitalization, he presented with chest pain due to pneumothorax. Subsequently, a chest drain tube was inserted and pleurodesis was performed; however, the lung could not be sufficiently expanded and an air leak remained. Further investigation revealed a tumor suspicious for lung cancer at the entrance of the left upper lobe bronchus. Due to poor lung function, surgical treatments were deemed high risk. Therefore, we performed bronchial occlusion using the Endobronchial Watanabe Spigot (EWS). Because we could not determine the affected bronchi by computed tomography (CT), we located the affected bronchi by balloon occlusion test and bronchography with iopamidol. After occlusion, the air leak decreased but still persisted. Thus, we performed pleurodesis twice, and the air leak ceased completely. Conclusions Refractory secondary pneumothorax, which affected multiple bronchi and developed into collateral ventilation due to lung cancer, was treated successfully with bronchial occlusion and EWS. In cases where the affected bronchi cannot be determined by the balloon occlusion test, bronchography with iopamidol might be an effective treatment.

The Critical Care Resource Nurse Team (CCRNT) evolved from our traditional Rapid Response Team (RRT). The CCRNT is a unique paradigm created using the conceptual framework of the American Association of Critical Care Nursing Synergy Model for Patient Care. The goal of the CCRNT is to help align nurse competencies with patient needs. This team was seen as a much-needed strong clinical support by nursing leadership as large numbers of inexperienced new graduate registered nurses were hired and senior experienced nurses were leaving the workforce. The CCRNT supports 24/7 RRT, Code Blue, Code Stroke, Emergency Airway Response Team, Early Warning System, Medical Emergency Team, simulation team training, and bedside nurse support and mentoring. Coverage expanded from in patient medical/surgical areas to all areas of the medical center and included hospital-wide initiatives. The focus for the CCRNT changed to a system-wide nursing and patient safety model to improve practice and intervene in near-miss events. This model improved communication between disciplines, provided critical surveillance of at-risk patients, supported patient safety with a significant decrease in patient mortality, and offered a 24/7 expert critical care nurse resource team for staff. [ABSTRACT FROM AUTHOR]

Safety is the most important component of any form of industry. The only factor in the mining business is safety. The mining industry takes many precautions to prevent accidents of any kind, including steel accidents. Rising temperatures are causing methane gas leaks and rising water levels in underground mines. The safety alert switch for protection will be enabled when worker is in danger. A reliable communication system should be implemented to improve safety between workers in underground mines and between fixed anti-personnel mines. There should never be gaps in the communication network. This paper offers the best wireless Early Warning System (EWS). Internet of Things (IoT) can track the working status. Every parameter, including methane gas, high temperatures, fire risk, etc., must always be controlled in underground mining. The safe level of coal mine production is still low. Accidents in coal mines occur regularly, which leads to heavy material losses and human casualties. [ABSTRACT FROM AUTHOR]

International studies show that including Early Warning Score (EWS) Systems in clinical care processes allows caregivers to anticipate patient decompensations and make timely decisions. Currently, it is possible to find different perspectives in the construction of EWS; however, the centile-based approach has not been applied to pediatric patients. This study aims to develop a pediatric EWS using the statistical properties of historical vital sign records. A scoring method with a supervised statistical approach was developed and evaluated. 178.970 vital sign records were obtained from 4,104 patients aged 0 to 18 years, in conjunction with information from Electronic Health Records from a pediatric hospital. Based on a 7-band scoring method and using different vital signs, a model was generated that allows us to predict an unplanned transfer of patients to ICU, 8 hours before it happened. The prediction obtained in the best case showed results in areas under the ROC Curve (AUC) of 0.71. In addition, the calculated cutoff thresholds are sensitive in the lower risk categories (0.877 at low-risk levels) and possessing greater specificity in the higher-risk categories (0.89 in the High-Risk category). The results of this study allow correcting the normal ranges in the vital signs in the Expert-based model, which is currently in operation. Our supervised statistical approach provides an auditable and reproducible method. [ABSTRACT FROM AUTHOR]

Since the Treaty of Lisbon, national parliamentary chambers in the European Union can issue reasoned opinions on legislative proposals by the European Commission. These individual reasoned opinions lead to a review if at least one third of all chambers raise such concerns. Hence, coordination among parliaments is key. Using advances in inferential network analysis, this article infers the underlying diffusion pathways among national parliaments through which chambers are related to each other in their decisions to raise subsidiarity concerns. The emerging diffusion network is characterised by a compartmentalization into communities of European Union budget net contributor and net recipient countries. This descriptive finding has implications for the institutional effectiveness and aspired democratic legitimacy of the Early Warning System. A multivariate statistical network analysis confirms that diffusion occurs among net recipient countries and that weak institutions follow the lead of strong institutions in the Early Warning System. [ABSTRACT FROM AUTHOR]

Loss of resilience in population numbers in response to environmental perturbations may be predicted with statistical metrics called early warning signals (EWS) that are derived from abundance time series. These signals, however, have been shown to have limited success, leading to the development of trait‐based EWS that are based on information collected from phenotypic traits such as body size. Experimental work assessing the efficacy of EWS under varying ecological and environmental factors are rare. In addition, disentangling how such warning signals are affected under varying ecological and environmental factors is key to their application in biological conservation. Here, we experimentally test how different rates of environmental forcing (i.e. warming) and varying ecological factors (i.e. habitat quality and phenotypic diversity) affected population stability and predictive power of early warning signals of population collapse. We analyzed population density and body size time series data from three phenotypically different populations of a protozoan ciliate Askenasia volvox in two levels of habitat quality subjected to three different treatments of warming (i.e. no warming, fast warming and slow warming). We then evaluated how well abundance‐ and trait‐based EWS predicted population collapses under different levels of phenotypic diversity, habitat quality and warming treatments. Our results suggest that habitat quality and warming treatments had more profound effects than phenotypic diversity had on both population stability and on the performance of abundance‐based signals of population collapse. In addition, trait‐based EWS generally performed well, were reliable and more robust in forecasting population collapse than abundance‐based EWS, regardless of variation in environmental and ecological factors. Our study points towards the development of a predictive framework that includes information from phenotypic traits such as body size as an indicator of loss of resilience of ecological systems in response to environmental perturbations. [ABSTRACT FROM AUTHOR]

Risk analysis and scenario testing are two of the core activities carried out by economists at central banks. With the increasing adoption of machine learning to enhance decision-support systems, and the amount of collected data spiking, institutions provide countless use-cases for the application of these innovative technologies. Consequently, in recent years, the term sup-tech has entered the financial jargon and is here to stay. In this paper, we address risk assessment from a central bank’s perspective. The uptrending number of involved banks and institutions raises the necessity of a standardised risk methodology. For that reason, we adopted the Risk Assessment Methodology (RAS), the quantitative pillar from the Supervisory Review and Evaluation Process (SREP). Based on real-world supervisory data from the Portuguese banking sector, from March 2014 until August 2021, we successfully model the supervisory risk assessment process, in its quantitative approach by the RAS. Our findings and the resulting model are proposed as an Early Warning System that can support supervisors in their day-to-day tasks, as well as within the SREP process.

Background: Pneumothorax is defined as the presence of air or gas in the pleural cavity. Secondary pneumothorax usually occurs in patients with overt underlying lung disease, most commonly chronic obstructive pulmonary disease (COPD). Patients with poor lung function often suffer from pneumothorax with a persistent air leak. Various strategies have been employed in the treatment of such refractory pneumothorax. Bronchial occlusion with an Endobronchial Watanabe Spigot (EWS) (Novatech, Grasse, France) has been shown to be useful in treating prolonged bronchopleural fistulas. Although the effects of bronchial occlusion with EWS are known, refractory pneumothorax often involves multiple affected bronchi, and in some cases the affected bronchi cannot be easily identified. In addition, secondary pneumothorax associated with advanced lung cancer often prolongs the treatment of pneumothorax, which can significantly reduce patients' quality of life and prognosis.Case Presentation: We report a case of refractory pneumothorax where collateral ventilation was successfully treated by bronchial occlusion of the affected bronchi using multiple methods. In August 2019, an 80-year-old Japanese man with asthma and COPD overlap was admitted for exacerbation triggered by respiratory tract infection. During hospitalization, he presented with chest pain due to pneumothorax. Subsequently, a chest drain tube was inserted and pleurodesis was performed; however, the lung could not be sufficiently expanded and an air leak remained. Further investigation revealed a tumor suspicious for lung cancer at the entrance of the left upper lobe bronchus. Due to poor lung function, surgical treatments were deemed high risk. Therefore, we performed bronchial occlusion using the Endobronchial Watanabe Spigot (EWS). Because we could not determine the affected bronchi by computed tomography (CT), we located the affected bronchi by balloon occlusion test and bronchography with iopamidol. After occlusion, the air leak decreased but still persisted. Thus, we performed pleurodesis twice, and the air leak ceased completely.Conclusions: Refractory secondary pneumothorax, which affected multiple bronchi and developed into collateral ventilation due to lung cancer, was treated successfully with bronchial occlusion and EWS. In cases where the affected bronchi cannot be determined by the balloon occlusion test, bronchography with iopamidol might be an effective treatment. [ABSTRACT FROM AUTHOR]

Poly(ADP‐ribose) polymerase 1 (PARP1) facilitates DNA damage response (DDR). While the Ewing's sarcoma breakpoint region 1 (EWS) protein fused to FLI1 triggers sarcoma formation, the physiological function of EWS is largely unknown. Here, we investigate the physiological role of EWS in regulating PARP1. We show that EWS is required for PARP1 dissociation from damaged DNA. Abnormal PARP1 accumulation caused by EWS inactivation leads to excessive Poly(ADP‐Ribosy)lation (PARylation) and triggers cell death in both in vitro and in vivo models. Consistent with previous work, the arginine‐glycine‐glycine (RGG) domain of EWS is essential for PAR chain interaction and PARP1 dissociation from damaged DNA. Ews and Parp1 double mutant mice do not show improved survival, but supplementation with nicotinamide mononucleotides extends Ews‐mutant pups' survival, which might be due to compensatory activation of other PARP proteins. Consistently, PARP1 accumulates on chromatin in Ewing's sarcoma cells expressing an EWS fusion protein that cannot interact with PARP1, and tissues derived from Ewing's sarcoma patients show increased PARylation. Taken together, our data reveal that EWS is important for removing PARP1 from damaged chromatin. Synopsis: EWS removes PARP1 from damaged DNA, and abnormal retention of PARP1 due to the loss of EWS triggers cell death. Loss of EWS leads to the accumulation of PARP1 on chromatin and to the synthesis of excessive PAR chains at damaged DNA.The second RGG domain of EWS interacts with PARP1 via its appended PAR chains under DNA damage conditions.Ewing Sarcoma cells, which lack RGG domains of EWS, show hyper‐PARylation and PARP1 accumulation. [ABSTRACT FROM AUTHOR]

Violation of the efficient market hypothesis (EMH) in a specific market may lead to construction of bubbles which is a signal of inefficiencies. Although speculative bubbles soon decay, if they exist for a long time, they will lead to financial crises. Early warning systems (EWSs) are designed to quickly alert the market to crises. Under EMH, the logarithm of price is a martingale process. Thus, it is necessary to use a suitable EWS tool for violation of martingale properties of the logarithm of asset prices. In this paper, using the auto-regressive (ARTA) models, and assuming Markov structure between financial random variables, the conditional means are formulated as a simple regression. Then, using the recursive formula for least square estimates of regression parameters, the hypothesis of variables being martingale is tested. This approach leads to a probability index which serves as an EWS. Then, throughout two real data sets, it is seen that the results of the study are applicable to construct EWS for detecting stock market crashes as well as exchange rate market crises. A discussion section is proposed. Finally, based on these results, conclusions are given. [ABSTRACT FROM AUTHOR]

Objective: Osteosarcoma is one of the most common malignant bone tumors which mainly occurs in children and adolescents. It is characterized by high malignancy and high metastasis rate, resulting in high mortality and disability. Accumulating studies have validated that long noncoding RNAs (lncRNAs) exerted vital roles in multiple cancer progression by regulating the expression of specific genes. This work aimed to explore the potential molecular mechanism of EWS in osteosarcoma. Results: In this study, we discovered that both EWS and Sox2 were highly expressed in osteosarcoma tissue samples. In addition, the expression of EWS was positively associated with Sox2 level. We conducted a series of functional assays and observed that Sox2 overexpression could significantly overturned the enhancement of cell proliferation and the decline of cell apoptosis induced by EWS knockdown in osteosarcoma. Moreover, we found a key upstream regulatory gene of Sox2: miR-199a-5p. Conclusions: Through molecular biology studies and rescue assays, we further demonstrated that EWS promotes tumor growth through the miR-199a-5p/Sox2 signaling axis in osteosarcoma. These findings may provide an important theoretical basis for the clinical diagnosis and treatment of osteosarcoma. [ABSTRACT FROM AUTHOR]

All clinical nurses need to be prepared to recognize deterioration in a patient's clinical status and activate the rapid response team when appropriate. This article explores the clinical nurse's role in recognizing and responding to deterioration in a patient's condition with a focus on hospital-based nurses practicing on a medical-surgical unit. [ABSTRACT FROM AUTHOR]

This study aims to analyze the relationship between the current account and budget deficit (twin deficits hypothesis), measuring the account performance and other macroeconomic indicators in predicting the debt crisis in Indonesia. Furthermore, the data used for hypothesis was obtained from 2004q1-2017q4, followed by the application of the ARDL method, while values based on debt crisis were taken from the year 1981–2017, and indicators performance measurement required the use of Early Warning System (EWS) method, which was conducted through Quadratic Probability Score (QPS), and Global Squared Bias (GSB). The results indicate a long-term positive relationship between the current account and budget deficit (twin deficits), while the short-term studies reveal a negative association termed twin divergence, which occur on instances where a country has high savings rate. Furthermore, it was established that the current account deficit towards predicting the debt crisis in Indonesia was of a low performance, and the leading macroeconomic indicators include short-term debt-foreign exchange reserves, the temporary debt-total external type, M2-foreign exchange reserves, inflation, IMF, and domestic credit-GDP. Therefore, the EWS model possesses 60% predictive abilities and an NTSR of 0.25, where the QPS value obtained was 0.373, and that of GSB was 0.005.