Ultrafast Nucleation Reverses Dissolution of Transition Metal Ions for Robust Aqueous Batteries.

The dissolution of transition metal ions causes the notorious peeling of active substances and attenuates electrochemical capacity. Frustrated by the ceaseless task of pushing a boulder up a mountain, Sisyphus of the Greek myth yearned for a treasure to be unearthed that could bolster his efforts. Inspirationally, by using ferricyanide ions (Fe(CN)63-) in an electrolyte as a driving force and taking advantage of the fast nucleation rate of copper hexacyanoferrate (CuHCF), we successfully reversed the dissolution of Fe and Cu ions that typically occurs during cycling. The capacity retention increased from 5.7% to 99.4% at 0.5 A g-1 after 10,000 cycles, and extreme stability of 99.8% at 1 A g-1 after 40,000 cycles was achieved. Fe(CN)63- enables atom-by-atom substitution during the electrochemical process, enhancing conductivity and reducing volume change. Moreover, we demonstrate that this approach is applicable to various aqueous batteries (i.e., NH4+, Li+, Na+, K+, Mg2+, Ca2+, and Al3+).

Oxygen Vacancies Boosted Hydronium Intercalation: A Paradigm Shift in Aluminum-Based Batteries.

In aqueous aluminum-ion batteries (AAIBs), the insertion/extraction chemistry of Al3+ often leads to poor kinetics, whereas the rapid diffusion kinetics of hydronium ions (H3O+) may offer the solution. However, the presence of considerable Al3+ in the electrolyte hinders the insertion reaction of H3O+. Herein, we report how oxygen-deficient α-MoO3 nanosheets unlock selective H3O+ insertion in a mild aluminum-ion electrolyte. The abundant oxygen defects impede the insertion of Al3+ due to excessively strong adsorption, while allowing H3O+ to be inserted/diffused through the Grotthuss proton conduction mechanism. This research advances our understanding of the mechanism behind selective H3O+ insertion in mild electrolytes.

Why different sugarcane cultivars show different resistant abilities to smut? : Comparisons of endophytic microbial compositions and metabolic functions in stems of sugarcane cultivars with different abilities to resist smut.

To elucidate the mechanisms underlying the resistance to smut of different sugarcane cultivars, endophytic bacterial and fungal compositions, functions and metabolites in the stems of the sugarcane cultivars were analyzed using high-throughput sequencing techniques and nontargeted metabolomics. The results showed that the levels of ethylene, salicylic acid and jasmonic acid in sugarcane varieties that were not sensitive to smut were all higher than those in sensitive sugarcane varieties. Moreover, endophytic fungi, such as Ramichloridium, Alternaria, Sarocladium, Epicoccum, and Exophiala species, could be considered antagonistic to sugarcane smut. Additionally, the highly active arginine and proline metabolism, pentose phosphate pathway, phenylpropanoid biosynthesis, and tyrosine metabolism in sugarcane varieties that were not sensitive to smut indicated that these pathways contribute to resistance to smut. All of the above results suggested that the relatively highly abundant antagonistic microbes and highly active metabolic functions of endophytes in non-smut-sensitive sugarcane cultivars were important for their relatively high resistance to smut.

Responses of sediment nitrogen forms and bacterial communities to different aquatic nitrogen conditions in three submerged macrophyte-type ecological treatment systems.

Ecological treatment system (ETS) has been recognized as a promising technology for mitigating agricultural non-point pollution, whereas it remains to be seen how nitrogen (N) forms and bacterial communities in ETS sediments respond to different aquatic N conditions. Therefore, a four-month microcosm experiment was conducted to investigate the effects of three aquatic N conditions (2 mg/L NH4+-N, 2 mg/L NO3--N and 1 mg/L NH4+-N + 1 mg/L NO3--N) on sediment N forms and bacterial communities in three ETSs vegetated by Potamogeton malaianus, Vallisneria natans and artificial aquatic plant, respectively. Through analysis of four transferable N fractions, the valence states of N in ion-exchange and weak acid extractable fractions were found to be mainly determined by aquatic N conditions, while significant N accumulation was observed only in strong oxidant extractable and strong alkali extractable fractions. Sediment N profiles were primarily influenced by time and plant types, with N condition having secondary effect, while sediment bacterial community structures experienced a significant shift over time and were slightly influenced by plant types. Sediment functional genes related to N fixation, nitrification, assimilable nitrate reduction, dissimilatory nitrite reduction (DNRA) and denitrification were substantially enriched in month 4, and the bacterial co-occurrence network exhibited less complexity but more stability under NO3- condition compared to others. Furthermore, certain sediment N fractions were found to have strong relationships with specific sediment bacteria, such as nitrifiers, denitrifiers and DNRA bacteria. Our findings highlight the significant influence of aquatic N condition in submerged macrophyte-type ETSs on sediment N forms and bacterial communities.

Effect of Deep Versus Moderate Neuromuscular Block on Pain After Laparoscopic Colorectal Surgery: A Randomized Clinical Trial.

BACKGROUND: Anesthesia with deep neuromuscular block for laparoscopic surgery may result in less postoperative pain with lower intra-abdominal pressure. However, results in the existing literature are controversial. OBJECTIVE: The study aimed to evaluate the effect of deep neuromuscular block on postoperative pain at rest and during coughing after laparoscopic colorectal surgery. DESIGN: The design is a parallel-group, randomized clinical trial. SETTINGS: The study was conducted at a tertiary care center. PATIENTS: Patients undergoing laparoscopic resection of colorectal tumors were included. INTERVENTIONS: Patients were randomly assigned to either a deep (posttetanic count 1 to 2) or moderate (train-of-four 1 to 2) neuromuscular group. MAIN OUTCOME MEASURES: The coprimary efficacy outcomes were numeric rating scale scores of the postoperative pain at rest and during coughing after surgery. RESULTS: Pain was lower in the deep neuromuscular block group at rest and during coughing at 1, 6, 24, and 48 hours after surgery (median difference of 2 points and 1 point at 1 h; p < 0.001 at each time point). The deep neuromuscular block group displayed a significantly lower number of bolus attempts by the patient (4 in the deep group vs 9 in the moderate group; p < 0.001) and boluses delivered (4 in the deep group vs 9 in the moderate group; p < 0.001) on postoperative day 1. The number of rescue analgesics was lower in the deep group on postoperative day 2 (p < 0.001). The deep neuromuscular block group showed a lower frequency of postoperative nausea and vomiting (p = 0.02) and lower intraoperative intra-abdominal pressure (p < 0.001). LIMITATIONS: This was a single-center study. CONCLUSIONS: Deep neuromuscular block resulted in better pain relief and lower opioid consumption and use of rescue analgesics after laparoscopic colorectal surgery. Deep neuromuscular block was associated with less postoperative nausea and vomiting and facilitated the use of lower intra-abdominal pressure in laparoscopic surgery. See Video Abstract at http://links.lww.com/DCR/B458. EFECTO DEL BLOQUEO NEUROMUSCULAR PROFUNDO VERSUS MODERADO EN EL DOLOR, DESPUS DE LA CIRUGA COLORRECTAL LAPAROSCPICA UN ENSAYO CLNICO ALEATORIZADO: ANTECEDENTES:La anestesia con bloqueo neuromuscular profunda para cirugía laparoscópica, puede resultar con menor dolor postoperatorio y con menos presión intraabdominal. Sin embargo, los resultados en la literatura existente son controvertidos.OBJETIVO:El objetivo del estudio, fue evaluar el efecto del bloqueo neuromuscular profundo en dolor postoperatorio de reposo y con la tos, después de cirugía colorrectal laparoscópica.DISEÑO:Ensayo clínico aleatorizado de grupos paralelos.AJUSTE:El estudio se realizó en un centro de atención terciaria.PACIENTES:Se incluyeron pacientes sometidos a resección laparoscópica de tumores colorrectales.INTERVENCIONES:Los pacientes fueron aleatorizados a un grupo neuromuscular profundo (recuento posttetánico 1 a 2) o moderado (tren de cuatro 1 a 2).PRINCIPALES MEDIDAS DE RESULTADO:Los resultados coprimarios de eficacia, fueron las puntuaciones numéricas en la escala de calificación del dolor postoperatorio en reposo y durante la tos, después de la cirugía.RESULTADOS:El dolor fue menor en el grupo de bloqueo neuromuscular profundo en reposo y durante la tos, en 1, 6, 24, 48 horas después de la cirugía, (diferencia de mediana de 2 puntos y 1 punto respectivamente en 1 hora; p <0,001 en cada punto de tiempo). El grupo de bloqueo neuromuscular profundo, mostró un número significativamente menor de intentos de bolo por parte del paciente, (4 en el grupo profundo versus 9 del grupo moderado, p <0,001) y de bolos administrados (4 en el grupo profundo versus 9 en el grupo moderado, p <0,001) en el primer día postoperatorio. El número de analgésicos de rescate, fue menor en el grupo profundo en el segundo día postoperatorio (p <0,001). El grupo de bloqueo neuromuscular profundo, mostró una menor frecuencia de náuseas y vómitos postoperatorios (p = 0,02) y una menor presión intraoperatoria e intraabdominal (p <0,001).LIMITACIONES:Este estudio fue un estudio de un solo centro.CONCLUSIONES:El bloqueo neuromuscular profundo, resultó en mayor alivio del dolor y menor consumo de opioides y uso de analgésicos de rescate, después de la cirugía colorrectal laparoscópica. El bloqueo neuromuscular profundo, se asoció con menos náuseas y vómitos posoperatorios y facilitó el uso de una presión intraabdominal más baja, en la cirugía laparoscópica. Consulte Video Resumen en http://links.lww.com/DCR/B458.

Thermal energy recovery from chlorinated drinking water distribution systems: Effect on chlorine and microbial water and biofilm characteristics.

Thermal energy recovery from drinking water has a high potential in the application of sustainable building and industrial cooling. However, drinking water and biofilm microbial qualities should be concerned because the elevated water temperature after cold recovery may influence the microbial activities in water and biofilm phases in drinking water distribution systems (DWDSs). In this study, the effect of cold recovery on microbial qualities was investigated in a chlorinated DWDS. The chlorine decay was slight (1.1%-15.5%) due to a short contact time (~60 s) and was not affected by the cold recovery (p > 0.05). The concentrations of cellular ATP and intact cell numbers in the bulk water were partially inactivated by the residual chlorine, with the removal rates of 10.1%-16.2% and 22.4%-29.4%, respectively. The chlorine inactivation was probably promoted by heat exchangers but was not further enhanced by higher temperatures. The higher water temperature (25 °C) enhanced the growth of biofilm biomass on pipelines. Principle coordination analysis (PCoA) showed that the biofilms on the stainless steel plates of HEs and the plastic pipe inner surfaces had totally different community compositions. Elevated temperatures favored the growth of Pseudomonas spp. and Legionella spp. in the biofilm after cold recovery. The community functional predictions revealed more abundances of five human diseases (e.g. Staphylococcis aureus infection) and beta-lactam resistance pathways in the biofilms at higher temperature. Compared with a previous study with a non-chlorinated DWDS, chlorine dramatically reduced the biofilm biomass growth but raised the relative abundances of the chlorine-resistant genera (i.e. Pseudomonas and Sphingomonas) in bacterial communities.

Algae-induced taste and odour problems at low temperatures and the cold stress response hypothesis.

The existence of taste and odour (T&O) in drinking water is one of the principal causes of consumer complaints and is commonly related to algae growth. Numerous studies have confirmed the existence of algal blooms emerging specifically in low-temperature periods, herein referred to as "cold algae"; these include chrysophytes, cryptophytes, dinoflagellates and diatoms. In addition, the adaption mechanisms of these "cold algae" involve high flexibility in their nutrient intake and to the hydrological characteristics of the waters and their high contents of intracellular polyunsaturated fatty acids (PUFAs). Like algae proliferating in higher temperature waters, cold algae can also produce offensive odours. The potential dominant T&O compounds of low-temperature algae probably include saturated/unsaturated aldehydes and even some terpenoids. Among these, the polyunsaturated aldehydes (PUAs), the derivatives of polyunsaturated fatty acids, are the dominant T&O compounds and are probably synthesized during cell rupture. It was found that, for cold algae, low temperature may have a favourable effect on the generation of algae-induced T&O compounds. Furthermore, to better understand the internal mechanisms of algal T&O production, the stress response theory is introduced, which provides ideas for T&O control in raw water and in water treatment. Finally, implications for T&O management are given based on this review. KEY POINTS: • Like algae proliferating in higher temperature waters, cold algae can produce offensive odours. • Low temperatures may have a favourable effect on the generation of algae-induced T&O compounds. • The stress response theory can help to better understand the internal mechanisms of algal T&O production.

Negative Lymph Node Count Predicts Survival of Resected Non-small Cell Lung Cancer.

PURPOSE: The purpose of this study was to explore the association between the negative lymph node (NLN) count and survival, as well as compare the prognostic value of the positive lymph node (PLN) count, lymph node ratio (the PLN count/total lymph nodes examined, LNR), and NLN count in patients with non-small cell lung cancer (NSCLC). METHODS: We identified patients diagnosed with NSCLC between 2005 and 2011 from the Surveillance, Epidemiology, and End Results database. Outcomes of interest were lung cancer-specific survival (LCSS) and overall survival (OS). Cases were divided into several groups based on the PLN count, NLN count, and LNR. The prognostic significance of the PLN count, NLN count, and LNR models was analyzed with the Kaplan-Meier method and the Cox regression model. RESULTS: 39,959 patients with surgical resection for NSCLC were identified. Univariate analysis demonstrated that a greater count of NLNs was associated with better LCSS (P < 0.001) and OS (P < 0.001). Subgroup analysis showed that the NLN count could predict survival in both node-negative and node-positive patients. Multivariable analysis revealed that the NLN count was an independent prognostic factor for LCSS and OS. CONCLUSION: The NLN count is an independent prognostic factor of OS and LCSS in patients with NSCLC, as well as the PLN count and LNR. The prognostic value of the PLN count, NLN count, and LNR shows no difference.

The Moderating Effect of Resilience on the Relationship between Adverse Childhood Experiences (ACEs) and Quality of Physical and Mental Health among Adult Sexual and Gender Minorities.

Sexual and gender minority (SGM) individuals experience a greater burden of poor mental health compared to heterosexual individuals. One factor that helps to explain this disparity is trauma experienced during childhood. SGM are more likely to report traumatic experiences during childhood contributing to this disparity. Previous research has shown that resilience moderates the relationship between childhood trauma and adults mental health outcomes. As part of the Strengthening Colors of Pride project, data on 463 SGM adults living in San Antonio were collected using surveys. A diverse recruitment strategy was used in conjunction with a community advisory board. The brief resilience scale (BRS) was used to assess intrapersonal level resilience to determine if there was an effect on the relationship between ACEs and quality of mental and physical health. Differences were noted for some items across low, normal, and high levels of resilience. Both ACEs and BRS significantly predicted quality of mental and physical health. We also noted a significant interaction between ACEs and BRS with regard to quality of mental health. Findings suggest there is a relationship between intrapersonal level resilience, ACEs, and quality of mental health.

A novel method: using an adenosine triphosphate (ATP) luminescence-based assay to rapidly assess the biological stability of drinking water.

The rapid and credible evaluations of the microbial stability of a drinking water distribution system (DWDS) are of great significance for ensuring the safety of drinking water and predicting microbial pollution. Conventional biostability assessment methods mainly focus on bacterial regrowth or evaluation of the level of nutrients that support bacterial regrowth. However, such methods are time-consuming and have many limitations. An adenosine triphosphate (ATP) assay can rapidly measure all active microorganisms and is known to be a useful method to assess the microbial activity of drinking water. The measurement of ATP has been used for more than a decade in the field of drinking water research. This article reviews the application of an ATP luminescence-based method to assess the biostability of drinking water and discusses the feasibility of ATP measurement as a parameter for quickly evaluating this criterion. ATP measurement will help researchers and water managers better monitor the biological stability of drinking water from the source to the consumer's tap. This review covers the: (1) principle and application of the ATP measurement in drinking water quality assessment; (2) comparison of the merits and demerits of several methods for evaluating the biostability of drinking water; (3) discussions on using ATP measurement in evaluating biostability; and (4) improvements in the use of ATP measurement in evaluating biostability. At the end of this review, recommendations were given for better application of the ATP measurement as a parameter for monitoring the microbial quality of drinking water.

MiR-125a-5p functions as a tumour suppressor in breast cancer by downregulating BAP1.

MicroRNAs (miRNAs) play an important role in the regulation of human cancers, including breast cancer (BC). In the current study, we examined the expression pattern of the miRNA miR-125a-5p in human BC tissues, tumorigenesis of BC progression. We found that miR-125a-5p was significantly downregulated in human BC tissues. Overexpression of miR-125a-5p in a xenograft mouse model indicated that miR-125a-5p may function as a tumour suppressor during carcinogenesis. To explore the molecular mechanism by which miR-125a-5p contributes to BC progression, we predicted the target genes of miR-125a-5p and identified BC susceptibility gene 1-associated protein 1 (BAP1) as a direct target. Finally, we demonstrated that BAP1 had opposing effects to those of miR-125a-5p on BC cells, suggesting that miR-125a-5p may inhibit cell proliferation and promote cell apoptosis by negatively regulating BAP1. Taken together, our findings provide the first clues regarding the role of miR-125a-5p as a tumour suppressor in BC via the inhibition of BAP1 translation.

LESS: Link Estimation with Sparse Sampling in Intertidal WSNs.

Deploying wireless sensor networks (WSN) in the intertidal area is an effective approach for environmental monitoring. To sustain reliable data delivery in such a dynamic environment, a link quality estimation mechanism is crucial. However, our observations in two real WSN systems deployed in the intertidal areas reveal that link update in routing protocols often suffers from energy and bandwidth waste due to the frequent link quality measurement and updates. In this paper, we carefully investigate the network dynamics using real-world sensor network data and find it feasible to achieve accurate estimation of link quality using sparse sampling. We design and implement a compressive-sensing-based link quality estimation protocol, L E S S , which incorporates both spatial and temporal characteristics of the system to aid the link update in routing protocols. We evaluate L E S S in both real WSN systems and a large-scale simulation, and the results show that L E S S can reduce energy and bandwidth consumption by up to 50 % while still achieving more than 90 % link quality estimation accuracy.

Pido: Predictive Delay Optimization for Intertidal Wireless Sensor Networks.

Intertidal habitats are among the harshest environments on the planet, and have emerged as a model system for exploring the ecological impacts of global climate change. Deploying reliable instrumentation to measure environmental conditions such as temperature is challenging in this environment. The application of wireless sensor networks (WSNs) shows considerable promise as a means of optimizing continuous data collection, but poor link quality and unstable connections between nodes, caused by harsh physical environmental conditions, bring about a delay problem. In this paper, we model and analyze the components of delays in an intertidal wireless sensor network system (IT-WSN). We show that, by properly selecting routing pathways, it is feasible to improve delay. To this end, we propose a Predictive Delay Optimization (Pido) framework, which provides a new metric for routing path selection. Pido incorporates delay introduced by both link quality and node conditions, and designs a classifier to predict future conditions of nodes, i.e., the likely time of aerial exposure at low tide in this case. We evaluate the performance of Pido in both a real IT-WSN system and a large-scale simulation, the result demonstrates that Pido decreases up to 73% of delays on average with limited overhead.

An ignored and potential source of taste and odor (T&O) issues-biofilms in drinking water distribution system (DWDS).

It is important for water utilities to provide esthetically acceptable drinking water to the public, because our consumers always initially judge the quality of the tap water by its color, taste, and odor (T&O). Microorganisms in drinking water contribute largely to T&O production and drinking water distribution systems (DWDS) are known to harbor biofilms and microorganisms in bulk water, even in the presence of a disinfectant. These microbes include T&O-causing bacteria, fungi, and algae, which may lead to unwanted effects on the organoleptic quality of distributed water. Importantly, the understanding of types of these microbes and their T&O compound-producing mechanisms is needed to prevent T&O formation during drinking water distribution. Additionally, new disinfection strategies and operation methods of DWDS are also needed for better control of T&O problems in drinking water. This review covers: (1) the microbial species which can produce T&O compounds in DWDS; (2) typical T&O compounds in DWDS and their formation mechanisms by microorganisms; (3) several common factors in DWDS which can influence the growth and T&O generation of microbes; and (4) several strategies to control biofilm and T&O compound formation in DWDS. At the end of this review, recommendations were given based on the conclusion of this review.

Hypoxic Bone Marrow Stromal Cells Secrete miR-140-5p and miR-28-3p That Target SPRED1 to Confer Drug Resistance in Multiple Myeloma.

Bone marrow stromal cell (BMSC)-derived small extracellular vesicles (sEV) promote drug resistance to bortezomib in multiple myeloma cells. Elucidating the components of BMSC sEV that induce drug resistance in multiple myeloma cells could help identify strategies to overcome resistance. Considering the hypoxic nature of the myeloma microenvironment, we explored the role of hypoxia in regulating BMSC sEV cargo and investigated whether hypoxia-driven sEV miRNAs contribute to the drug resistance in multiple myeloma cells. Hypoxia increased the release of sEVs from BMSCs, and these sEVs more strongly attenuated bortezomib sensitivity in multiple myeloma cells than sEVs from BMSCs under normoxic conditions. RNA sequencing revealed that significantly elevated levels of miR-140-5p and miR-28-3p were enclosed in hypoxic BMSC-derived sEVs. Both miR-140-5p and miR-28-3p conferred bortezomib resistance in multiple myeloma cells by synergistically targeting SPRED1, a member of the Sprouty protein family that regulates MAPK activation. SPRED1 inhibition reduced sensitivity to bortezomib in multiple myeloma cells through activating MAPK-related pathways and significantly promoted multiple myeloma bortezomib resistance and tumor growth in a mouse model. These findings shed light on the role of hypoxia-induced miRNAs shuttled in BMSC-derived sEVs to multiple myeloma cells in inducing drug resistance and identify the miR-140-5p/miR-28-3p/SPRED1/MAPK pathway as a potential targetable axis for treating multiple myeloma. SIGNIFICANCE: Hypoxia induces stromal cells to secrete extracellular vesicles with increased miR-140-5p and miR-28-3p that are transferred to multiple myeloma cells and drive drug resistance by increasing the MAPK signaling.

Endophytic Microorganisms in Tomato Roots, Changes in the Structure and Function of the Community at Different Growing Stages.

This study analyzed flower bud differentiation and fruiting stages to investigate how the structure of the plant endophytic microbial community in the roots of tomatoes changes with plant senescence. Based on high-throughput sequencing technology, the diversity and relative abundance of endophytic microorganisms (bacteria and fungi) in tomato stems at different growth stages were analyzed. At the same time, based on LEfSe analysis, the differences in endophytic microorganisms in tomato stems at different growth stages were studied. Based on PICRUSt2 function prediction and FUNGuild, we predicted the functions of endophytic bacterial and fungal communities in tomato stems at different growth stages to explore potential microbial functional traits. The results demonstrated that not only different unique bacterial genera but also unique fungal genera could be found colonizing tomato roots at different growth stages. In tomato seedlings, flower bud differentiation, and fruiting stages, the functions of colonizing endophytes in tomato roots could primarily contribute to the promotion of plant growth, stress resistance, and improvement in nutrient cycling, respectively. These results also suggest that different functional endophytes colonize tomato roots at different growth stages.

How Rhizosphere Microbial Assemblage Is Influenced by Dragon Fruits with White and Red Flesh.

The synthesis of betalain using microorganisms is an innovative developmental technology, and the excavation of microorganisms closely related to betalain can provide certain theoretical and technical support to this technology. In this study, the characteristics of soil microbial community structures and their functions in the rhizospheres of white-fleshed dragon fruit (Hylocereus undatus) and red-fleshed dragon fruit (Hylocereus polyrhizus) were analyzed. The results show that the soil bacterial and fungal compositions in the rhizospheres were shaped differently between H. undatus and H. polyrhizus. Bacterial genera such as Kribbella and TM7a were the unique dominant soil bacterial genera in the rhizospheres of H. undatus, whereas Bradyrhizobium was the unique dominant soil bacterial genus in the rhizospheres of H. polyrhizus. Additionally, Myrothecium was the unique dominant soil fungal genus in the rhizospheres of H. polyrhizus, whereas Apiotrichum and Arachniotus were the unique dominant soil fungal genera in the rhizospheres of H. undatus. Moreover, TM7a, Novibacillus, Cupriavidus, Mesorhizobium, Trechispora, Madurella, Cercophora, and Polyschema were significantly enriched in the rhizospheres of H. undatus, whereas Penicillium, Blastobotrys, Phialemonium, Marasmius, and Pseudogymnoascus were significantly enriched in the rhizospheres of H. polyrhizus. Furthermore, the relative abundances of Ascomycota and Penicillium were significantly higher in the rhizospheres of H. polyrhizus than in those of H. undatus.

Case report: Pulmonary artery sarcoma diagnosed through rare brain metastases.

We present the case of a 33-year-old male referred across several hospitals because of suspected chronic thromboembolic pulmonary hypertension (CTEPH). Initially admitted in October 2022 for a recurrent, severe cough and diagnosed with CTEPH, he received anticoagulant therapy. However, his symptoms worsened, necessitating a transfer to another facility for thrombolysis treatment. Following an episode of syncope, an MRI scan revealed a metastatic brain tumor. Subsequently, he experienced a third transfer to our hospital, emergency surgery was performed to alleviate cerebral edema and excise a lesion in the left frontal lobe. Postoperative pathology was inconclusive, but a multidisciplinary team meeting, aided by experienced radiologists, eventually confirmed a diagnosis of pulmonary artery sarcoma (PAS) with systemic metastases. This case underscores the necessity of promptly ruling out PAS in patients presenting with significant emboli in the central pulmonary arteries and suggests early referral to specialized centers for suspected cases.

Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients.

BACKGROUND: In patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost and procedural inconvenience. Without the initiation of appropriate anticoagulation, these patients are at risk of increased ischemic stroke recurrence. Hence, cost-effective and accurate methods of predicting AF in ESUS patients are highly sought after. OBJECTIVE: We aimed to incorporate clinical and echocardiography data into machine learning (ML) algorithms for AF prediction on ILRs in ESUS. METHODS: This was a single-center cohort study that included 157 consecutive patients diagnosed with ESUS from October 2014 to October 2017 who had ILR evaluation. We developed four ML models, with hyperparameters tuned, to predict AF detection on an ILR. RESULTS: The median age of the cohort was 67 (IQR 59-74) years old and the median monitoring duration was 1051 (IQR 478-1287) days. Of the 157 patients, 32 (20.4%) had occult AF detected on the ILR. Support vector machine predicted for AF with a 95% confidence interval area under the receiver operating characteristic curve (AUC) of 0.736-0.737, multilayer perceptron with an AUC of 0.697-0.708, XGBoost with an AUC of 0.697-0.697, and random forest with an AUC of 0.663-0.674. ML feature importance found that age, HDL-C, and admitting heart rate were important non-echocardiography variables, while peak mitral A-wave velocity and left atrial volume were important echocardiography parameters aiding this prediction. CONCLUSION: Machine learning modeling incorporating clinical and echocardiographic variables predicted AF in ESUS patients with moderate accuracy.

Deep belief improved bidirectional LSTM for multivariate time series forecasting.

Multivariate time series (MTS) play essential roles in daily life because most real-world time series datasets are multivariate and rich in time-dependent information. Traditional forecasting methods for MTS are time-consuming and filled with complicated limitations. One efficient method being explored within the dynamical systems is the extended short-term memory networks (LSTMs). However, existing MTS models only partially use the hidden spatial relationship as effectively as LSTMs. Shallow LSTMs are inadequate in extracting features from high-dimensional MTS; however, the multilayer bidirectional LSTM (BiLSTM) can learn more MTS features in both directions. This study tries to generate a novel and improved BiLSTM network (DBI-BiLSTM) based on a deep belief network (DBN), bidirectional propagation technique, and a chained structure. The deep structures are constructed by a DBN layer and multiple stacked BiLSTM layers, which increase the feature representation of DBI-BiLSTM and allow for the model to further learn the extended features in two directions. First, the input is processed by DBN to obtain comprehensive features. Then, the known features, divided into clusters based on a global sensitivity analysis method, are used as the inputs of every BiLSTM layer. Meanwhile, the previous outputs of the shallow layer are combined with the clustered features to reconstitute new input signals for the next deep layer. Four experimental real-world time series datasets illustrate our one-step-ahead prediction performance. The simulating results confirm that the DBI-BiLSTM not only outperforms the traditional shallow artificial neural networks (ANNs), deep LSTMs, and some recently improved LSTMs, but also learns more features of the MTS data. As compared with conventional LSTM, the percentage improvement of DBI-BiLSTM on the four MTS datasets is 85.41, 75.47, 61.66 and 30.72%, respectively.