Background and Purpose: Selective endothelin A (ETA) antagonism has shown promise as a potential treatment for chronic kidney disease (CKD), but the adverse effect of fluid retention associated with ETA antagonists has limited their clinical utility. Combination of low doses of the selective ETA antagonist zibotentan with a fixed-dose sodium-glucose cotransporter 2 inhibitor (SGLT2i) dapagliflozin is currently being evaluated in the Zibotentan and Dapagliflozin for the Treatment of CKD (ZENITH-CKD) clinical trial as an approach to maximize kidney protection via ETA antagonism and SGLT2 inhibition in combination. Approach: This study utilized a quantitative systems pharmacology modeling approach to simulate the dose-response relationship of zibotentan alone and in combination with dapagliflozin in a virtual CKD patient population. Key Results: Simulations predict that interstitial fluid volume (IFV) changes will remain below baseline for zibotentan doses below 0.5 mg when combined with dapagliflozin, while the combination therapy will provide substantial additional improvements in urinary albumin-to-creatinine ratio (uACR), glomerular hypertension, and proximal tubule energy demand, indicating enhanced renoprotection. The simulation also indicate that patients with higher baseline eGFR (>30 mL/min/1.73m2) and baseline uACR (>800 mg/g) may experience greater kidney protective response to the combination therapy with less potential for detrimental fluid retention. Conclusions and impact: If the predicted results are confirmed by the ZENITH-CKD trial, this analysis will enhance mechanistic understanding of the balance between albuminuria reduction and fluid retention with this combination treatment strategy, and will provide a tool to inform optimal population selection for late phase clinical studies and lifecycle management planning.

INTRODUCTIONThe prognosis of adult relapse or refractory B cell acute lymphoblastic leukemia (r/r B-ALL) is dismal, with a complete remission rate of approximately 18%-44% if receiving salvage chemotherapy[1]. In recent years, immunotherapy represented by blinatumomab, inotuzumab ozogamicin (InO) and chimeric antigen T-cell (CART) therapy has demonstrated profound efficacy in r/r B-ALL[3-5]. However, those who have persistent positive measurable residual disease (MRD) still remain a high risk of relapse and poor outcome [2]. So far, only blinatumomab is approved for the treatment of MRD in B-ALL[4]. CD22 is detected to be expressed in more than 90% of B-ALL patients, indicating that CD22 is an ideal therapeutic target for B-ALL [6]. InO is an antibody-drug conjugate comprising a humanized anti-CD22 monoclonal antibody conjugate to calicheamicin. According to the INO-VATE study, significantly higher rate of complete remission was observed in r/r B-ALL patients who received InO monotherapy compared with traditional chemotherapy (73.8% vs 30.9%, P <0.0001) This encouranging data lead to the approvment of InO for the treatment of r/r B-ALL by the US Food and Drug Administration in 2017 [3]. Hitherto, the application of InO in the treatment of MRD has not been reported.

Background: The question of whether inhaled long-acting bronchodilators (iLABs) increase the incidence of cardiovascular adverse events (CVAEs) remains unresolved. The present study analyzed real world data using the U.S. Food and Drug Administration Adverse Events Reporting System (FAERS) database to evaluate iLABs-related CVAEs in patients with COPD. Methods: Disproportionality analysis was used in data mining to screen the suspected CVAEs after different iLABs based on the FAERS database (0/12014-12/2022). The times to onset, outcomes of iLABs-associated CVAEs were also investigated. Results: We identified 12152 reports of adverse events related to three classes of drugs (LABAs, LAMAs, and LABAs combined with LAMAs), of which 591(4.86%) were CVAEs specific to cardiac failure, ischemic heart disease and cardiac arrhythmia. The percentage of men who were affected was higher than that of women (66.80% vs. 30.73%), and elderly patients were more vulnerable than middle-aged patients (52.81% vs. 21.53%). Compared with the full database, the use of iLABs was associated with a higher reporting rate of major CVAEs (n=591, ROR=1.44, 95%CI, 1.30-1.60). LABAs may have a stronger association, based on the highest ROR value (n=304, ROR=1.91, 95%CI, 1.67-2.18). The majority of cardiovascular events related to iLABs occurred within the first 30 days after drug initiation. iLABs-associated CVAEs generally led to mortality and hospitalization rates of 46.19% and 62.61%, respectively. Conclusions: According to the FAERS database, we profiled CVAEs related to various iLABs with more details on occurrences, clinical characteristics, and prognosis. Concerns should be placed on patients with new initiation of iLABs.

Northern peatlands have been a persistent net sink of atmospheric carbon (C) due to the greater rates of gross primary production (GPP) compared to ecosystem respiration (ER). Global warming has raised concerns about the C sink strength of northern environments. In the vast peatlands of the Hudson Bay Lowlands (HBL) region of Canada, warming-induced changes in sea ice dynamics over the Bay have altered its advective influence on the adjacent lowlands. Despite our knowledge of the short-term C exchange in these peatlands, there remain uncertainties in the long-term combined response of GPP and ER to climate change. In this study, the satellite data-driven Vegetation Photosynthesis and Respiration Model (VPRM) was employed to investigate the response of peatland GPP, ER, and net ecosystem exchange (NEE) to temperature and moisture changes. The results show contrasting net CO2 exchange at the two peatland sites over the last 20 years, with the fen acting as a net C source (+24 g C m-2) to the atmosphere and the bog serving as a net C sink (-130 g C m-2). There is ample evidence that a warmer and wetter climate enhanced GPP more than ER, while cooler temperatures weakened the peatland net C sink, regardless of the moisture conditions. Additionally, the advective influence of Hudson Bay on the lowlands produced markedly different C dynamics between offshore and onshore winds, with higher respiration rates (12%–26%) during offshore winds. We discuss the implications for peatland C balance under more frequent onshore winds in the region.

Parentage analyses via molecular markers have revealed multiple paternity within the broods of polytocous species, reshaping our understanding of animal behavior, ecology, and evolution. In a meta-analysis of multiple paternity in bird and mammal species, we conducted a literature search and found 138 bird and 64 mammal populations with microsatellite DNA paternity results. Bird populations averaged 19.5% multiple paternity and mammals more than twice that level (46.1%). We used a Bayesian approach to construct a null model for how multiple paternity should behave at random among species, under the assumption that all mated males have equal likelihood of siring success, given mean brood size and mean number of sires. We compared the differences between the null model and actual probabilities of multiple paternity. While a few bird populations fell close to the null model, most did not, averaging 34.0-percentage points below null model predictions; mammals had an average probability of multiple paternity 13.6-percentage points below the null model. Differences between bird and mammal species were also subjected to comparative phylogenetic analyses that generally confirmed our analyses that did not adjust for estimated historical relationships. Birds exhibited extremely low probabilities of multiple paternity, not only compared to mammals, but relative to other major animal taxa. The generally low probability of multiple paternity in birds might be produced by a variety of factors, including behaviors that reflect sexual selection (extreme mate guarding or unifocal female choice) and sperm competition (e.g., precedence effects favoring fertilization by early or late matings).

Introduction: Leadless pacemakers (LPs) have been suggested to have a lower incidence of pacemaker induced cardiomyopathy (PICM) compared with transvenous systems. LPs have also been suggested to cause less frequent and less severe tricuspid valve regurgitation (TVR) when compared to traditional transvenous pacemakers (TVPs). Given limited research in this field, our study aims to better understand the incidence of PICM and TVR in patients with a LP and the factors that affect these incidences. Methods: The study comprised of patients within the National Capital Region Military Health System who received a Medtronic Micra LP from 2017 to 2021 and had a pacing percentage of >20%. Pre-procedural and follow-up echocardiograms were retrospectively assessed to determine the change in left ventricular ejection fraction (LVEF) and the degree of TVR. Given the known impact of the PICM definition on the reported incidence, we assessed rates of PICM using two distinct definitions, 1.) ≥10% decrease in LVEF or 2.) ≥10% decrease in LVEF to an LVEF of <50%. We also assessed the pacemaker implantation location and the change in QRS duration after implantation and pacing. Results: The study included a total of 48 patients. The average age of patients in the study was 77, with 67% males. The most common reason for LP implantation was complete AV block (38%). Pacemaker locations included high (13%), mid (31%), and apical septum (56%). The mean time interval between pacemaker implantation and follow up echocardiogram was 697 days (SD 460). A total of 5 patients (12.5%) met definition 1 for PICM and 3 patients (6.25%) met definition 2. TVR was graded to be more severe than baseline in 37% of patients, unchanged in 32%, and improved in 30%. The average change in QRS duration after pacing was an increase of 46ms with an average QRS duration of 159ms at follow-up. Conclusion: Compared to commonly reported incidences of PICM, LPs appear to have a significantly lower rate of PICM, regardless of the PICM definition used, increase in QRS duration, or implantation location. In this study, LPs did not statistically significantly impact TVR severity.

Coat colour and pattern are a distinguished feature in mammalian carnivores, shaped by climatic cycles and habitat type. It can be expressed in various ways, such as gradients, polymorphisms, and rare colour variants. Although natural selection explains much of the phenotypic variation found in the wild, genetic drift and heterozygote deficiency, as prominent in small and fragmented populations, may also affect phenotypic variability through the fixation of recessive alleles. The aim of this study was to test whether rare colour variants in the wild could relate to a deficiency of heterozygotes, resulting from habitat fragmentation and small population size. We present an overview of all rare colour variants in the order Carnivora, and compiled demographic and genetic data of the populations where they did and did not occur, to test for significant correlations. We also tested how phylogeny and body weight influenced the presence of colour variants with phylogenetic generalized linear mixed models (PGLMMs). We found 40 colour-variable species and 59 rare colour variants. In 17 variable phenotypic populations for which genetic diversity was available, the average AR was 4.18, HO = 0.59, and HE = 0.66, and FIS = 0.086. We found that variable populations displayed a significant reduction in heterozygosity and allelic richness compared to non-variable populations across species. We also found a significant negative correlation between population size and inbreeding coefficients. Therefore, it is possible that small effective size had phenotypic consequences on the extant populations. The high frequency of the rare colour variants (averaging 20%) also implies that genetic drift is locally overruling natural selection in small effective populations. As such, rare colour variants could be added to the list of phenotypic consequences of inbreeding in the wild.

Chromosomal translocations involving RUNX1 or ABL1 are frequently observed in haematologic neoplasms. Here, we describe a novel fusion between RUNX1 and ABL1 identified by mRNA sequencing in a recurrent case of B-cell acute lymphoblastic leukemia (B-ALL). Four in-frame transcripts were found, and the cells exhibited a BCR-ABL1+ ALL-like gene expression profile. The patient was a 12-year-old boy carrying a complex karyotype. He achieved complete remission (CR) after aggressive treatment with anti-CD19 chimeric antigen receptor modified T-cell (CD19 CAR-T) therapy followed by allogeneic hematopoietic stem cell transplant (HSCT). However, at 14 months after transplant, the patient developed bone marrow relapse. With sequential CD22 CAR-T and CD19 CAR-T infusions, he achieved minimal residual disease (MRD)-negative CR again and took olverembatinib and dasatinib as maintenance therapy. In summary, the novel fusions RUNX1::ABL1/ABL1::RUNX1 were identified for the first time in our patient, and truncated RUNX1 and ABL1 might play a pivotal role in relapse. These patients with ABL fusions may benefit from tyrosine kinase inhibitors (TKIs), but the function of RUNX1::ABL1 as well as ABL1::RUNX1 in vivo needs to be further investigated.

Case report

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Aphasia is a neurological condition that manifests itself through deficiencies in linguistic functions, which are essential for social interaction and activities of daily living. This deficiency is associated with a loss of working memory capacity, which is responsible for the temporary storage of information. This work sought to develop an approach to aid professionals involved in aphasia treatment and rehabilitation programs, aiming to improve the manner in which evidences of rehabilitation are obtained. The methodology is based on an electroencephalography device, which captures brain signals from individuals while they execute a task that stimulates verbal working memory. The signals are processed using an approach based on event-related potentials, which are then used as input to a statistical model trained with a scientifically validated measurement of working memory. The results indicated that the error of the model was slightly larger than expected, but diminished proportionally to the amount of training samples. We conclude the study suggesting research paths to reduce the error of the model and investigate the feasibility of this approach in a clinical context.

Developing smart hydrogel with excellent physicochemical properties and multiple signal output capability for interactively electronic skin still remains challenging. Here, a conductive structural color hydrogels with desirable physicochemical properties (including high stretchability and robustness, self-adhesion and self-healing) was developed to provide synchronous electronic and visual color signals for e-skins. Highly charged elastic nanoparticles were elaborately used as building units for structural color and the hydrogel were prepared by the self-assembly of the nanoparticle to form a non-close-packed array in a mixture comprised of acrylamide, SF, rGO and then photopolymerization. Benefiting from the improved interfacial compatibility between flexible hydrogel network and elastic nanoparticle, covalent cross-linking network structure and synergistic multiple non-covalent bonding interactions, the hydrogel exhibits extraordinary mechanical properties, excellent self-adhesion to diverse substrate and self-healing at room temperature. In addition, the hydrogel also exhibited sensitive resistance changes and synchronous structural color changes under strain. As a proof-to-concept, the hydrogel displayed superior capability for real-time color-sensing and electrical signal monitoring of various human motions, the spatial distribution of external mechanical stimuli as well as identification of different external stimuli, indicating promising applications in the fields of interactively visual electronic skin, wearable devices, and human-machine interfaces.

The positive drift at the end of nanoindentation P-h plot in case of hard titanium diboride (TiB2) films was ascribed to swelling taking place due to strain gradient plastic deformation with the sample contacting the indenter. The indentations performed at lower loads based on the positioning however suffered resistance towards any plastic deformation as per GTN theory. Although the formation of nanocrystallites inside larger grains were observed, indentation performed at grain boundaries or area having comparatively lower atomic density caused plastic deformation.

The current study explores an emerging cardiac metric, heart rate fragmentation (HRF), as a novel biomarker for allostatic load (AL). HRF may better address the limitations of existing cardiac biomarkers (e.g., confounds and interpretation consistency) in applied research settings, with nonclinical samples. The study’s objectives were: 1) can HRF represent response to psychological stress and 2) can resting HRF be used as a measure of predicting subclinical mental health symptoms. One hundred and fifty-six (n = 156; 75% female) undergraduate students were fitted with a chest band to monitor cardiovascular activity, and completed online demographic and psychosocial surveys in which they were grouped as healthy or displaying probable mental health symptoms (pMH; n = 94, 60.25%) based on respective inventory thresholds for depression, anxiety, and posttraumatic stress disorder. Cardiovascular activity was measured capturing the three R’s of cardiac vagal control: a resting baseline, a reactive acute stressor task, and a paced breathing recovery. Results supported the first hypothesis, in that that HRF significantly differentiated between each RRR condition (p < 0.001). While healthy and pMH individuals did not significantly differ within individual conditions, exploratory analyses revealed healthy individuals displayed significantly larger change in HRF reactivity between conditions (p’s < 0.001) in comparison to pMH, which displayed a more blunted pattern. Overall, this study establishes associations between HRF and mental health, and serves as a promising new biomarker that may identify AL in samples that may be otherwise considered “healthy”, while addressing the limitations of prior biomarkers in non-clinical studies.

The present study introduces a health insurance prediction system that leverages machine learning methodologies. In contemporary times, there has been a notable increase in endeavors focused on tackling this matter since the significance of health insurance as a research topic has markedly escalated following the pandemic. The dataset employed in this research comprises 1338 observations 7 columns and corresponds to individual medical expenditures in the United States, available at the Kaggle platform. The dataset encompasses a variety of variables utilized in the prediction of insurance prices, including age, gender, BMI, smoking status, and number of children. The researchers used machine learning models, including neural networks, XAI, and auto modeling, to determine the correlation between pricing and the attributes. The training process involved partitioning the dataset into an 80-20 ratio for training and evaluation. Consequently, the system achieved an accuracy rate of 97% by Gradient Boosting, but we corrected it to 92% by Gradient Boosting Regressor by encoding and hyper-tuning. Also, among predictive machine learning models, Random Forest had the best accuracy i.e., of 83.44%.Â

In this paper, there is a novel model based on ensemble learning for predicting phishing websites. The overall design is a combination of three individual machine-learning models with the help of the uni-variate feature selection model for detecting phishing and non-phishing URLs. The proposed model can minimize the error rate and provide improved accuracy with a short execution time. As compared with other traditional models, this model has higher performance metrics for detecting phishing websites compared with traditional machine learning and deep learning models. Â

Lindenia tetraphylla (Van der Linden, 1825) eggs exhibit an egg structure that is very rare in other Gomphidae species. They have a well-developed surface reticulation structure. The anterior pole of the egg has a small, rounded micropylar area consisting of 7 orifices arranged radially around a central area. The posterior pole has a sessile, truncated cone that carries 55-65 coiled filaments. This study provides a detailed analysis of the ultrastructure of L. tetraphylla eggs using scanning electron microscopy, and the functional and taxonomic significance of the eggshell are discussed.

With the development of medical treatment partnership and “internet + medical service” in China, this study proposes a remote patient perceived value satisfaction model (RPPVSM) with online medical service for specialties from the perspective of patient perceived value. Taking Shanghai Pulmonary Hospital Specialist Alliance (SPHSA) as the research subject, RPPVSM was constructed based on ACSI and TAM. Structural Equation Modeling (SEM) was modified to have a better degree of fitness and validation outcomes of the hypothesis as follows: Perceived ease of use has a significantly positive impact on perceived value with coefficient being 0.248; perceived usefulness has a significantly positive impact on the satisfaction with coefficient being 0.577; perceived value has a significantly positive impact on satisfaction with coefficient being 0.163. Perceived synergy has a significantly positive impact on perceived value with coefficient of 0.547; perceived ease of use will have a significantly positive impact on satisfaction through the perceived value variable with coefficient of mediation being 0.094; perceived synergy has a significant impact on satisfaction through perceived value with mediation coefficient being 0.196. The results suggest that the inclusion of the patient’s perception value index in the medical information platform is conducive to the construction of RPPVSM.

This paper presents a shadow signal generator that produces square and triangular waveforms. The oscillator frequency can be changed using an external circuit (shadow oscillator). This method will make the conversion speed better than the conventional oscillators. The technique is based on utilizing an external circuit to modify the comparator’s tripping point. The circuit is built using widely available commercial integrated circuits, 1% accurate resistors, and DC supplies with a ±5V voltage. The recommended setup is suitable for instrumentation where the oscillation frequency is directly proportional to the variation in the resistance of the sensor. The functionality of the proposed design was confirmed by experimentation and simulation. The oscillation’s frequency can be changed to be nearly 10 times greater than its starting value, according to the results.

Despite the performed progressive research work, the interpretation of negative group delay (NGD) function remains not familiar to non-specialist design and fabrication circuit engineers. The functionality misunderstanding limits the NGD circuit applications compared to other classical electronic functions. The present paper is dealing on the design of tunable property circuit by operating with positive and negative delay behaviors. The topology of the tunable circuit by using low-pass (LP) type NGD one is described. The design formulas for calculating the circuit resistor and capacitor parameters from the desired delay are expressed. The design feasibility of the tunable circuit composed of LP-NGD cell and RC-circuit is validated with a proof-of-concept (PoC) implemented on a test board. Two different signals with pulse and arbitrary waveforms having tens-milliseconds duration were considered during the validation tests. As expected by tuning a varistor from 0.4 kΩ to 1 kΩ, the negative delay behavior varying from about -0.4 ms was verified thanks to the time-advanced effect due to the LP-NGD property. Then, the output signal delay was observed to become positive when the varistor is tuned from 1 kΩ to 3 kΩ.

The creation of a system for depression detection is proposed, based on the acquisition and processing of ECG and PPG signals, followed by the development of an algorithm for pattern classification and detection. The main goal is to achieve an accurate classification of an individual into a depression or non-depression group, ultimately achieving the correct detection of the mentioned problem. This was accomplished through the analysis of a set of physiological variables taken from PPG and ECG signals, using an experimental protocol called script-driven imagery adapted to the current paradigm, applied to individuals from the High Specialized Medical Center of Bajio T1 in Leon, Mexico. The variables to be used include heart rate variability, pulse transit time, heart rate, respiration signal, physiological coherence of each, and the global coherence index, as well as other frequency-related variables selected based on a literature review. Subsequently, a Python program was developed for processing and obtaining the values of the mentioned variables for later use in a machine learning code. A multi machine learning model test was carried just to find out that the binary classification algorithm that yielded the best performance was a Random Forest, with a sensitivity and accuracy of 76% for the validation group, although higher percentages were achieved with smaller groups of individuals. A review of the performance of the best features in the algorithm was also conducted to identify which variables can have a greater impact when attempting to detect a depressive state in an individual.

Salt stress is one of the main abiotic stresses that affect plants. The jasmonic acid ( JA) signaling pathway is an important pathway that converts the normal growth state into the stress state when plant cells encounter abiotic stress. OsJAZ5 is a JAZ protein family gene, but how the JA signaling pathway promotes rice responses to salt stress is unclear. In this study, after screening for the OsJAZ5 gene, a yeast function analysis using the yeast mutant Axt3k was performed to determine its salt resistance sensitivity. The phenotype analysis showed that it was overexpressed in rice and promoted growth under salt stress. An analysis of the superoxide dismutase, peroxidase, phenylalanine ammonolyase, and catalase activities showed that the OE-3 and OE-5 lines promoted OsJAZ5 activity to maintain the reactive oxygen species dynamic balance under salt stress. In addition, the protein-protein interaction analysis and protein-protein docking confirmed that OsJAZ5 interacts with OsMYL1 and OsMYL2, demonstrated that OsJAZ5 promotes reactions by OsMYL1, OsMYL2, and OsMYC2 and that their expressions were further enhanced by OsJAZ5 through JA signaling of O sMYC2. Thus, expression of the JA signaling response gene was activated by salt stress and its effect on OsJAZ5 promoted salt tolerance in rice.

Stomata play a pivotal role in regulating gas exchange between terrestrial plants and the atmosphere controlling water and carbon cycles at organismal, ecosystem and global levels. Accordingly, our objective was to investigate the impact of ultraviolet-B radiation, a neglected environmental factor varying with ongoing global change, on stomatal morphology and function by means of a comprehensive meta-analysis. We found 45 peer-reviewed publications containing altogether 143 case studies for analysis. The overall UV effect at the leaf level is to decrease stomatal conductance, stomatal aperture and stomatal size, although stomatal density was increased. The significant decline in conductance is marked in short-term experiments, with more modest decreases noted in long-term UV studies. We found that short-term experiments in growth chambers are not representative of long-term field UV effects on stomatal conductance. Further, we found a stronger UV effect in grasses than in herbs, while the reduction of stomatal conductance was insignificant in trees. It is hypothesised that these alterations in stomatal function have important potential consequences for plant life. In the short term, UV-mediated stomatal closure may reduce transpiration and alleviate drought stress. However, in the long term more complex changes in stomatal aperture, size and density may reduce carbon sink capacity, and enhance leaf and surface warming, potentially exacerbating the negative effects of drought and/or heatwaves on plant ecosystems and endangering long-term plant survival.

Summary: The hindrance of kernel development caused by waterlogging stress (WS) is the direct reason for the peanut yield reduction. Currently, the mechanism of kernel filling responding to WS remains unknown. The waterlogging-sensitive variety Huayu 39 was subjected to WS for 3 days after 7 days after gynophores touched the ground (DAG), and the key stage of WS affecting kernel filling is 14, 21, and 28 DAG. WS decreased the average filling rate and kernel dry weight. Therefore, transcriptome sequencing and widely-targeted metabolomic analysis were conducted on kernel to elucidate the mechanism for the decrease in average filling rate under WS, revealing that overexpression of the gene encoding tryptophan decarboxylase ( AhTDC), which caused the accumulation of melatonin, reduced kernel weight. The sucrose transformation rate was limited by the crosstalk between melatonin and ethylene, thereby reducing the kernel filling rate and hindering kernel development. Our results are crucial for formulating measures to alleviate the negative impact of WS on peanut yield and quality, providing a basis for exploring high-yield and high-quality cultivation, molecular-assisted breeding, and waterlogging prevention.