The purpose is to analyze the clinical features and mortality rates of Chinese acute leukemia patients affected by COVID-19 infection. We retrospectively analyzed the clinical characteristics of acute leukemia patients with COVID-19 infection in Henan Province, China, from December 1, 2022, to January 31, 2023. Our study included 100 cases of acute leukemia with COVID-19 infection. The median age was 49.5 years old (58% male and 42% female). Patients with acute myeloid leukemia were 76%, and 24% were acute lymphoblastic leukemia.86% of patients were asymptomatic; 35% of patients received antibiotic treatment, and 25% received antiviral treatment. For the first time, we analyzed the factors affecting the days of nucleic acid cycle threshold (CT) (CT≤36) in acute leukemia patients infected with COVID-19; the days in severe cases and dead patients was significantly longer. We found that in patients with neutropenia who were receiving antibiotic treatment the days was significantly longer, whereas in patients receiving antiviral treatment or delayed treatment this number was shorter. All patients were followed up for three months, and the overall mortality rate was 6%. Although multivariate analysis showed that no death related factor, univariate analysis showed that neutropenia was the main factor affecting mortality in patients infected with COVID-19. Early application of antiviral drug shorten the number of days of COVID-19 nucleic acid CT value≤36 in AL patients infected with COVID-19, which may further reduce the proportion of patients with severe symptoms or death.

Treatment of Acute Lymphoblastic Leukemia is associated with neurocognitive deficits in young children. While computerized measures have been utilized in pediatric oncology research, they exclude patients below the age of 4 years old. Patients enrolled on “Treatment of Newly Diagnosed Acute Lymphoblastic Leukemia in Children and Adolescents” were offered participation in an optional cognitive study. Three-year old patients did not differ from four-year old patients on their ability to complete tests or perform tests. Including patients diagnosed at age 3 will serve to improve our understanding of at-risk patients and the cognitive trajectory of this age group both during treatment.

Plant diseases cause an annual global crop loss of 20-40%, leading to estimated economic losses of 30-50 billion dollars. Tomatoes are susceptible to more than 200 diseases. Breeding disease-resistant cultivars is more cost-effective and environmentally sustainable than the frequent use of pesticides. Traditional breeding methods for disease resistance, relying on direct visual observation to measure disease-related traits, are time-consuming, inaccurate, expensive, and require specific knowledge of tomato diseases. High-throughput disease phenotyping is essential to reduce labor costs, improve measurement accuracy, and expedite the release of new varieties, thereby more effectively identifying disease-resistant crops. Precision agriculture efforts have primarily focused on detecting diseases on individual tomato leaves under controlled laboratory conditions, neglecting the assessment of disease severity of the entire plant in the field. To address this, we created a synthetic dataset using existing field and individual leaf datasets, leveraging a game engine to minimize additional data labeling. Consequently, we developed a customized unsupervised domain-adaptive tomato disease segmentation algorithm that monitors the entire tomato plant and determines disease severity based on the proportion of affected leaf areas. The system-derived disease percentages show a high correlation with manually labeled data, evidenced by a correlation coefficient of 0.91. Our research demonstrates the feasibility of using ground robots equipped with deep-learning algorithms to monitor tomato disease severity under field conditions, potentially accelerating the automation and standardization of whole-plant disease severity monitoring in tomatoes. This high-throughput disease phenotyping system can also be adapted to analyze diseases in other crops with similar foliar diseases, such as maize, soybeans, and cotton.

Scanning electron microscopy (SEM) has significantly advanced morphological studies, particularly in the investigation of fish scale structures. This technique has unveiled intricate architectural details that are crucial for fish identification and classification. In this study, macro- and microscopic analyses were employed to examine the scale morphology of Schizothorax plagiostomus, a vulnerable cyprinid fish from Kashmir, focusing on two body regions (key scales, which were taken from the region below dorsal fin and above lateral line; lateral line scales which were taken from the lateral line). The general scale type observed in Schizothorax plagiostomus was cycloid. Two types of shapes viz., polygonal and cordate were reported in this species. The rostral margin of the scales displayed round and waved forms. The scales exhibited a small and round focus which was antero-centrally positioned. The scales featured narrow or wide grooves (radii) categorized into three types: primary, secondary, and tertiary, present across all four scale fields (anterior, posterior, nuand lateral), forming a tetra-sectioned type. Circuli, arranged in circular patterns around focus were present which were densely placed in anterior and lateral field and widely spaced in posterior field. Notably, lepidonts on the circuli and chromatophores on the posterior margin were absent in this species. These scale characteristics and their morphologies offer a valuable tool for the identification, classification, and phylogenetic analysis of various freshwater fish species and genera.

Vegetation overgrowth in rivers worldwide has been a significant problem due to its potential to reduce flood-flowing capacity and cause biodiversity loss. This study tried to develop a model to predict vegetation recruitment during the initial stage of secondary succession, leading to vegetation overgrowth. This study chose a logistic regression model for predicting vegetation recruitment because of its simplicity and lower computational load than machine learning. The model was designed for the Kinu River in Japan, undergoing significant vegetation overgrowth. Data for the model development was obtained from UAV (unmanned aerial vehicle) aerial surveys and public databases. To ensure the model’s applicability beyond the training rivers, we trained the logistic regression model in its performance across different river flows and geomorphic characteristics, including the normal and flood times and the gravel-bed and sand-bed. The results indicated that the logistic regression model with three explanatory variables — the distance from the river stream, the relative height, and the vegetation existence history —was optimal for all rivers with the F-measures of 0.79 to 0.85. Additionally, using UAV imagery allowed for high spatial resolution in predicting vegetation recruitment. The best model’s prediction map of the vegetation recruitment demonstrated that it could accurately predict vegetation distributions along the main river channel for the gravel and sand beds.

This study assessed the impact of tourism on fish communities in similar tidal pools with varying intensities of tourist activities on two beaches in Ceará, Brazil: Iparana (less structured for tourism) and Flecheiras (more structured). Visual censuses were conducted on days with low visitation (LV, during the week) and high visitation (HV, weekend) in 28 pools each. The study compared the responses of fish communities between the beaches and the intensity of tourist visitation in terms of species richness, abundance, and Shannon’s diversity index. The similarity between tidal pool fish communities was also compared, assuming taxonomic and trophic functional groups. Tourism structure, visitation intensity, and their interaction significantly impacted species richness and the Shannon diversity index. Beaches, visitation intensity, and temperature affect community parameters and trophic functional composition of the tidal pools. Tourism structure visitation intensity mostly influenced species richness, abundance, and diversity. Omnivorous species were more prevalent in areas where tourists provided food, particularly in Flecheiras. The number of tourists significantly altered the composition of fish assemblages in tidal pools, indicating it is a crucial variable affecting the fish community.

This work proposes a WebXR-based cross-platform architecture for developing spatial web apps using the A-Frame and Networked-Aframe frameworks with a view to an open and interoperable metaverse, accessible from both the web and extended reality devices. A prototype was implemented and evaluated, supporting the capability of the proposed technology stack to enable immersive experiences across different platforms and devices. Positive feedback on ease of use of the immersive environment further corroborates the proposed approach, underscoring its effectiveness in facilitating engaging and interactive virtual spaces. This research enriches the discourse on the metaverse by describing an architecture based on web technologies and open standards as opposed to proprietary technologies. By adhering to principles of interoperability and inclusivity, it lives up to Tim Berners-LeeâĂŹs vision of the World Wide Web as an open platform that transcends geographical and technical boundaries.

An all-digital calibration technique for time-interleaved ADC(TIADC) timing mismatch is proposed in this paper. The calibration technique is based on a direction correction-based technique for TIADCs. The proposed method uses Least Mean Squares (LMS) Iteration to gradually estimate and the compensation algorithmfocuses on third-order Tayler series expansion. Different from conventional calibration architecture, the proposed method introduces a corrective technique addressing calibration direction, which may be wrong when the frequency of the input signal does not satisfy the Nyquist sampling theorem of the sub-ADC. The bandwidth of the input signal stands to be broadened when integrated with the proposed calibration algorithm.

11institutetext: Knowledge-based Systems and Document Processing Research Group Faculty of Computer Science Otto-von-Guericke-University Magdeburg 11email: [email protected] Chemical changes of base cations in bulk precipitation ( BP) induced by canopy alteration significantly influence the buffer action against soil acidification and the consequent biogeochemical processes in forest ecosystems. However, the underlying mechanisms that influence the varying magnitudes and directions of acid neutralizing capacities (ANC) in BP during canopy passage remain less understood. Here, we investigated the chemical compositions of base cations (potassium (K +), calcium (Ca 2+), magnesium (Mg 2+) and sodium (Na +)), the capacity of individual alkaline ions to neutralize acidity, in addition to their spatio-temporal variabilities outside and beneath the canopies of Chinese pine plantation ( Pinus tabuliformis Carr.) throughout 2019 growing season with a large proportion of annual rainfall. Results showed that volume-weighted mean concentrations of base cations in throughfall ( TF) were significantly increased with the highest enrichment ratio by K +, followed by Mg 2+, Ca 2+ and Na +. Canopy leaching mainly occurred for K + (59.06%) and Mg 2+ (54.20%) whereas dry deposition of Ca 2+ (57.27%) were the dominant net throughfall flux component. TF ANC was significantly higher than BP, indicating that rainwater beneath the pine canopy became less acidic. Ca 2+ was the predominant acid neutralizing component, followed by K + and Mg 2+ in both BP and TF. However, the capacity of Ca 2+ for neutralizing acidity was weakened whereas K + and Mg 2+ were enhanced in TF compared to BP. Additionally, the concentrations of TF base cations were significantly negatively or positively correlated to canopy cover and TF amount, with exception of TF K +. Antecedent dry period and rainfall intensity were the most influential meteorological parameters affecting the intra-event variation trend and magnitude of TF base cations. Our findings contribute to understanding the controlling processes and underlying mechanisms that drive the complex interactions between base cations nutrients and forest ecosystem.

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Exploring a new method of pharyngoplasty surgery, which uses CO2 laser to dislocate the mucosa and then covers the wound with mucosal flap complementary sutures, successfully preventing postoperative pharyngeal stenosis.

Upstream materials for media formulations are often identified as potential sources of contamination by microorganisms in cellular agriculture. Therefore, this study aimed to evaluate the thermal tolerance of foodborne pathogens cultured in L-15 with varying FBS concentrations (0%, 2%, and 10%) at 36°C, subjecting the media formulations to thermal treatments at 55, 60, 65, 70, and 75°C. The highest thermal inactivation gradients for bacteria were observed in media containing 10% FBS, suggesting that the presence of 10% FBS plays a significant role in increasing bacterial susceptibility to thermal treatment. Escherichia coli cultured in 10% FBS and subjected to 55°C exhibited the highest D-value compared to those cultured in 0% and 2% FBS. However, Salmonella cultured in 10% FBS showed opposite trends with the lowest D-value. Among the Gram-positive and Gram-negative bacteria evaluated, E. coli exhibited the highest z-value across all tested media, signifying its exceptional thermal tolerance compared to the other bacteria. Gram-negative bacteria (E. coli and Salmonella) had decreasing z-values with higher FBS, while Gram-positive bacteria (Listeria and Staphylococcus) showed opposite trends. This study establishes that bacterial response to serum concentrations significantly impacts thermal treatments in cell culture-based food processing and storage. Additionally, the impact of thermally treated samples on cell performance showed no significant difference in cell metabolic activities between control (unpasteurized media) and media pasteurized at 55°C for 75.24 minutes. However, increasing temperature significantly reduced cell metabolic activities, with the lowest metabolic activities observed in cells grown in media heated to 75°C for 0.54 min.

One of the most intriguing outcomes of hybridization is the emergence of asexual hybrids, where canonical gametogenesis is altered, leading to clonal or hemiclonal genome propagation. However, maintaining these lineages is challenging due to frequent irregularities in gamete formation. These irregularities increase the diversity of gametogenic pathways, though their triggers and outcomes remain unknown. We studied these processes in water frog hybrids from the Pelophylax esculentus complex, which reproduce asexually via hybridogenesis. During this process, P. esculentus hybrids usually produce gametes with a genome from either P. ridibundus or P. lessonae. Using fluorescent in situ hybridization with probes to species-specific satellite repeats, we identified genome composition in spermatocytes and spermatids from 47 hybrid males collected from four localities in Eastern Ukraine. Some males exclusively eliminated either the P. ridibundus or P. lessonae genome, suggesting selection before meiosis. Other males transmitted gametes with both genomes simultaneously, indicating elimination of one genome from different gonocyte populations. Such variability in gametogenic pathways among males from different localities implied independent hybrid origins. Additionally, abnormal pairing between P. ridibundus and P. lessonae chromosomes during meiosis indicated an inability to eliminate and endoreplicate genomes of parental species. By comparative genome hybridization, we for the first time identified intensive genome rearrangements between ridibundus and lessonae chromosomes and unstained chromosomal parts suggesting the introgression of different species genome in such hybrids. These genomic rearrangements and introgressions affect hybridogenetic reproduction, causing aneuploidy in gametes.

Habitat selection in animals results from a careful balance of individual requirements, environmental conditions, and ecological disturbances. Preferences can vary across sexes and ages due to differences in survival and reproductive priorities. Despite this variability, most studies have traditionally focused on isolated aspects of either sex or age-related differences in habitat selection, rather than considering a comprehensive range of influencing factors. The mountain dragon lizard (Diploderma splendidum) exemplifies a species adapted to shrub habitats in the dry-hot river valleys of the lower Jinsha River, western China, playing a crucial role in regional ecosystem stability. In this study, we examined the influence of 11 ecological factors on habitat selection by male and female D. splendidum across two distinct age classes (juvenile and adult) to explore sex and age-related disparities. The lizards showed considerable similarity in habitat preferences, but notable differences in their selection of specific ecological factors. Compared to adult females, adult males displayed a preference for higher tree positions, lower light intensity, and moderate vegetation density. Compared to juvenile females, juvenile males favored higher tree positions, low rock formations, and shrubby grassland and forest. Compared to juvenile females, adult females preferred higher tree positions and habitats further from water. Compared to juvenile males, adult males preferred higher tree habitats. Overall, habitat selection complexity in D. splendidum was significantly influenced by sex and age factors. This study contributes to our understanding of how these lizards respond to different physiological structures and resource requirements. These findings enhance current knowledge on reptile habitat selection and provide theoretical insights crucial for ecological restoration and species protection in the hot and dry valley areas of Hengduan Mountain.

Objective To identify phenotypes of pain in patients with endometriosis and to investigate their associations with predictors and quality of life (QoL). Design Population-based study. Setting A referral university center in Quebec City, Canada. Population or Sample A total of 352 patients aged 18‒50 years and diagnosed with endometriosis. Methods Latent class analysis (LCA) was used to identify pain phenotypes. To assess the associations, the three-step approach of LCA was applied. Main Outcome Measures Pain phenotypes, predictors of pain phenotypes, QoL. Results A total of 352 patients were included in the analyses. The diagnosis of endometriosis was either based on histology (N=135), imaging (N=106) or clinical presentation (N=111). The optimal model identified two distinct and homogeneous phenotypes of patients with endometriosis. The two groups had distinct clinical presentations, one with more severe and frequent pain symptoms and poorer quality of life (54%); the other with mild and less frequent pain symptoms (46%). Predictors of a high pain phenotype were a previous treatment failure, use of pain killers, a family history of endometriosis, a low annual family income, and pain comorbidities such as painful bladder, fibromyalgia, migraines, low back pain, irritable bowel syndrome, anxiety, and depression or mood disorders. The presence of endometrioma was predictive of the low pain phenotype. Phenotype membership was associated with distinct quality of life profiles (p<0.001). Conclusion Patients with endometriosis and pelvic pain can be grouped into two distinct and homogeneous phenotypes. Phenotypes membership correlates with quality of life and can be predicted with the patients’ characteristics. These findings will need to be validated in other populations and may inform the development of more specialized or personalized interventions based on the pain phenotypes.

Aims: Endostatin is a type of human vascular endostatin with more stable and higher activity. This study sought to evaluate pharmacokinetics (PK), safety and preliminary efficacy between treatment with endostatin 4 hours intravenous infusion and 72 hours or 168 hours intravenous pump infusion in patients with advanced non-small cell lung cancer (NSCLC). Methods: A total of 24 patients with advanced NSCLC were randomly assigned to group A and B. All patients received a standard 21 days treatment cycle of platinum-based doublet chemotherapy (paclitaxel or pemetrexed) and endostatin. Endostatin was administered at 7.5 mg/m2/day for 4 hours from day 1 to day 14 of cycle 1. Starting from day 1 of cycle 2, endostatin was administered at 105 mg/m2/cycle for 72 hours (group A) or 168 hours (group B), respectively. The total treatment duration was 4 cycles, with the option to extend up to 6 cycles. Results: The PK exposure per cycle of endostatin 4 hours infusion and 72 hours or 168 hours pump infusion were comparable between group A and group B. The majority of adverse events during pump infusion were consistent with those observed during infusion and no endostatin-related serious adverse events were reported. The overall objective response rate (ORR) was 37.5%. Conclusion: The PK exposure between intravenous infusion and intravenous pump infusion at the same total cycle dose is similar. Both 72 hours and 168 hours intravenous pump infusion endostatin were well tolerated, and no new unexpected safety signals were observed.

Although previous studies have indicated that the occurrence of stimulus-response binding (and feature-response binding) is automatic, the influence of attention on the strength of stimulus-response binding remains unclear. This study investigated whether feature-based attention affected feature-response binding within multi-feature objects. We employed a modified partial repetition cost (PRC) paradigm. By maintaining a constant level of attention to features during the retrieval phase and manipulating the task relevance of features during the binding phase, we were able to modulate attention to features during the binding phase. Behavioral data and EEG signals were recorded, incorporating temporal EEG signal decomposition and representational similarity analysis (RSA) to comprehensively examine the influence of attention on the strength of stimulus-response binding during both the binding and retrieval phases. Our results indicated that features attended to during the binding phase exhibited greater behavioral PRC effects during the retrieval phase compared to unattended features. Correspondingly, ERP P3 and decomposed C-cluster P3 components showed larger amplitudes under partial repetition conditions, but this modulation was only observed for task-relevant features during the retrieval phase. Additionally, RSA results during the binding phase demonstrated higher representational similarity scores for feature-response binding when features were attended to. These findings suggest that feature-based attention during the binding phase enhances the strength of feature-response binding, aligning with the theory of intentional weighting in cognitive control.