An unprecedented surge of Omicron infections appeared nationwide in China in December 2022 after the adjustment of COVID-19 response policy. In this study, we report the clinical and virological characteristics of SARS-CoV-2 Omicron BA.5 infections among children in Shanghai during the outbreak in late December 2022. We sequenced the 64 SARS-CoV-2 positive samples obtained from hospitalized children. The genomic monitoring revealed that the current outbreak was driven by the BA.5.2.48 and BF.7.14 subvariants. Additionally, children with BA.5.2.48 infection were more frequently observed to experience vomiting/diarrhea compared to those with BF.7.14 infection. The high-frequency unique non-synonymous mutations were present in BA.5.2.48 (N: Q241K) and BF.7.14 (nsp2: V94I, nsp12: L247F, S: C1243F, ORF7a: H47Y) with respect to their parental lineages. Of these mutations, C1243F mutation in S protein, L247F mutation in nsp12, and H47Y mutation in ORF7a protein were predicted to have a deleterious effect on the protein function. Besides, H47Y mutation was also found to increase the stability of ORF7a protein. Therefore, attention should be paid to these specific mutations, especially for H47Y mutation, which could serve as a viral immune escape strategy due to the potential immunomodulatory ability of the ORF7a protein. Continuous genomic monitoring and clinical manifestation assessments of the emerging variants will be crucial for effective responses to the ongoing COVID-19 pandemic.

Temporal and spatial distribution of fine root influences the potential for resource acquisition in soil profiles, which defines how plants interact with local soil environments; however, a deep understanding of how vertical fine root distribution and their temporal dynamics varies with soil structural variations is lacking. We subjected four xerophytic species native to an arid valley of China, Artemisia vestita, Bauhinia brachycarpa, Sophora davidii, and Cotinus szechuanensis, to increasing rock fragment content (RFC) treatments (0%, 25%, 50%, and 75%, v v-1) in an arid environment and measured fine root vertical profiles over four years of growth. Fine root depth and biomass of woody species increased with increasing RFC, but the extent of increase declined with plant age. Increasing RFC also increased the degree of interannual decreases in fine-root diameter. The limited supplies of soil resources in coarse soils explained the increases in rooting depth and variations in the pattern of fine root profiles across RFC. Fine root depth and biomass of the subshrub species (A. vestita) in soil profiles decreased with the increase in RFC and plant age, showing an opposite pattern from the other three woody species. Within species, the annual increase in fine root biomass varied with RFC, which led to large interannual differences in the patterns of fine root profiles. Capacity of younger or subshrub plants to cope with soil environmental changes were greater than the older or shrub plants. These results provide insights into the limitations of soil resources in dry and rocky environments, and have management implications for degraded agroforest ecosystem.

Left atrial (LA) dilatation is a powerful predictor of cardiovascular morbidity and mortality. LA longitudinal strain parameters evaluating reservoir, conduit and contractile strain can represent LA functions. We investigated the association between LA strain and left ventricular (LV) functions using speckle-tracking echocardiography in children with mitral regurgitation in 45 asymptomatic mitral regurgitation patients graded as mild, moderate and severe. LV strain was lower in the moderate group (–17.8±3.7%) and further reduced in the severe regurgitation group (-16±2.14%) in comparison with the reference group (-20.5±6.2%). Regarding LA functions, reservoir strain was higher in the severe and moderate mitral regurgitation groups (38±12.9% and 40.7±9.5%, respectively) in comparison with the controls (40.0±7.2%; p<0.0001). A milder depression of contraction was observed in the severe group (12.2%) than in the moderate group (13±7.2%). In the moderate and severe groups, LV strain correlated significantly with the vena contracta (r=–0.858; p=0.04). Vena contracta was the only independent association for LV longitudinal strain. ROC curve analysis predicted LV longitudinal strain as shown by vena contracta, with a cut-off value >5.65 mm. Vena contracta had a positive predictive value of 75% for predicting LV function. We propose the use of LA and ventricular strain during the follow-up of asymptomatic children with mitral regurgitation. Also, a vena contracta diameter of >5.6 mm can be used as a threshold for LV function impairment.

Introduction: A giant right ventricular myxoma with simultaneous pulmonary embolism during Transthoracic Echocardiographic examination is rare, hardly been reported in the literature. We present a case of a giant right ventricular myxoma with being separated into pulmonary thrombus simultaneously during process of Transthoracic Echocardiographic examination. Case presentation: An 18-year-old young man performed physical examination before college entrance examination. Transthoracic echocardiography (TTE) showed: a heterogeneous mass was found in the right ventricle. The patient suddenly felt the symptoms of chest pain and dyspnea during a transthoracic ultrasound examination, and TTE demonstrated the mass maybe a myxoma with being separated into pulmonary thrombus simultaneously. Electrocardiogram showed complete right bundle branch block. The young man underwent intracardiac repair immediately and was doing well. Discussion/Conclusion: Although myxoma of the right heart is common, complicating of pulmonary embolism during examination is rare especially. Early diagnosis of right heart myxoma complicated with pulmonary embolism provides an important basis for timely operation, and provides a guarantee for saving the life of patients.

An asymptomatic 48-year-old gentleman presented for routine interrogation of his Medtronic dual chamber transvenous pacemaker. The device was implanted 4 years ago for post-operative intermittent high grade atrio-ventricular block following mechanical aortic valve replacement. As per our protocol, we performed a 12-lead electrocardiogram with and without magnet application. The unusual response elicited after application of magnet is mechanistically explained.

Background: Previous studies described a higher prevalence of cardiovascular comorbidities during the winter season. Data regarding seasonal association of atrioventricular (AV) block are scarce. Methods: A retrospective cohort analysis of all patients admitted to a tertiary medical center with AV block requiring a permanent pacemaker (PPM) implantation between 2006-2017 was performed. In a time-series analysis, the seasonal incidence of PPM implementations due to AV block was assessed and adjusted for meteorological factors. The association between the weekly incidence of PPM implantations and the weekly rates of influenza as reported by the Israel Center of Disease Control (ICDC) were also assessed. Result: The study population included 759 patients. Mean age was 76.1 years and 55% were males. Most of the patients (34.1%) were admitted in the winter season. In multivariate analysis, there was a significantly higher incidence of PPM implantations among men during the winter season as compared to the fall season (Adjusted IRR [Incidence Rate-Ratio] 1.40, 95% CI 1.05;1.88; p<0.05), and a significant increase of 24% in the incidence of PPM implantations during the influenza season as compared to the rest of the year (Unadjusted IRR 1.24, 95% CI 0.99;1.53; p<0.05). Conclusion: In the present analysis the incidence of PPM implantations due to AV block was higher among men during the winter season and correlated with high influenza illness rates. Further prospective and larger studies are required to assess these findings.

We introduce a fast and easy method of successfully grasping a lead without a free end called the “Wire ThRoUgh Snare Twice (Wire TRUST)” technique in a 49-year-old male patient who required transvenous lead extraction (TLE) and lead replacement due to lead malfunction. Our proposed technique is less difficult than using the Needle’s eye snare because the pigtail catheter is softer and has better operability. The Wire TRUST technique promptly allows a combined superior and femoral approach for TLE, even when the lead tip is difficult to free because of severe adhesion.

Binary similarity detection determines whether two given binary code snippets are similar or not, usually on function granularity. This task is challenging due to different compilation optimizations and CPU architectures. Recently, deep-learning methods have made great achievements in this field, although most of them use artificially selected features or ignore some important semantic information like code literals or function signatures during feature processing. In addition, random samples and pair loss function are used in similarity training, which only covers limited similarity relations between functions. In this paper, a new framework MFEN-Sim is proposed to detect similar binary functions. The framework contains three stages: feature extraction and normalization, mutli-feature based function feature embedding network (MFEN) and similarity learning network. Multiple features including assembly instructions, CFG structures and function code literals are extracted from binary functions. Then these features are fed into MFEN composed of three modules: function semantic and structure embedding module, function signature prediction module, and function code literal embedding module. The three modules generate embeddings representing the function semantic and structural features, the function signature prediction features and the function code literal features. Finally, MFEN-Sim utilizes a similarity training network based on contrastive learning to make MFEN recognize more similarity relations between functions. MFEN-Sim is evaluated on 281,601 functions in 144 binaries and 17 CVEs in real-world software. Experimental results show that our work outperforms state-of-the-art systems ( i.e., Gemini, FIT and SAFE) by 7.1%, 9.9% and 8.2% on AUC metric in cross-architecture, optimization-level similarity detection, and achieves higher recall than baselines in searching vulnerabilities in real-world applications.

Biodiversity varies across the world and is influenced by multiple factors, such as environmental stability and past historical events (e.g., Panama Isthmus). At same time, organisms with unique life-histories (e.g., parasites) are subject to unique selection pressures that structure their diversity patterns. Parasites represent one the most successful life-strategies, impacting directly and indirectly the ecosystem by cascading effects on host fitness and survival. Here, I focused on a highly diverse, prevalent, and cosmopolitan group of parasites (avian haemosporidians) to investigate the main drivers of regional parasite diversity on a global scale. To do so, I compiled data from four global datasets on (i) avian haemosporidian (malaria and malaria-like) parasites, (ii) bird species richness, (iii) avian functional traits, and (iv) climate data. Then, using generalized mixed models, I evaluated potential drivers of haemosporidian diversity. I found that haemosporidian diversity is driven by both host regional diversity and functional traits, and by environmental conditions. In other words, parasite diversity increased with increasing host richness and higher numbers of resident and territorial birds. Further, greater temperature seasonality was also positively correlated with parasite diversity. Hence, regions harboring the greatest resident/territorial avian diversity (e.g., neotropics) and/or higher temperature seasonality (e.g., North America) generally harbor the highest diversity of haemosporidian parasites. Overall, I demonstrated that haemosporidian parasite diversity is intrinsically associated with their hosts’ diversity and functional traits.

Nickel(II) complexes with pyrazole-based ligands are widely employed in catalysis of ethylene oligomerization and subsequent Friedel-Crafts alkylation of toluene. We have prepared ten new nickel(II) dibromide complexes with various substituted bis(azolyl)methanes. They have been characterized using 1H NMR, IR, high resolution mass spectrometry and elemental analysis. The structures of three complexes have been unambiguously established using X-ray diffraction. It was found that these complexes in the presence of Et2AlCl or Et3Al2Cl3 are active both in ethylene oligomerization and Friedel-Crafts alkylation processes (activity up to 3720 kgoligomer·mol[Ni]−1·h−1). The use of Et3Al2Cl3 results in the higher share of alkylated products (up to 60%). Moreover, catalytic systems activated with Et3Al2Cl3 produced small amounts of odd carbon number olefins (up to 0.8%). The Friedel-Crafts alkylation was used as a trap for previously undetected short-chain odd carbon number olefins (C3 and C5).

Recently, there is an exponential influx of textual data in big data applications, which necessitates the requirement of text mining tools for analysis of data. In Text Mining applications (TM), Text Summarization (TS) has emerged as an emergent field in Natural Language Processing (NLP). Mostly, in TS, abstractive approaches are presented which build complex models, and thus, a shift is envisioned towards graph-based extractive text summarization models. Such models allow review and feedback analysis of a service or product, and have the benefits of being less complex, flexible, and require low computational resources. This makes them an effective fit for modern text mining based big data and Internet-of-Things (IoT) applications. Thus, in the proposed work, we present a scheme, GETS, which exploits a graph-based model to establish relations between words and sentences based on statistical operations. In the scheme, a post processing phase is presented which uses sentence clustering based on graph preparation. To make the scheme scalable fit for real world applications, we use the Apache Spark environment for parallel execution of graph-based operations. In experimental setup, the Recall-oriented Understudying Gisting Evaluation (ROUGE) parameters is used to evaluate the proposed graph based model with a comparative analysis with ROUGE 1,2,L measures. Comparative analysis is done based on clustered and non-clustered approaches. The obtained results renders the scheme effective as a backend of Artificial Intelligence (AI) models in crowdsourcing applications and decision-analytics models.

Turbine wake and local blockage effects are known to alter wind farm power production in two different ways: (1) by changing the wind speed locally in front of each turbine; and (2) by changing the overall flow resistance in the farm and thus the so-called farm blockage effect. To better predict these effects with low computational costs, we develop data-driven emulators of the ‘local’ or ‘internal’ turbine thrust coefficient CT* as a function of turbine layout. We train the model using a multi-fidelity Gaussian Process (GP) regression with a combination of low (engineering wake model) and high-fidelity (Large-Eddy Simulations) simulations of farms with different layouts and wind directions. A large set of low-fidelity data speeds up the learning process and the high-fidelity data ensures a high accuracy. The trained multi-fidelity GP model is shown to give more accurate predictions of CT* compared to a standard (single-fidelity) GP regression applied only to a limited set of high-fidelity data. We also use the multi-fidelity GP model of CT* with the two-scale momentum theory (Nishino & Dunstan 2020, J. Fluid Mech. 894, A2) to demonstrate that the model can be used to give fast and accurate predictions of large wind farm performance under various mesoscale atmospheric conditions. This new approach could be beneficial for improving annual energy production (AEP) calculations and farm optimisation in the future.

Microbial communities are complex networks of microorganisms that interact with each other and their environment. Understanding the functional roles of individual species and their interactions is challenging. High-throughput sequencing has provided valuable insights into microbial communities, but the vast amounts of data generated make deciphering mechanisms difficult. Gene regulatory networks (GRNs) provide a powerful framework for studying the functional roles of individual genes and their interactions in complex biological systems. In microbial ecology, GRNs can be used to identify key regulatory genes and their targets involved in ecological processes. By integrating genomic and transcriptomic data with environmental metadata, GRNs can reveal the genetic architecture of microbial communities. This review provides an overview of the application of GRNs in microbial ecology and discusses the challenges and opportunities of using this approach. Case studies demonstrate the potential of GRNs in uncovering novel insights into microbial community structure and function. Integration of GRNs with other omics approaches and environmental metadata holds great promise in advancing our understanding of microbial ecology and its relevance to human health and environmental sustainability.

This research study was conducted to understand the adoption of the Internet of Things as a technology in the Australian manufacturing industries. As a part of the study, the adoption of the Internet of Things in the manufacturing domain was identified as a dependent variable through various online literature reviews. The following five independent variables were then identified as follows: competitiveness, regulatory support, cost savings, management support, and manufacturing growth. The objective of the research and the research questions were defined to assess the independent variables on the adoption of the technology Internet of Things. It was identified that all five independent variables positively impacted the adoption of the Internet of Things in the manufacturing industries in Australia. This will lead to unplanned downtime reduction and clearer data transparency to take the faster decision.

Abstract A recent study identified two EGFR gene mutations commonly found in the EGFR gene for glioblastoma multiforme (GBM), EGFRvIII, and EGFRvIVa in two of ten African American patients with esophageal squamous cell carcinoma (ESCC). EGFRvIII mutation is a key driver in tumor progression and is associated with a poor prognosis as it lacks the L1 and CR1 domains, which are crucial for ligand binding. Herein a discussion is presented on the identification of these rare and clinically significant mutations in ESCC patients, which raises important questions about the functional implications of these mutations, the feasibility of observational clinical trials, and the use of off-label EGFR inhibitors.Keywords:  EGFR, Esophageal Squamous Cell Carcinoma, Glioblastoma Multiforme, Genomics, Targeted Therapy Introduction Esophageal cancer has a strikingly low survival rate, mainly due to the lack of diagnostic markers for early detection and effective therapies. Their incidence rate in the U.S. alone still remains skewed in the disfavor of the African American population. According to recent trends from the NCI SEER data \cite{application}, the incidence rates of individuals in African Americans (AA) diagnosed with esophageal squamous cell carcinoma (ESCC) are nearly twice as much as combined rates from all other races (Fig 1). Though the incidence rates have witnessed a remarkable decline in the AA population and their predisposition to ESCC, the resulting mortality rates still remain high compared to the rest of the population in the US.Recently, a study by whole-genome sequencing was carried out in matched tumor and normal tissues from 10 African American patients to identify tumor-specific genomic abnormalities\cite{Erkizan2021}. Two interesting mutations were identified in the EGFR gene that is typically found in the EGFR gene for Glioblastoma Multiforme (GBM), EGFRvIII, and EGFRvIVa. These findings raise important questions about the functional implications of these mutations between these two cancers, the feasibility of observational clinical trials, and the use of off-label EGFR inhibitors; a discussion of which is presented below.

Objective During the COVID-19 pandemic, the adopted containment measures have affected other respiratory virus epidemiology. Consequently, we aimed to describe the characteristics of respiratory virus infection in hospitalized pediatric acute respiratory infections (ARIs) patients prior to and throughout COVID-19 in East China.   Methods Nasopharyngeal secretions were collected from 9782 pediatric ARIs patients hospitalized in Shaoxing Maternal and Child Health Hospital from January 2018 to December 2022.  Changes in positivity viral detection rates and epidemiological as well as clinical characteristics were analyzed and compared. Results 1633 strains of 7 common respiratory viruses were detected, with a total positive rate of 16.37% (821/5021) in 2018-2019 and 17.06% (812/4761) in 2020-2022.  Compared with 2018-2019, RSV positive rate increased significantly in 2020-2022, while ADV, PIV-2, PIV-3, and flu-B detection rates were significantly reduced (P < 0.05).  The RSV-positive rate in winter increased significantly more than in other seasons (P < 0.05), while PIV-3 was mainly prevalent in spring and summer.   Conclusion During the COVID-19 pandemic, there were significant age distribution and seasonal differences in respiratory virus infection among hospitalized children with ARIs in East China.

Chemoreception is critical for the survival and reproduction of animals. Except for a reduced group of insects and spiders, the molecular identity of chemosensory proteins is poorly understood in invertebrates. Gastropoda is the extant mollusk class with the greatest species richness, including marine, freshwater, and terrestrial lineages, and likely, highly diverse chemoreception systems. Here, we performed a comprehensive comparative genome analysis taking advantage of the chromosome-level information of two Gastropoda species, one of which belongs to a lineage that underwent a whole genome duplication event. We identified thousands of previously uncharacterized chemosensory-related genes, the majority of them encoding G protein-coupled receptors (GPCR), mostly organized into clusters distributed across all chromosomes. We also detected gene families encoding degenerin epithelial sodium channels (DEG-ENaC), ionotropic receptors (IR), sensory neuron membrane proteins (SNMP), Niemann–Pick type C2 (NPC2) proteins, and lipocalins, although much smaller in size. Our phylogenetic analysis of the GPCR gene family across protostomes revealed: (i) large gene family expansions in Gastropoda; (ii) clades including members from all protostomes; and (iii) species-specific clades with a huge number of receptors. For the first time, we provide new and valuable knowledge into the evolution of the chemosensory gene families in invertebrates other than arthropods.

The Special Issue brought together papers that highlighted the power of high-throughput sequencing (HTS) data to address classic questions in ecology and evolution, and/or use models/theory to infer key ecological and evolutionary processes, and make predictions, particularly focused on metabarcoding (amplicon) datasets in conjunction with complementary -omics data types. We highlight key papers that show the power of the new technology to address questions related to: (1) community assembly, and the interplay between competition, environmental filtering, and neutral processes, that can be inferred from the data, and how these change according to environmental conditions, and across successional and extended evolutionary time. (2) Interaction networks, and how these can show predictable changes over similar spatial and temporal gradients, providing insights into questions of biotic resilience. Studies also examined (3) cross scale interactions and those involving hosts and their microbiomes, with the critical development being the ease of comparison and integration across scales of organismic complexity, allowing insights at one scale to inform the other. The approach is also amenable to (4) studies of invasive species and biotic homogenization, providing insights of shifts in alpha and beta diversity across a wide range of spatial scales.

Sharks, rays and chimaera form the clade Chondrichthyes, an ancient group of morphologically and ecologically diverse vertebrates that has played an important role in our understanding of gnathostome evolution. Increasingly studies have are seeking to investigate evolutionary processes operating within the chondrichthyan crown group, with the broad aim of understanding the driving forces behind the vast phenotypic diversity observed amongst its constituent taxa. Genetic, morphological and behavioural studies have all contributed to our understanding of phenotypic evolution yet are typically considered in isolation in the context of Chondrichthyes. I argue that integrating these core fields of organismal biology is vital if we are to understand the evolutionary processes operating in contemporary chondrichthyan taxa, and how such processes have contributed to past phenotypic evolution. In light of the global extinction crisis facing this clade, this understanding is crucial if we are to successfully conserve rapidly declining chondrichthyan populations.

Worldwide climate-driven shifts in the distribution of species is of special concern when it involves habitat-forming species. In the coastal environment, large Laminarian algae – kelps – form key coastal ecosystems that support complex and diverse food webs. Among kelps, Macrocystis pyrifera is the most widely distributed habitat-forming species and provides essential ecosystem services. This study aimed to establish the main drivers of future distributional changes on a global scale and use them to predict future habitat suitability with a focus on the southeastern Pacific coast. Using species distribution models (SDM), we examined the changes in global distribution of M. pyrifera under different emission scenarios. To constrain the drivers of our simulations to the most important factors controlling kelp forest distribution across spatial scales, we explored a suite of environmental variables and validated the predictions derived from the SDMs. Minimum sea surface temperature was the most important variable explaining the global distribution of suitable habitat for M. pyrifera. Under different climate change scenarios, we always observed a decrease of suitable habitat at low latitudes, while an increase was detected in other regions, mostly at high latitudes. Along the southeast Pacific, we observed a range contraction of 14.5◦ of latitude for 2100 under the RCP 8.5 scenario, implying a loss of habitat suitability throughout the coast of Peru and poleward to 27.83◦S in Chile. On the northern coast of Chile, the area coinciding with the complete habitat loss predicted by our model is under heavy exploitation with over 11,180 tons harvested every year from natural populations of M. pyrifera. The loss of habitat suitability will likely have significant impacts on marine biodiversity and ecosystem functioning and is a harbinger of massive impacts in the socio-ecological systems of the southeastern Pacific.

A document by Kritika Mishra. Click on the document to view its contents.

Background: Healthcare for transgender people can be unsafe and inequitable. Objectives: To explore the experiences of care surrounding hysterectomy as part of female to male (FtM) gender affirming surgery. Design: Qualitative observational study Setting: Aotearoa/New Zealand Participants: Ten people (out 12 people) who underwent FtM over a four-year period. Results: No one person’s experience of the FtM journey was affirming across the whole surgery journey. Transgender health literacy was central to inclusive practice as it mediated bodily autonomy being upheld. FtM (hysterectomy) surgery was described as “ life-saving”. The physical care environment influenced the experience of the healthcare encounter. For example, the waiting room was intimidating, with a gendered clinic name and toilets. Some participants took a female support person/partner so that “ people looking would assume that I was there supporting her, not the other way around.” Communication misalignments were evident around information provided/understood about fertility and ovarian preservation, requirement of a pre-operative pregnancy test, and post-operatively, about bleeding and when sexual intercourse could be resumed. Participants were also placed in the position of both receiving care and providing education: “ I also shouldn’t have to be going in there for treatment, and then being expected to educate the medical professional that’s meant to be helping me… I’m not getting paid to give you a TED talk on how my trans body works.” Conclusions: A whole care pathway approach to increasing transgender health literacy will facilitate better alignments in communication, uphold bodily autonomy and lead to equitable inclusive practice.

Objective: To establish a prediction model to help the doctor determine which patients are more suitable for transvaginal repair based on the prediction model. Design:All enrolled patients underwent CSD repair performed by a single team. All women in this study had a follow-up clinic visit at 6 months to record their menstruation and measure multiple parameters of the CSD by MRI. Setting:Retrospective study Sample: This study included 1015 women who underwent transvaginal repair of cesarean scar diverticulum (CSD) at Xinhua Hospital and Shanghai First Maternity & Infant Hospital between June 2014 and May 2021. Main outcome measures: CSD patients are categorized as having optimal healing when the menstruation duration is no more than 7 days and the thickness of residual myometrium（TRM） is no less than 5.39 mm after vaginal repair. The final nomogram is constructed to predict surgical outcomes based on pre- and postoperative variables. Results: The key factors determining optimal healing are the timing of cesarean section; menstrual cycle; CSD length, width, depth, and the myometrial layer thickness of the lower uterine segment. With the prediction model, scores are given to each parameter according to the statistics. Total scores range from 0 to 25 points with a cutoff point of 16.5. Predicted that transvaginal repair achieves optimal healing when a score greater than 16.5 points. Uterine position and preoperative TRM are the key factors affecting postoperative TRM. The width of the CSD and the thickness of the lower uterine segment are the key factors affecting postmenstrual abnormal uterine bleeding (P<0.01). Conclusions: We establish a prediction model system for the first time that may predict the repair effect of CSD and can potentially be useful in future clinical trials to determine which patients should be repaired or other treatment options.

Density-Driven Gravity and Layer Formation A New Framework for Understanding Matter in the Universe