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Simultaneous localization and mapping (SLAM) provides user tracking and environmental mapping capabilities, enabling communication systems to gain situational awareness. Advanced communication networks with ultra-wideband, multiple antennas, and a large number of connections present opportunities for deep integration of sensing and communications. First, the development of integrated sensing and communications (ISAC) is reviewed in this study, and the differences between ISAC and traditional communication are revealed. Then, efficient mechanisms for multi-domain collaborative SLAM are presented. In particular, research opportunities and challenges for cross-sensing, cross-user, cross-frequency, and cross-device SLAM mechanisms are proposed. In addition, SLAM-aided communication strategies are explicitly discussed. We prove that the multi-domain cooperative SLAM mechanisms based on hybrid sensing and crowdsourcing can considerably improve the accuracy of localization and mapping in complex multipath propagation environments through numerical analysis. Furthermore, we conduct testbed experiments to show that the proposed SLAM mechanisms can achieve decimeter-level localization and mapping accuracy in practical scenarios, thereby proving the application prospect of multi-domain collaborative SLAM in ISAC., Comment: Accepted by the IEEE Wireless Communications Magazine

This work aimed to investigate the role of nuclear factor peroxisome proliferator-activated receptor α (PPARα) in modification of circadian clock and their relevance to development of nonalcoholic fatty liver disease (NAFLD). Both male wild-type (WT) and Pparα-null (KO) mice treated with high-fat diet (HFD) were used to explore the effect of PPARα and lipid diet on the circadian rhythm. WT, KO, and PPARα-humanized (hPPARα) mice were treated with PPARα agonist fenofibrate to reveal the hPPARα dependence of circadian locomotor output cycles kaput (CLOCK) down-regulation. The mouse model and hepatocyte experiments were designed to verify the action of PPARα in down-regulating CLOCK and lipid accumulation in vivo and in vitro. Strongest NAFLD developed in mice fed 45%HFD, and it was inhibited in WT mice. The activity rhythm of WT mice was found to be different from that of the KO mice on normal diet and HFD. The core circadian factor CLOCK was down-regulated by HFD in both WT and KO mice in the liver, not in the hypothalamus. More interestingly, hepatic CLOCK was down-regulated by basal PPARα and activated PPARα in dose dependence of fenofibrate. Accordingly, CLOCK down-regulation dependent of PPARα activity was involved in inhibition of lipid metabolism in hepatocytes. Down-regulation of hepatic CLOCK by basal PPARα contributes to tolerance against development of NAFLD. Inhibition of CLOCK by activated PPARα is involved in inhibition of NAFLD by PPARα agonists. KEY MESSAGES: • PPARα inhibited NAFLD development induced by HFD. • PPARα mediated modifications of circadian rhythm and the hepatic circadian factor CLOCK in NAFLD models. • Down-regulation of hepatic CLOCK by basal PPARα contributed to tolerance against development of NAFLD. • Inhibition of CLOCK by activated PPARα was involved in therapeutic actions against fatty liver diseases by PPARα agonists.

BackgroundWe established a novel diethylnitrosamine (DEN) -induced mouse model that reflected the progression of cholangiocarcinoma (CCA) from atypical cystic hyperplasia.MethodsBALB/c mice were administered DEN by oral gavage. Cells isolated from livers were analyzed for expression of CSNK2A1, MAX and MAX-interacting proteins. Human CCA cell lines (MzChA-1, HuCCT1), normal human cholangiocyte (H69), human hepatic stellate cells (LX-2), macrophages (RAW 264.7), and primary hepatic cells were used for cellular and molecular biology assays.ResultsExpression of MAX, CSNK2A1, C-MYC, β-catenin, HMGB1, and IL-6 was upregulated in hepatic cells from CCA liver tissue. The half-life of MAX is higher in CCA cells, and this favors their proliferation. Overexpression of MAX increased growth, migration, and invasion of MzChA-1, whereas silencing of MAX had the opposite effect. MAX positively regulated IL-6 and HMGB1 through paracrine signaling in HepG2, LX2, and RAW cells and autocrine signaling in MzChA-1 cells. CSNK2A1-mediated MAX phosphorylation shifts MAX-MAX homodimer to C-MYC-MAX and β-catenin-MAX heterodimers and increases the HMGB1 and IL-6 promoter activities. Increase of MAX phosphorylation promotes cell proliferation, migration, invasion, and cholangiocarcinogenesis. The casein kinase 2 inhibitor CX-4945 induces cell cycle arrest and inhibits cell proliferation, migration, invasion, and carcinogenesis in MzChA-1 cells through the downregulation of CSNK2A1, MAX, and MAX-interaction proteins.ConclusionC-MYC-MAX and β-catenin-MAX binding to E-box site or β-catenin-MAX bound to TCFs/LEF1 enhanced HMGB1 or IL-6 promoter activities, respectively. IL-6 and HMGB1 secreted by hepatocytes, HSCs, and KCs exert paracrine effects on cholangiocytes to promote cell growth, migration, and invasion and lead to the progression of cholangiocarcinogenesis. CX-4945 provides perspectives on therapeutic strategies to attenuate progression from atypical cystic hyperplasia to cholangiocarcinogenesis.

Background The genetic locus responsible for duck body size has been fully explained before, but the growth trait-related genetic basis is still waiting to be explored. For example, the genetic site related to growth rate, an important economic trait affecting marketing weight and feeding cost, is still unclear. Here, we performed genome wide association study (GWAS) to identify growth rate-associated genes and mutations. Result In the current study, the body weight data of 358 ducks were recorded every 10 days from hatching to 120 days of age. According to the growth curve, we evaluated the relative and absolute growth rates (RGR and AGR) of 5 stages during the early rapid growth period. GWAS results for RGRs identified 31 significant SNPs on autosomes, and these SNPs were annotated by 24 protein-coding genes. Fourteen autosomal SNPs were significantly associated with AGRs. In addition, 4 shared significant SNPs were identified as having an association with both AGR and RGR, which were Chr2: 11483045 C>T, Chr2: 13750217 G>A, Chr2: 42508231 G>A and Chr2: 43644612 C>T. Among them, Chr2: 11483045 C>T, Chr2: 42508231 G>A, and Chr2: 43644612 C>T were annotated by ASAP1, LYN and CABYR, respectively. ASAP1 and LYN have already been proven to play roles in the growth and development of other species. In addition, we genotyped every duck using the most significant SNP (Chr2: 42508231 G>A) and compared the growth rate difference among each genotype population. The results showed that the growth rates of individuals carrying the Chr2: 42508231 A allele were significantly lower than those without this allele. Moreover, the results of the Mendelian randomization (MR) analysis supported the idea that the growth rate and birth weight had a causal effect on the adult body weight, with the growth rate having a greater effect size. Conclusion In this study, 41 SNPs significantly related to growth rate were identified. In addition, we considered that the ASAP1 and LYN genes are essential candidate genes affecting the duck growth rate. The growth rate also showed the potential to be used as a reliable predictor of adult weight, providing a theoretical reference for preselection.

Background: Patients diagnosed with influenza and upper respiratory tract infections (URTIs) have similar clinical manifestations and biochemical indices and a low detection rate of viral pathogens, mixed infection with diverse respiratory viruses, and targeted antiviral treatment difficulty in the early stage. According to the treatment strategy of “homotherapy for heteropathy” in traditional Chinese medicine (TCM), different diseases with the same clinical symptoms can be treated with the same medicines. Qingfei Dayuan granules (QFDY), a type of Chinese herbal preparation included in the TCM Diagnosis and Treatment Protocol for COVID-19 of Hubei Province issued by the Health Commission of Hubei Province in 2021, are recommended for patients suffering from COVID-19 with symptoms of fever, cough, and fatigue, among others. Additionally, recent studies have shown that QFDY effectively alleviates fever, cough, and other clinical symptoms in patients with influenza and URTIs.Materials and methods: The study was designed as a multicenter, randomized, double-blind, placebo-controlled clinical trial for treatment for influenza and URTIs manifested by pulmonary heat-toxin syndrome (PHTS) with QFDY. A total of 220 eligible patients were enrolled from eight first-class hospitals in five cities of Hubei Province in China and randomly assigned to receive either 15 g of QFDY or a placebo three times a day for 5 days. The primary outcome was the complete fever relief time. Secondary outcomes included efficacy evaluation of TCM syndromes, scores of TCM syndromes, cure rate of each single symptom, incidence of comorbidities and progression to severe conditions, combined medications, and laboratory tests. Safety evaluations mainly involved adverse events (AEs) and changes in vital signs during the study.Results: Compared with the placebo group, the complete fever relief time was shorter in the QFDY group, 24 h (12.0, 48.0) in the full analysis set (FAS) and 24 h (12.0, 49.5) in the per-protocol set (PPS) (p ≤ 0.001). After a 3-day treatment, the clinical recovery rate (22.3% in the FAS and 21.6% in the PPS) and cure rate of cough (38.6% in the FAS and 37.9% in the PPS), a stuffy and running nose, and sneezing (60.0% in the FAS and 59.5% in the PPS) in the QFDY group were higher than those in the placebo group (p < 0.05). The number of patients taking antibiotics for more than 24 h in the placebo group (nine cases) was significantly higher than that in the QFDY group (one case) (p < 0.05). There were no significant differences between the two groups in terms of scores of TCM syndromes, incidence of comorbidities or progression to severe conditions, combined use of acetaminophen tablets or phlegm-resolving medicines, and laboratory tests (p > 0.05). Meanwhile, no significant difference was found in the incidence of AEs and vital signs between the two groups (p > 0.05).Conclusion: The trial showed that QFDY was an effective and safe treatment modality for influenza and URTIs manifested by PHTS because it shortened the complete fever relief time, accelerated clinical recovery, and alleviated symptoms such as cough, a stuffy and running nose, and sneezing during the course of treatment.Clinical trial registration:https://www.chictr.org.cn/showproj.aspx?proj=131702, identifier ChiCTR2100049695.

Enantioselective transformations of olefins are among the most important strategies for the asymmetric synthesis of organic compounds. Chemo-, diastereo-, and stereoselective control of reactions with internal acyclic alkenes for the construction of functionalized acyclic alkanes still remain a persistent challenge. Here, we report a palladium-catalyzed asymmetric regiodivergent Heck-type diarylation of internal acyclic alkenes. The 1,2-diarylation of two accessible acyclic alkenes, cinnamyl carbamates and enamides with diazonium salts and aromatic boronic acids, furnishes products containing vicinal stereogenic centers via the stereospecific formation of carbonyl coordination-assisted transient palladacycles. Moreover, the asymmetric migratory diarylation of enamides enables the formation of incontiguous stereocenters by an interrupted diastereoselective 1,3-chain-walking process. This protocol streamlines access to highly functionalized multisubstituted enantioenriched carbamates and amine derivatives which are embedded in the key biologically active motifs.

Flow visualization is essentially a tool to answer domain experts' questions about flow fields using rendered images. Static flow visualization approaches require domain experts to raise their questions to visualization experts, who develop specific techniques to extract and visualize the flow structures of interest. Interactive visualization approaches allow domain experts to ask the system directly through the visual analytic interface, which provides flexibility to support various tasks. However, in practice, the visual analytic interface may require extra learning effort, which often discourages domain experts and limits its usage in real-world scenarios. In this paper, we propose FlowNL, a novel interactive system with a natural language interface. FlowNL allows users to manipulate the flow visualization system using plain English, which greatly reduces the learning effort. We develop a natural language parser to interpret user intention and translate textual input into a declarative language. We design the declarative language as an intermediate layer between the natural language and the programming language specifically for flow visualization. The declarative language provides selection and composition rules to derive relatively complicated flow structures from primitive objects that encode various kinds of information about scalar fields, flow patterns, regions of interest, connectivities, etc. We demonstrate the effectiveness of FlowNL using multiple usage scenarios and an empirical evaluation.

Pd(ii)-Catalyzed highly enantioselective intermolecular oxidative 1,2-diarylation reaction of internal enamides with aryl boronic acids is reported.

Land managers are making concerted efforts to control the spread of invasive plants, a task that demands extensive ecosystem monitoring, for which unoccupied aerial vehicles (UAVs or drones) are becoming increasingly popular. The high spatial resolution of unoccupied aerial vehicles imagery may positively or negatively affect plant species differentiation, as reflectance spectra of pixels may be highly variable when finely resolved. We assessed this impact on detection of invasive plant species Ailanthus altissima (tree of heaven) and Elaeagnus umbellata (autumn olive) using fine-resolution images collected in northwestern Virginia in June 2020 by a unoccupied aerial vehicles with a Headwall Hyperspec visible and near-infrared hyperspectral imager. Though E. umbellata had greater intraspecific variability relative to interspecific variability over more wavelengths than A. altissima, the classification accuracy was greater for E. umbellata (95%) than for A. altissima (66%). This suggests that spectral differences between species of interest and others are not necessarily obscured by intraspecific variability. Therefore, the use of unoccupied aerial vehicles-based spectroscopy for species identification may overcome reflectance variability in fine resolution imagery.

Objective: We aimed to explore a new method to reverse early relapse in patients with AML1-ETO–positive acute myeloid cell transplantation.Methods: A chidamide-based 3-drug combination regimen was used in our center to treat patients with AML1-ETO–positive AML post transplantation but negative flow cytometry results. A retrospective analysis was performed of the survival rate and possible influencing factors of patients with relapse treated with this regimen in our center from January 2018 to January 2022.Results: The overall response rate was 95.8% (23/24), and the median number of treatment courses was 4 (range, 3–12 courses). The total molecular complete response (MCR) was 79.1% (19/24) after all treatments, and the molecular complete response was 37.5% (9/24) after one cycle of treatment but reached 58.3% (14/24) after four cycles; overall, the proportion of MCR increased gradually with the increase in treatment cycles. The projected 5-year overall survival rate was 73.9%. The projected 5-year leukemia-free survival rate was 64.8%, and the projected 1-year cumulative relapse rate was 35.5%. The incidence of grade II–IV graft-versus-host diseases (GVHD) was 29.2% (7/24), and that of grade III–IV GVHD was 20.8% (5/24), which could be effectively controlled by glucocorticoid therapy combined with calcineurin inhibitors The total incidence of chronic GVHD was 29.2% (7/24), and all cases were localized chronic GVHD. The total infection rate was 33.3% (8/24), mainly involving bacterial and fungal infections, and the incidence of life-threatening infections was 4.17% (1/24). The treatment-related mortality rate was 0%; and the total mortality rate was 20.8% (5/24). Nausea and vomiting, thrombocytopenia, and neutropenia were common adverse reactions, all of which were Common Terminology Criteria for Adverse Events grade 2–3 events and reversible after drug withdrawal. In terms of immunity, Th1 cell counts gradually increased, Th17 cell counts gradually decreased, and the Th1/Th17 ratio gradually increased after treatment. The CD8+ T lymphocyte count increased gradually, while the CD4+ T lymphocyte count did not change significantly.Conclusion: Our chidamide-based 3-drug combination regimen led to a high remission rate and tolerable adverse reactions in patients with AML1-ETO–positive post-transplant relapse, and most patients can achieve long-term survival with this regimen.

Myelopoiesis is the process in which the mature myeloid cells, including monocytes/macrophages and granulocytes, are developed. Irregular myelopoiesis may cause and deteriorate a variety of hematopoietic malignancies such as leukemia. Myeloid cells and their precursors are difficult to capture in circulation, let alone observe them in real time. For decades, researchers had to face these difficulties, particularly in in-vivo studies. As a unique animal model, zebrafish possesses numerous advantages like body transparency and convenient genetic manipulation, which is very suitable in myelopoiesis research. Here we review current knowledge on the origin and regulation of myeloid development and how zebrafish models were applied in these studies.

Synthesising a text-to-image model of high-quality images by guiding the generative model through the Text description is an innovative and challenging task. In recent years, AttnGAN based on the Attention mechanism to guide GAN training has been proposed, SD-GAN, which adopts a self-distillation technique to improve the performance of the generator and the quality of image generation, and Stack-GAN++, which gradually improves the details and quality of the image by stacking multiple generators and discriminators. However, this series of improvements to GAN all have redundancy to a certain extent, which affects the generation performance and complexity to a certain extent. We use the popular simple and effective idea (1) to remove redundancy structure and improve the backbone network of AttnGAN. (2) to integrate and reconstruct multiple losses of DAMSM. Our improvements have significantly improved the model size and training efficiency while ensuring that the model's performance is unchanged and finally proposed our SEAttnGAN. Code is avalilable at https://github.com/jmyissb/SEAttnGAN., Comment: 12 pages, 3 figures

LLMs now exhibit human-like skills in various fields, leading to worries about misuse. Thus, detecting generated text is crucial. However, passive detection methods are stuck in domain specificity and limited adversarial robustness. To achieve reliable detection, a watermark-based method was proposed for white-box LLMs, allowing them to embed watermarks during text generation. The method involves randomly dividing the model vocabulary to obtain a special list and adjusting the probability distribution to promote the selection of words in the list. A detection algorithm aware of the list can identify the watermarked text. However, this method is not applicable in many real-world scenarios where only black-box language models are available. For instance, third-parties that develop API-based vertical applications cannot watermark text themselves because API providers only supply generated text and withhold probability distributions to shield their commercial interests. To allow third-parties to autonomously inject watermarks into generated text, we develop a watermarking framework for black-box language model usage scenarios. Specifically, we first define a binary encoding function to compute a random binary encoding corresponding to a word. The encodings computed for non-watermarked text conform to a Bernoulli distribution, wherein the probability of a word representing bit-1 being approximately 0.5. To inject a watermark, we alter the distribution by selectively replacing words representing bit-0 with context-based synonyms that represent bit-1. A statistical test is then used to identify the watermark. Experiments demonstrate the effectiveness of our method on both Chinese and English datasets. Furthermore, results under re-translation, polishing, word deletion, and synonym substitution attacks reveal that it is arduous to remove the watermark without compromising the original semantics., Comment: Code will be available at https://github.com/Kiode/Text_Watermark_Language_Models

Objective: To develop a natural language processing system that solves both clinical concept extraction and relation extraction in a unified prompt-based machine reading comprehension (MRC) architecture with good generalizability for cross-institution applications. Methods: We formulate both clinical concept extraction and relation extraction using a unified prompt-based MRC architecture and explore state-of-the-art transformer models. We compare our MRC models with existing deep learning models for concept extraction and end-to-end relation extraction using two benchmark datasets developed by the 2018 National NLP Clinical Challenges (n2c2) challenge (medications and adverse drug events) and the 2022 n2c2 challenge (relations of social determinants of health [SDoH]). We also evaluate the transfer learning ability of the proposed MRC models in a cross-institution setting. We perform error analyses and examine how different prompting strategies affect the performance of MRC models. Results and Conclusion: The proposed MRC models achieve state-of-the-art performance for clinical concept and relation extraction on the two benchmark datasets, outperforming previous non-MRC transformer models. GatorTron-MRC achieves the best strict and lenient F1-scores for concept extraction, outperforming previous deep learning models on the two datasets by 1%~3% and 0.7%~1.3%, respectively. For end-to-end relation extraction, GatorTron-MRC and BERT-MIMIC-MRC achieve the best F1-scores, outperforming previous deep learning models by 0.9%~2.4% and 10%-11%, respectively. For cross-institution evaluation, GatorTron-MRC outperforms traditional GatorTron by 6.4% and 16% for the two datasets, respectively. The proposed method is better at handling nested/overlapped concepts, extracting relations, and has good portability for cross-institute applications.

Introduction: This year is the year of the soccer World Cup. With the adult team unable to participate in the World Cup, society's attention has turned to college soccer. However, as a highly aggressive sport, soccer will inevitably cause various sports injuries. Objective: Investigate the causes and characteristics of sports injuries of young school soccer players in some areas of China, and propose measures to prevent and control sports injuries. Methods: A total of 1024 adolescents aged 6 to 17 years were research volunteers; the causes and characteristics of sports injuries of these young college soccer players were investigated through field investigation, questionnaire survey, expert interview, and mathematical analysis. Results: The results of the survey show that 73.2% (750 people) of the respondents have suffered sports injuries, among which the common injuries in elementary school (6-12 years old) are knee and upper limb joints, and the common injuries in middle school (12-17 years old) are mainly ankle and knee joints, with the same characteristics as adult players. The degree of injury in different segments is the same, with mild injuries being the most common, followed by moderate and severe. As the learning period increased, the mild injuries decreased significantly, while the moderate and severe injuries showed an increasing trend. Most injuries occurred in the summer, with the injury rate during training significantly higher than during competition. The causes of injuries are different in different age groups. Conclusion: Young school soccer players are prone to sports injuries in the sporting process, and specific preventive measures are needed to prevent these injuries from causing adverse effects on young players. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Reconfigurable intelligent surfaces (RISs) have drawn much attention recently for their appealing advantages in shaping wireless channels to improve the spectral and energy efficiencies of wireless communications. However, conventional fully-passive RISs generally suffer from the so-called ``multiplicative fading'' effect which thereby limits RISs' practicability and manufacturability. In this paper, a novel architecture of ``Reconfigurable Distributed Antennas and Reflecting Surfaces (RDARS)'' is first proposed to overcome this limitation from the ``multiplicative fading'' effect. Specifically, unlike existing active RIS variants, RDARS inherits the low-cost and low-energy-consumption benefits of fully-passive RISs by default configuring all the elements as passive to perform the reflection mode. On the other hand, based on the design of the additional direct-through state, any element of the RDARS can be dynamically programmed to connect with the base station (BS) via fibers and perform the connected mode as remote distributed antennas of the BS to receive signals. Consequently, a controllable trade-off between the reflection gain and the distribution gain can be achieved via RDARS at the BS. To unveil the system behavior of the RDARS-aided system, we analyze the received signal-to-noise ratio (SNR) under maximum ratio combining (MRC) at BS. Closed-form outage probability and ergodic achievable rate are also provided and are verified through extensive simulations. To demonstrate the superiority of the proposed RDARS, experiments are carried out using a prototype of RDARS with a total number of 256 elements which revealed extra 76% throughput improvement could be achieved by deploying RDARS with only three elements performing connected mode. This thus confirms the effectiveness of the proposed RDARS and envisions it as a promising candidate for future 6G wireless systems., Comment: 30 pages, 12 figures. This paper has been submitted to IEEE journal for possible publication

In this work, we study sensing-aided uplink transmission in an integrated sensing and communication (ISAC) vehicular network with the use of orthogonal time frequency space (OTFS) modulation. To exploit sensing parameters for improving uplink communications, the parameters must be first associated with the transmitters, which is a challenging task. We propose a scheme that jointly conducts parameter association, channel estimation and signal detection by formulating it as a constrained bilinear recovery problem. Then we develop a message passing algorithm to solve the problem, leveraging the bilinear unitary approximate message passing (Bi-UAMP) algorithm. Numerical results validate the proposed scheme, which show that relevant performance bounds can be closely approached.

Supplemental material, sj-docx-1-tam-10.1177_17588359231169975 for Rationale and value of consolidative cranial local therapy in EGFR-mutant non-small cell lung cancer patients with baseline brain metastasis treated with first-line EGFR-TKIs by Ya Zeng, Xi Su, Yang Zhao, Yue Zhou, Tiantian Guo, Xiao Chu, Li Chu, Xi Yang, Jianjiao Ni and Zhengfei Zhu in Therapeutic Advances in Medical Oncology

Metacognitive skills have been commonly associated with preparation for future learning in deductive domains. Many researchers have regarded strategy- and time-awareness as two metacognitive skills that address how and when to use a problem-solving strategy, respectively. It was shown that students who are both strategy-and time-aware (StrTime) outperformed their nonStrTime peers across deductive domains. In this work, students were trained on a logic tutor that supports a default forward-chaining (FC) and a backward-chaining (BC) strategy. We investigated the impact of mixing BC with FC on teaching strategy- and time-awareness for nonStrTime students. During the logic instruction, the experimental students (Exp) were provided with two BC worked examples and some problems in BC to practice how and when to use BC. Meanwhile, their control (Ctrl) and StrTime peers received no such intervention. Six weeks later, all students went through a probability tutor that only supports BC to evaluate whether the acquired metacognitive skills are transferred from logic. Our results show that on both tutors, Exp outperformed Ctrl and caught up with StrTime., Comment: arXiv admin note: text overlap with arXiv:2303.11965

Large Language Models (LLMs) can generate texts that carry the risk of various misuses, including plagiarism, planting fake reviews on e-commerce platforms, or creating fake social media postings that can sway election results. Detecting whether a text is machine-generated has thus become increasingly important. While machine-learning-based detection strategies exhibit superior performance, they often lack generalizability, limiting their practicality. In this work, we introduce GPT Paternity Test (GPT-Pat), which reliably detects machine-generated text across varied datasets. Given a text under scrutiny, we leverage ChatGPT to generate a corresponding question and provide a re-answer to the question. By comparing the similarity between the original text and the generated re-answered text, it can be determined whether the text is machine-generated. GPT-Pat consists of a Siamese network to compute the similarity between the original text and the generated re-answered text and a binary classifier. Our method achieved an average accuracy of 94.57% on four generalization test sets, surpassing the state-of-the-art RoBERTa-based method by 12.34%. The accuracy drop of our method is only about half of that of the RoBERTa-based method when it is attacked by re-translation and polishing.

We report Tensorial tomographic Fourier Ptychography (ToFu), a new non-scanning label-free tomographic microscopy method for simultaneous imaging of quantitative phase and anisotropic specimen information in 3D. Built upon Fourier Ptychography, a quantitative phase imaging technique, ToFu additionally highlights the vectorial nature of light. The imaging setup consists of a standard microscope equipped with an LED matrix, a polarization generator, and a polarization-sensitive camera. Permittivity tensors of anisotropic samples are computationally recovered from polarized intensity measurements across three dimensions. We demonstrate ToFu's efficiency through volumetric reconstructions of refractive index, birefringence, and orientation for various validation samples, as well as tissue samples from muscle fibers and diseased heart tissue. Our reconstructions of muscle fibers resolve their 3D fine-filament structure and yield consistent morphological measurements compared to gold-standard second harmonic generation scanning confocal microscope images found in the literature. Additionally, we demonstrate reconstructions of a heart tissue sample that carries important polarization information for detecting cardiac amyloidosis.

To compare the research hotspots of infections with the Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 2019 (COVID-19) pandemic and to identify future research trends.Studies about Delta and Omicron variant infections published over the last 3 years were retrieved from the Web of Science (WoS) database. A comparative bibliometric analysis was conducted through machine learning and visualization tools, including VOSviewer, Bibliographic Item Co-Occurrence Matrix Builder, and Graphical Clustering Toolkit. Research hotspots and trends in the field were analyzed, and the contributions and collaborations of countries, institutions, and authors were documented. A cross-sectional analysis of the relevant studies registered at ClinicalTrials.gov was also performed to clarify the direction of future research.A total of 1,787 articles distributed in 107 countries and 374 publications from 77 countries focused on the Delta and Omicron variants were included in our bibliometric analysis. The top five productive countries in both variants were the USA, China, the UK, India, and Germany. In 5,999 and 1,107 keywords identified from articles on the Delta and Omicron, the top two frequent keywords were the same: "COVID-19" (occurrence: 713, total link strength: 1,525 in Delta; occurrence: 137, total link strength: 354 in Omicron), followed by "SARS-CoV-2" (occurrence: 553, total link strength: 1,478 in Delta; occurrences 132, total link strength: 395 in Omicron). Five theme clusters from articles on Delta variant were identified: transmission, molecular structure, activation mode, epidemiology, and co-infection. While other three theme clusters were recognized for the Omicron variant: vaccine, human immune response, and infection control. Meanwhile, 21 interventional studies had been registered up to April 2022, most of which aimed to evaluate the immunogenicity and safety of different kinds of vaccines in various populations.Publications and clinical trials related to COVID-19 increased annually. As the first comparative bibliometric analysis for Delta and Omicron variants, we noticed that the relevant research trends have shifted from vaccine development to infection control and management of complications. The ongoing clinical studies will verify the safety and efficacy of promising drugs.

PurposeTo investigate the effectiveness and safety of gonadotropin-releasing hormone analogue (GnRHa) in combination with recombinant human growth hormone (rhGH) in girls with central precocious puberty (CPP).MethodsClinical data of 80 girls diagnosed with idiopathic central precocious puberty (ICPP) between January 2017 and June 2021 were retrospectively analyzed. Treatment strategy involved GnRHa alone (group A: n=34) and GnRHa+rhGH (group B: n=46). Children’s heights (Ht), weights (Wt) and sex hormone levels were measured every 3 months after treatment and bone age (BA) every six months. Heights, growth velocity (GV), predicted adult height (PAH), weights, body mass index (BMI), sex hormone levels and bone age were compared between the two groups.ResultsChildren in group B showed greater height gain at the 12th, 24th and 30th months after treatment (p0.05). Levels of LH and FSH were lower in both groups after treatment with no statistical differences between groups (p>0.05). The gap between bone age and chronological age gradually decreased in both groups and no abnormal progression of bone age or other adverse side effects occurred.ConclusionsThe combination of GnRHa with rhGH produced better height gains than GnRHa alone for patients with CPP. The gonadal axis was suppressed and progression of bone age delayed with good safety and efficacy.

Endothelial-mesenchymal transition (EndMT) is a differentiation process in which endothelial cells lose their own characteristics and acquire mesenchymal-like characteristics, which contributes to the formation and development of atherosclerotic plaques. Until now, there is still a lack of effective measures to treat atherosclerosis (AS), so there is an urgent need to understand the underlying mechanisms of AS. In addition, although various studies have shown that EndMT is involved in the pathological stages of cardiovascular diseases, such as myocardial fibrosis, myocardial hypertrophy, and hypertension, the specific molecular mechanisms driving EndMT are still in the exploratory stage. In this review, we review the role of histone modifications (methylation, demethylation and acetylation, deacetylation) on EndMT in cardiovascular disease, aiming to target histone-modifying enzymes to guide cardiovascular disease therapy.

1. High stocking densities can lead to animal stress responses and lead to changes in bird behaviour, egg production and the fertility of laying birds. The oviduct plays a crucial role during the process of laying eggs. Therefore, it is essential to know how high stocking density affects oviduct function.2. In this study, a total of 2,115 differentially expressed genes (DEGs) were identified in duck oviduct tissues between different stocking density groups. These genes are mainly enriched in membrane components, calcium ion binding, cytokine-cytokine receptor interaction and focal adhesion. These pathways were closely related to the formation of eggs. This indicated that secretion and material transport functions of the oviduct are affected under high-density stocking. Further analysis showed that a total of 408 genes related to the transportation process were expressed in the oviduct, of which 96 genes were differentially expressed (LogFC≥1, P 0.05). Forty-two of these DEGs belonged to the solute carrier family. The data showed that the expression of 31 transcripts was different between the two density groups. Expression of

Birth weight (BW) and days to 100 kg (D100) are important economic traits that are both affected by polygenes. However, the genetic architecture of these quantitative traits is still elusive. Genotyping-by-sequencing (GBS) data containing a large number of single nucleotide polymorphisms (SNPs) have become a powerful tool in genomic analysis. To better understand their complex genetic structure, a total of 600 Yorkshire pigs were sequenced using GBS technology. After quality control, 279 787 SNPs were generated for subsequent genome-wide association study (GWAS). A total of 30 genome-wide SNPs (P

IntroductionIdentifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventive cardiology. We developed machine learning (ML) algorithms and investigated their performance in predicting patients’ current CVD risk (coronary heart disease and stroke in this study).Materials and methodsWe compared traditional logistic regression (LR) with five ML algorithms LR with Elastic-Net, Random Forest (RF), XGBoost (XGB), Support Vector Machine, Deep Learning, and an Ensemble model averaging predictions from RF, XGB, and Deep Learning for CVD risk prediction using pre-existing patient-level data from a multi-center, cross-sectional study (the Microalbuminuria Screening in Hypertensive Patients Project initiated by the China International Exchange and Promotive Association for Medical and Healthcare) that enrolled 143,043 patients with hypertension from 600 tertiary, secondary, or community hospitals. Each of the five ML algorithms incorporated 18 variables, such as demographics, examinations, comorbidities, and treatment regimens, and were trained and evaluated using 5-fold cross-validation. Predictive accuracy was assessed by the area under the receiver operating curve (AUROC).ResultsPatients’ mean age was 62 ± 12 years and 57% were men. Advanced ML algorithms outperformed the traditional LR model. Particularly, the Ensemble model had superior discrimination with an AUROC of 0.760 than LR (AUC = 0.737) and other tested models.ConclusionWe establishes an Ensemble model that shows better performance in predicting patients’ current CVD risk using routine information compared to the traditional LR model. ML can help physicians design follow-up plans with more accurate results, offering new possibilities for short-term risk prediction and early detection. Further, ML models can be trained with longitudinal data and used to predict long-term CVD risks, thereby informing CVD prevention.

BackgroundDrug-resistance is a significant clinical issue in persons with epilepsy. In the past few years, many studies have been published investigating the management of drug-resistant epilepsy (DRE); however, no systematic and quantitative evaluation of this research has been performed. Therefore, a bibliometric analysis was conducted to demonstrate the current status of DRE research and to reflect the trends and hotspots within the field.MethodsWe retrieved publications on DRE published between 2011 and 2021 from the Science Citation Index Expanded of the Web of Science Core Collection. All articles related to DRE were included in this study. VOSviewer, R software, and CiteSpace were used to perform bibliometric research.ResultsA total of 3,088 original articles were included in this study. The number of publications on DRE has continued to increase over the past 11 years. The USA published the most papers with the highest number of citations and H-index. The National Institutes of Health and the University of Toronto were the most prolific funding agency and affiliation, respectively. Epilepsy & Behavior and Epilepsia ranked first as the most prolific and co-cited journals, respectively. The keywords “cannabidiol”, “neuromodulation”, “seeg” and “perampanel” revealed recent research hotspots. The top 100 most cited papers were classified into eight main topics, of which pharmacotherapy, disease mechanisms/pathophysiology, and neuromodulation were the three most important topics.ConclusionsThis analysis of bibliometric data demonstrated that DRE has always been a topical area of research. The mechanisms of epilepsy and therapies have been the focus of DRE research, and innovative antiseizure medications and surgical approaches are fast-developing research trends.

Unique scientific instruments designed and operated by large global collaborations are expected to produce Exabyte-scale data volumes per year by 2030. These collaborations depend on globally distributed storage and compute to turn raw data into science. While all of these infrastructures have batch scheduling capabilities to share compute, Research and Education networks lack those capabilities. There is thus uncontrolled competition for bandwidth between and within collaborations. As a result, data "hogs" disk space at processing facilities for much longer than it takes to process, leading to vastly over-provisioned storage infrastructures. Integrated co-scheduling of networks as part of high-level managed workflows might reduce these storage needs by more than an order of magnitude. This paper describes such a solution, demonstrates its functionality in the context of the Large Hadron Collider (LHC) at CERN, and presents the next-steps towards its use in production., Submitted to the proceedings of the XLOOP workshop held in conjunction with Supercomputing 22

Gansu province is located at the intersection of the three plateaus(Qinghai-Tibet Plateau, Inner Mongolia Plateau, and Loess Plateau) and the three river basins(Yellow River Basin, Yangtze River Basin, and inland river basin). The complex eco-environment and climate conditions here have created rich and diverse vegetation. Therefore, it is of great significance to study the spatial distribution characteristics of rare and endangered medicinal plant resources in Gansu province for formulating reasonable protection po-licies and promoting the development of medicinal plant industry. The data of rare and endangered medicinal plant resources in 87 counties of Gansu province were collected from results of the fourth general survey. The spatial distribution and the high-or low-value gathering area of rare and endangered medicinal plant resources in Gansu province were analyzed by geostatistical methods such as exploratory spatial data analysis, trend surface analysis, and Anselin Local Moran's I. The eco-environment characteristics of the high-or low-value gathering area were analyzed with the data of vegetation type, soil texture classification, annual mean temperature, annual mean precipitation, and elevation. Furthermore, the relationships of the spatial distribution and diversity with the geographical environment of rare and endangered medicinal plants in Gansu province were analyzed to provide support for the restoration and protection policy making of these plant resources.

Objective: To develop a natural language processing (NLP) system to extract medications and contextual information that help understand drug changes. This project is part of the 2022 n2c2 challenge. Materials and methods: We developed NLP systems for medication mention extraction, event classification (indicating medication changes discussed or not), and context classification to classify medication changes context into 5 orthogonal dimensions related to drug changes. We explored 6 state-of-the-art pretrained transformer models for the three subtasks, including GatorTron, a large language model pretrained using >90 billion words of text (including >80 billion words from >290 million clinical notes identified at the University of Florida Health). We evaluated our NLP systems using annotated data and evaluation scripts provided by the 2022 n2c2 organizers. Results:Our GatorTron models achieved the best F1-scores of 0.9828 for medication extraction (ranked 3rd), 0.9379 for event classification (ranked 2nd), and the best micro-average accuracy of 0.9126 for context classification. GatorTron outperformed existing transformer models pretrained using smaller general English text and clinical text corpora, indicating the advantage of large language models. Conclusion: This study demonstrated the advantage of using large transformer models for contextual medication information extraction from clinical narratives.

Speckle-type Poz protein (SPOP), an E3 ubiquitin ligase adaptor, is the most frequently mutated gene in prostate cancer. The SPOP-mutated subtype of prostate cancer shows high genomic instability, but the underlying mechanisms causing this phenotype are still largely unknown. Here, we report that upon DNA damage, SPOP is phosphorylated at Ser119 by the ATM serine/threonine kinase, which potentiates the binding of SPOP to homeodomain-interacting protein kinase 2 (HIPK2), resulting in a nondegradative ubiquitination of HIPK2. This modification subsequently increases the phosphorylation activity of HIPK2 toward HP1γ, and then promotes the dissociation of HP1γ from trimethylated (Lys9) histone H3 (H3K9me3) to initiate DNA damage repair. Moreover, the effect of SPOP on the HIPK2-HP1γ axis is abrogated by prostate cancer-associated SPOP mutations. Our findings provide new insights into the molecular mechanism of SPOP mutations-driven genomic instability in prostate cancer.

Secondary rewards acquire enhanced incentive motivation via increasing anticipatory activity of the lateral orbitofrontal cortex

Based on the survey data on animal husbandry from 1,689 households in semi-agricultural and semi-pastoral counties in Inner Mongolia, this paper applied the “buffer capacity–organizational capacity-learning capacity” framework to analyze the current livelihood resilience of farmers and herdsmen, as well as the impact of ecological vulnerability and disaster shocks on this resilience. The results show that, first, due to the vicious ecological environment and natural disasters, livelihood resilience among farmers and herdsmen is generally low in the region, but that of herdsmen is significantly higher than that of farmers. There are clear differences between the dimensions of livelihood resilience in different households. Second, natural disasters, of which drought is the most obvious, have a great impact on livelihood resilience. However, there is a significant positive correlation between ecological vulnerability and the livelihood resilience of farmers and herdsmen; thus, we should reflect on the past development model of the region. Third, In addition to the impact of ecological vulnerability and disaster shocks, per capita income, human capital, policy support, social networks, and information access are the main obstacles to livelihood resilience. Combined with these research findings, this paper seeks to improve livelihood resilience through the strategies of avoiding disaster risk, changing the development mode, reducing path dependence, and identifying obstacles.

Introduction: There are increasing reports of a link between chronic constipation and allergies in children. However, similar epidemiological evidence is limited in the general adult population. Therefore, in this study, we attempted to assess the association between chronic constipation and allergy in adults aged ≥20 years in the USA. Methods: We established a logistic regression model to test the relationship between chronic constipation and 19 specific immunoglobulin E (sIgE) types in adults aged ≥20 years using large-sample data from the National Health and Nutrition Examination Survey database (2005–2006). The weekly defecation times of the allergic and non-allergic groups were compared using the t test. Results: We found that sIgE-sensitized participants had a 0.723 lower risk of chronic constipation than the general population (95% confidence interval (CI) = 0.566–0.923). There was a negative association between chronic constipation and sensitizations to peanut (odds ratio (OR) = 0.579, 95% CI = 0.381–0.935), egg (OR = 0.335, 95% CI = 0.134–0.838), dog (OR = 0.723, 95% CI = 0.522–0.965), and cockroach (OR = 0.540, 95% CI = 0.373–0.784). In addition, the frequency of defecation per week increased significantly in people allergic to peanuts and cockroaches (p < 0.05). Discussion/Conclusion: The results of this study demonstrate an inverse relationship between sIgE sensitization and chronic constipation in adults. However, the specific association mechanism needs to be further studied.

The Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider (LHC) distributes its data by leveraging a diverse array of National Research and Education Networks (NRENs), which CMS is forced to treat as an opaque resource. Consequently, CMS sees highly variable performance that already poses a challenge for operators coordinating the movement of petabytes around the globe. This kind of unpredictability, however, threatens CMS with a logistical nightmare as it barrels towards the High Luminosity LHC (HL-LHC) era in 2030, which is expected to produce roughly 0.5 exabytes of data per year. This paper explores one potential solution to this issue: software-defined networking (SDN). In particular, the prototypical interoperation of SENSE, an SDN product developed by the Energy Sciences Network, with Rucio, the data management software used by the LHC, is outlined. In addition, this paper presents the current progress in bringing these technologies together.

Background Epidemiological evidence for the association of allergies with diabetes mellitus (DM) is limited. Objective To Investigate the association of allergic symptoms and allergens with DM by analyzing National Health and Nutrition Examination Survey (NHANES) data. Methods Data from 1687 subjects were screened from the 2005–2006 NHANES (n = 10348) data, and logistic regression models were built and stratified analysis was performed to describe the association of allergic symptoms and allergens with DM and the constraints in which they were associated. Results After adjusting for confounding factors, the stratified analysis found that the risk of allergic symptoms in DM patients increased by 1.847-fold, 1.646-fold, 3.859-fold, 2.862-fold, and 1.476-fold among the middle-aged, males, people with total household size of 3 or 4, and high blood pressure (HBP) patients, but decreased by 0.024-fold and 0.285-fold in people living alone or with normal weight. In females or when the total number of people in the household was 4, the risk of allergen sensitization in DM patients increased by 2.028-fold and 4.674-fold. Compared with people without DM, people with DM had a 1.585-fold increased risk of developing a D. Pteronyssinus allergy and a 0.372-fold lower risk of developing an oak allergy. Conclusions DM is a risk factor for allergic symptoms and allergen sensitization under certain conditions and increases the risk of D. Pteronyssinus allergy and reduces the risk of oak allergy.

Myelopoiesis is the process in which the mature myeloid cells, including monocytes/macrophages and granulocytes, are developed. Irregular myelopoiesis may cause and deteriorate a variety of hematopoietic malignancies such as leukemia. Myeloid cells and their precursors are difficult to capture in circulation, let alone observe them in real time. For decades, researchers had to face these difficulties, particularly in in-vivo studies. As a unique animal model, zebrafish possesses numerous advantages like body transparency and convenient genetic manipulation, which is very suitable in myelopoiesis research. Here we review current knowledge on the origin and regulation of myeloid development and how zebrafish models were applied in these studies.

PurposeThe aim of this study was to describe the treatment technique, outcomes, and complications of Schobinger stage IV head and neck arteriovenous malformations (HNAVMs) with associated high-output cardiac failure (HOCF) using ethanol and coils with the percutaneous suture technique.MethodsFrom January 2015 to December 2019, 19 patients who had HNAVMs with associated HOCF were treated first with a percutaneous suture of the remarkably dilated dominant drainage vein (RDDOV) and subsequent embolization with coils and ethanol. The percutaneous suture of RDDOV was preferred to be performed, followed by the deployment of coils and the injection of absolute ethanol via transarterial approach, direct puncture approach, or both of them. Treatment outcomes and complication rates were evaluated at follow-up.ResultsA total of 19 patients who experienced HNAVMs with HOCF received 19 percutaneous suture procedures and 84 embolization procedures with ethanol and coils. Complete or >90% shunt reduction of the AVM was achieved in 16 patients. Notably, 19 patients with New York Heart Association (NYHA) stage II improved to stage I, and the symptom of dyspnea disappeared after embolization. The symptoms of five patients with bleeding disappeared. All patients presented with cosmetic concerns; Four were cured, and eight had a clearly recognizable improvement. Of note, 19 (100%) patients presented with impairment of daily life, which was resolved. The minor complications were encountered and recovered by the self. No major complications occurred.ConclusionThis study provides evidence that ethanol and coil embolotherapy is effective and safe in treating HOCF caused by HNAVMs with acceptable complications in these cases. The percutaneous suture technique for RDDOV management can act as an adjunct for embolotherapy.