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Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is a rapidly progressing infectious disease with a high fatality rate caused by a novel bunyavirus (SFTSV). The role of lipids in viral infections is well-documented; however, the specific alterations in lipid metabolism during SFTSV infection remain elusive. This study aims to elucidate the lipid metabolic dysregulations in the early stages of SFTS patients. Methods This study prospectively collected peripheral blood sera from 11 critical SFTS patients, 37 mild SFTS patients, and 23 healthy controls during the early stages of infection for lipidomics analysis. A systematic bioinformatics analysis was conducted from three aspects integrating lipid differential expressions, lipid differential correlations, and lipid-clinical indices correlations to reveal the serum lipid metabolic dysregulation in SFTSV-infected individuals. Results Our findings reveal significant lipid metabolic dysregulation in SFTS patients. Specifically, compared to healthy controls, SFTS patients exhibited three distinct modes of lipid differential expression: increased levels of lipids including phosphatidylserine (PS), hexosylceramide (HexCer), and triglycerides (TG); decreased levels of lipids including lysophosphatidylcholine (LPC), acylcarnitine (AcCa), and cholesterol esters (ChE); and lipids showing “dual changes” including phosphatidylcholine (PC) and phosphatidylethanolamine (PE). Finally, based on lipid metabolic pathways and literature analysis, we systematically elucidated the potential mechanisms underlying lipid metabolic dysregulation in the early stage of SFTSV infection. Conclusions Our study presents the first global serum lipidome profile and reveals the lipid metabolic dysregulation patterns in the early stage of SFTSV infection. These findings provide a new basis for the diagnosis, treatment, and further investigation of the disease.

Forests have experienced unprecedented decline and mortality beyond their historical range in past decades, which is attributed to disturbances like drought, fire, insects and disease. Traditional disturbance detection methods that typically employ a time series perspective to identify discrete disturbance events within continuous tree growth signals and were mainly designed for gap-scale often fail to identify disturbances across populations. To more accurately identify growth suppression and release clusters based on the perspective of forest population dynamics, here we applied a novel method of detecting forest disturbances using a Gaussian mixture model with an expectation maximisation algorithm (DGE), to fit annual distributions of growth indicators, i.e., tree-ring index. We further compared our novel approach of DGE with five traditional methods based on two sets of real tree-ring data and simulated tree-ring data. The results show an improvement of accuracy (35.5 %–48.1 %), sensitivity (36.6 %–58.1 %), precision (21.2 %–51.5 %) and specificity (11.1 %–20.6 %) for the average of two real radial growth datasets and an improvement of accuracy (7.6 %–13.9 %), sensitivity (70 %), precision (100 %) and specificity (9.1 %–9.7 %) for the simulation radial growth dataset, indicating that our DGE approach performs much better than the traditional methods. This study contributes to an improved strategy and understanding for sustainable forest management in the context of climate warming, demonstrating that our DGE approach can be better applied to global forest disturbance detection under global change.

Regional budget assessments of methane (CH4) are critical for future climate and environmental management. CH4 emissions from rice cultivation (CH4-rice) constitute one of the most significant sources. However, previous studies mainly focus on historical emission estimates and lack consideration of future changes in CH4-rice under climate change or anthropogenic policy intervention, which hampers our understanding of long-term trends and the implementation of targeted emission reduction efforts. This study investigates the spatiotemporal variations of CH4-rice over the past two decades, using an integrated method to identify the major drivers and predict future emissions under climate change scenarios and policy perspectives. Results indicate that the CH4-rice emissions in China ranged between 6.21 and 6.57 Tg yr−1 over the past two decades, with a spatial distribution characterized by decreases in the south and increases in the north, associated with economic development, dietary shifts, technological advancements, and climate change. Factors such as the rate of straw added (RSA), fertilization, soil texture, temperature, and precipitation significantly influence CH4 emissions per unit rice production (CH4-urp), with RSA identified as the most significant tillage management factor, explaining 32 % of the variance. Lowering RSA to 8 % is beneficial for reducing CH4-urp. Scenario analysis indicates that under policies focusing on production or demand, CH4-rice is expected to increase by 0.3 % to 5.6 %, while adjusting RSA can reduce CH4-rice by 9.4 % to 10.0 %. Structural adjustments and regional cooperation serve as beneficial starting points for controlling and reducing CH4-rice in China, while optimizing industrial layouts contributes to regional development and CH4-rice control. Implementing policies related to maintaining field and crop yields can achieve a balance between rice supply and demand ahead of schedule. Dynamic adjustment of rice cultivation based on supply–demand balance can effectively reduce CH4-rice from excess rice production. By 2060, the reduction effect could reach 8.95 %–12.01 %. Introducing policy-driven tillage management measures as reference indicators facilitates the reduction of CH4-rice.

Abstract Background Head and neck squamous carcinoma (HNSCC) is known for its high aggressiveness and susceptibility to cervical lymph node metastasis, which greatly contributes to its poor prognosis. During tumorigenesis, many types of cancer cells acquire oncogenic super-enhancers (SEs) that drive the overexpression of oncogenes, thereby maintaining malignant progression. This study aimed to identify and validate the role of oncogenic SE-associated genes in the malignant progression of HNSCC. Methods We identified HNSCC cell-specific SE-associated genes through H3K27Ac ChIP-seq and overlapped them with HNSCC-associated genes obtained from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) datasets using weighted gene coexpression network analysis (WGCNA) to identify hub genes. The expression of IGF2BP2 and KLF7 in HNSCC was detected using clinical samples. To determine the biological role of IGF2BP2, we performed CCK-8, colony formation assay, Transwell migration assay, invasion assay, and orthotopic xenograft model experiments. Furthermore, we utilized a CRISPR/Cas9 gene-editing system, small-molecule inhibitors, ChIP-qPCR, and dual-luciferase reporter assays to investigate the molecular mechanisms of IGF2BP2 and its upstream transcription factors. Results Our study identified IGF2BP2 as a hub SE-associated gene that exhibited aberrant expression in HNSCC tissues. Increased expression of IGF2BP2 was observed to be linked with malignant progression and unfavorable prognosis in HNSCC patients. Both in vitro and in vivo experiments confirmed that IGF2BP2 promotes the tumorigenicity and metastasis of HNSCC by promoting cell proliferation, migration, and invasion. Mechanistically, the IGF2BP2-SE region displayed enrichment for H3K27Ac, BRD4, and MED1, which led to the inhibition of IGF2BP2 transcription and expression through deactivation of the SE-associated transcriptional program. Additionally, KLF7 was found to induce the transcription of IGF2BP2 and directly bind to its promoter and SE regions. Moreover, the abundance of KLF7 exhibited a positive correlation with the abundance of IGF2BP2 in HNSCC. Patients with high expression of both KLF7 and IGF2BP2 showed poorer prognosis. Lastly, we demonstrated that the small molecule inhibitor JQ1, targeting BRD4, attenuated the proliferation and metastatic abilities of HNSCC cells. Conclusions Our study reveals the critical role of IGF2BP2 overexpression mediated by SE and KLF7 in promoting HNSCC progression. Targeting SE-associated transcriptional programs may represent a potential therapeutic strategy in managing HNSCC.

Abstract Ameloblastoma is a benign tumor characterized by locally invasive phenotypes, leading to facial bone destruction and a high recurrence rate. However, the mechanisms governing tumor initiation and recurrence are poorly understood. Here, we uncovered cellular landscapes and mechanisms that underlie tumor recurrence in ameloblastoma at single-cell resolution. Our results revealed that ameloblastoma exhibits five tumor subpopulations varying with respect to immune response (IR), bone remodeling (BR), tooth development (TD), epithelial development (ED), and cell cycle (CC) signatures. Of note, we found that CC ameloblastoma cells were endowed with stemness and contributed to tumor recurrence, which was dominated by the EZH2-mediated program. Targeting EZH2 effectively eliminated CC ameloblastoma cells and inhibited tumor growth in ameloblastoma patient-derived organoids. These data described the tumor subpopulation and clarified the identity, function, and regulatory mechanism of CC ameloblastoma cells, providing a potential therapeutic target for ameloblastoma.

Abstract The monitoring of physiological parameters is a crucial topic in promoting human health and an indispensable approach for assessing physiological status and diagnosing diseases. Particularly, it holds significant value for patients who require long-term monitoring or with underlying cardiovascular disease. To this end, Visual Contactless Physiological Monitoring (VCPM) is capable of using videos recorded by a consumer camera to monitor blood volume pulse (BVP) signal, heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and blood pressure (BP). Recently, deep learning-based pipelines have attracted numerous scholars and achieved unprecedented development. Although VCPM is still an emerging digital medical technology and presents many challenges and opportunities, it has the potential to revolutionize clinical medicine, digital health, telemedicine as well as other areas. The VCPM technology presents a viable solution that can be integrated into these systems for measuring vital parameters during video consultation, owing to its merits of contactless measurement, cost-effectiveness, user-friendly passive monitoring and the sole requirement of an off-the-shelf camera. In fact, the studies of VCPM technologies have been rocketing recently, particularly AI-based approaches, but few are employed in clinical settings. Here we provide a comprehensive overview of the applications, challenges, and prospects of VCPM from the perspective of clinical settings and AI technologies for the first time. The thorough exploration and analysis of clinical scenarios will provide profound guidance for the research and development of VCPM technologies in clinical settings.

The integrated satellite-terrestrial communication system is considered one of the development trends of future communication systems for its ability to provide seamless coverage and service.However, the differences between satellite and terrestrial communication networks, e.g., large propagation delays, large Doppler shifts, and large cell radius, pose challenges to fulfilling integrated satellite-terrestrial communication systems.The network architectures and key enabling technologies were discussed and analyzed and a prototype system for the terrestrial verification of integrated satellite-terrestrial communication systems was proposed.

Abstract Pleomorphic adenoma (PA) is the most common benign tumour in the salivary gland and has high morphological complexity. However, the origin and intratumoral heterogeneity of PA are largely unknown. Here, we constructed a comprehensive atlas of PA at single-cell resolution and showed that PA exhibited five tumour subpopulations, three recapitulating the epithelial states of the normal parotid gland, and two PA-specific epithelial cell (PASE) populations unique to tumours. Then, six subgroups of PASE cells were identified, which varied in epithelium, bone, immune, metabolism, stemness and cell cycle signatures. Moreover, we revealed that CD36+ myoepithelial cells were the tumour-initiating cells (TICs) in PA, and were dominated by the PI3K-AKT pathway. Targeting the PI3K-AKT pathway significantly inhibited CD36+ myoepithelial cell-derived tumour spheres and the growth of PA organoids. Our results provide new insights into the diversity and origin of PA, offering an important clinical implication for targeting the PI3K-AKT signalling pathway in PA treatment.

Abstract With the increasing number of user terminals (UTs), the interference among UTs might significantly decrease the throughput of the low earth orbit satellite communication system. In this paper, the user scheduling method is investigated to suppress user interference. Specifically, leveraging the strong spatial directivity of satellite channels, a low‐complexity angle‐based orthogonal user selection (AOUS) algorithm is proposed, which selects UTs with nearly orthogonal channels via angle information of UTs. A rate‐based proportionally fair (PF)‐AOUS algorithm is further proposed to ensure fairness among UTs, which combines the AOUS with the PF criterion. To reduce complexity, an improved angle‐based PF‐AOUS algorithm that schedules UTs according to their pitch angles rather than their rates is proposed. In addition, efficient precoding schemes for orthogonal UTs are designed by combining the steering vector and power allocation matrix, and it is shown that precoding can be converted into power allocation problems that further balance fairness and throughput. The numerical results indicate that the AOUS achieves a near‐optimal sum rate performance, and the angle‐based PF‐AOUS has the similar performance to the rate‐based PF‐AOUS, which achieves a high fairness index with the proposed precoding scheme.

Abstract Tumor budding (TB) is a small tumor cell cluster with highly aggressive behavior located ahead of the invasive tumor front. However, the molecular and biological characteristics of TB and the regulatory mechanisms governing TB phenotypes remain unclear. This study reveals that TB exhibits a particular dynamic gene signature with stemness and partial epithelial‐mesenchymal transition (p‐EMT). Importantly, nuclear expression of CYTOR is identified to be the key regulator governing stemness and the p‐EMT phenotype of TB cells, and targeting CYTOR significantly inhibits TB formation, tumor growth and lymph node metastasis in head and neck squamous cell carcinoma (HNSCC). Mechanistically, CYTOR promotes tumorigenicity and metastasis of TB cells by facilitating the formation of FOSL1 phase‐separated condensates to establish FOSL1‐dependent super enhancers (SEs). Depletion of CYTOR leads to the disruption of FOSL1‐dependent SEs, which results in the inactivation of cancer stemness and pro‐metastatic genes. In turn, activation of FOSL1 promotes the transcription of CYTOR. These findings indicate that CYTOR is a super‐lncRNA that controls the stemness and metastasis of TB cells through facilitating the formation of FOSL1 phase separation and SEs, which may be an attractive target for therapeutic interventions in HNSCC.

BackgroundThe increasing number of older adults with mental, behavioral, and memory challenges presents significant public health concerns. Reminiscence is one type of nonpharmacological intervention that can effectively evoke memories, stimulate mental activities, and improve psychological well-being in older adults through a series of discussions on previous experiences. Fully immersive virtual reality (FIVR) may be a useful tool for reminiscence interventions because it uses realistic virtual environments connected to a person’s significant past stories. ObjectiveThis review aims to examine empirical evidence regarding the application of FIVR in reminiscence interventions, its usability and acceptability, and its effectiveness in assisting the intervention to achieve optimal outcomes. MethodsWe followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach for scoping reviews. The PubMed, PsycINFO, Embase, CINAHL, Web of Science, ACM, and IEEE Xplore electronic databases were used for the search. We included peer-reviewed studies that used FIVR as an assistive tool for reminiscence interventions; were published between January 1, 2000, and August 1, 2022; reported empirical research; involved older adults as participants; and addressed health- and behavior-related outcomes or the feasibility and usability of FIVR. We used Endnote X9 to organize the search results and Microsoft Excel for data extraction and synthesis. ResultsOf the 806 articles collected from the databases and other resources, 11 were identified. Most of the studies involved participants aged between 70 and 90 years. Only 1 study did not involve those with cognitive impairments, whereas 3 specifically targeted people living with dementia. The results indicated that FIVR reminiscence interventions enhanced engagement and reduced fatigue. Although some studies have observed positive effects on anxiety, apathy, depression, cognitive functions, and caregiver burden reduction, these findings were inconsistent across other research. In addition, FIVR showed overall usability and acceptability with manageable side effects among older adults across various health conditions during reminiscence sessions. However, 1 study reported adverse feelings among participants, triggered by unpleasant memories evoked by the virtual reality content. ConclusionsThe role of FIVR in reminiscence interventions remains nascent, with limited studies evaluating its impacts on older adults. Many of the reviewed studies had notable limitations: small sample sizes, absence of rigorous research design, limited assessment of long-term effects, lack of measures for health and behavior outcomes, and quality of life. Beyond these limitations, this review identified a list of future research directions in 6 categories. On the basis of the review findings, we provide practical recommendations to enhance FIVR reminiscence interventions, covering topics such as virtual reality content, device choice, intervention types, and the role and responsibility of facilitators.

Electrocardiogram (ECG) reconstruction from contact photoplethysmogram (PPG) would be transformative for cardiac monitoring. We investigated the fundamental and practical feasibility of such reconstruction by first replicating pioneering work in the field, with the aim of assessing the methods and evaluation metrics used. We then expanded existing research by investigating different cycle segmentation methods and different evaluation scenarios to robustly verify both fundamental feasibility, as well as practical potential. We found that reconstruction using the discrete cosine transform (DCT) and a linear ridge regression model shows good results when PPG and ECG cycles are semantically aligned—the ECG R peak and PPG systolic peak are aligned—before training the model. Such reconstruction can be useful from a morphological perspective, but loses important physiological information (precise R peak location) due to cycle alignment. We also found better performance when personalization was used in training, while a general model in a leave-one-subject-out evaluation performed poorly, showing that a general mapping between PPG and ECG is difficult to derive. While such reconstruction is valuable, as the ECG contains more fine-grained information about the cardiac activity as well as offers a different modality (electrical signal) compared to the PPG (optical signal), our findings show that the usefulness of such reconstruction depends on the application, with a trade-off between morphological quality of QRS complexes and precise temporal placement of the R peak. Finally, we highlight future directions that may resolve existing problems and allow for reliable and robust cross-modal physiological monitoring using just PPG.

Abstract Organic electrochemical transistors (OECTs) have emerged as versatile platforms for broad applications spanning from flexible and wearable integrated circuits to biomedical monitoring to neuromorphic computing. A variety of materials and tailored micro/nanostructures have recently been developed to realized stretchable OECTs, however, a solid-state OECT with high elasticity has not been demonstrated to date. Herein, we present a general platform developed for the facile generation of highly elastic all-polymer OECTs with high transconductance (up to 12.7 mS), long-term mechanical and environmental durability, and sustainability. Rapid prototyping of these devices was achieved simply by transfer printing lithium bis(trifluoromethane)sulfonimide doped poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT:PSS/LiTFSI) microstructures onto a resilient gelatin-based gel electrolyte, in which both depletion-mode and enhancement-mode OECTs were produced using various active channels. Remarkably, the elaborate 3D architectures of the PEDOT:PSS were engineered, and an imprinted 3D-microstructured channel/electrolyte interface combined with wrinkled electrodes provided performance that was retained (> 70%) through biaxial stretching of 100% strain and after 1000 repeated cycles of 80% strain. Furthermore, the anti-drying and degradable gelatin and the self-crosslinked PEDOT:PSS/LiTFSI jointly enabled stability during > 4 months of storage and on-demand disposal and recycling. This work thus represents a straightforward approach towards high-performance stretchable organic electronics for wearable/implantable/neuromorphic/sustainable applications.

Abstract Background Trimalleolar fracture is a common ankle fracture with serious complications and costly healthcare problem. Most studies used clinical assessments to evaluate the functional status of the patients. Although clinical assessments are valid, they are static and subjective. Dynamic, objective and precise evaluations such as gait analysis are needed. Ankle biomechanics studies on gait in patients with trimalleolar fractures are still rare. This study aimed to investigate the clinical outcomes and gait biomechanics in patients with trimalleolar fractures in the early postoperative period and compared to healthy controls. Methods This was a cross-sectional study. 12 patients with trimalleolar fractures were recruited, and 12 healthy people served as controls. All patients underwent clinical assessments: Olerud and Molander ankle score (OMAS), ankle swelling and passive range of motion (ROM) of ankle, and completed gait biomechanical analysis when weight-bearing was allowed: temporal-spatial parameters, plantar pressure distributions, and surface electromyography (sEMG). The control group only performed gait test. Results Patients had poor outcomes of clinical assessments in the short-term. During gait analysis, patients presented compromised gait patterns: shorter step length, larger step width, slower walking speed and shorter single support compared to healthy controls (P

To achieve fast and secure information steganography in underwater acoustic channel scenarios, this paper proposes a PSO (Particle Swarm Optimization) and IWT (integer wavelet transform) based image steganography algorithm for underwater acoustic communication. Firstly, the underwater image to be embedded is interleaved and packed to generate the secret information code-stream to improve the detection and recovery performance of transmission errors. Secondly, the cover image is divided into non-overlapping blocks and IWT is applied to each block, which can save PSO search space and improve the optimal solution performance. Thirdly, the embedding position matrix of the high frequency sub-band coefficients is chaotic scrambled, and PSO is used to select the optimal key to obtain the optimal matching position for the secret information to produce the best stego-image quality. Finally, transmission error detection and recovery measures are applied to the extracted secret information to improve the reconstruction quality in underwater acoustic channel scenarios. Experimental results show that the proposed algorithm outperforms existing approaches in terms of information embedding capacity and steganographic visual quality, meeting the requirements of safety and real-time performance of underwater communication. Moreover, it also has the ability of error detection and recovery for harsh underwater acoustic channel.

Abstract In this paper, massive multiple‐input‐multiple‐output (MIMO) wireless communication systems are considered to investigate joint transceiver beamforming. A base station (BS) equipped with a uniform planar array (UPA) serves several multi‐antennas users in a single cell. Based on the channel state information (CSI), the low complexity design of transceiver beamforming to minimize the transmit power subject to some quality of service (QoS) constraints is investigated. As the upper bound of the transmit power performance, the existing iteration‐based algorithms are leveraged as a reference. A general deep learning (DL)‐based framework and deep neural network (DNN) structure are proposed to reduce the complexity of the existing algorithms, where the properly trained DNN structure can learn directly from CSI. Consider the complexity of the DNN structure itself, a heuristic algorithm is proposed to replace the DNN structure, which takes the max‐eigenvalue‐eigenvector of the CSI as the direction of receive beamforming directly. The DNN structure is trained in the offline stage, therefore, only the complexity in the online stage is taken into consideration. Based on the numerical simulation, the complexity of the proposed DL‐based framework and the transceiver beamforming algorithms is reduced significantly while maintaining nearly the optimal performance compared with the existing iterative algorithms.

Satellite communication is an indispensable part of future wireless communications given its global coverage and long-distance propagation. In satellite communication systems, channel acquisition and energy consumption are two critical issues. To this end, we investigate the tradeoff between the total energy efficiency (TEE) and minimum EE (MEE) for robust multigroup multicast satellite communication systems in this paper. Specifically, under the total power constraint, we investigate the robust beamforming aimed at balancing the TEE-MEE, so as to achieve the balance between the fairness and total performance on the system EE. For this optimization problem, we first model the balancing problem as a nonconvex problem while deriving its approximate closed-form average user rate. Then, the nonconvex problem is handled by solving convex programs sequentially with the help of the semidefinite relaxation and the concave-convex procedure. In addition, depending on the solution rank value, Gaussian randomization and eigenvalue decomposition method are applied to generate the feasible solutions. Finally, simulation results illustrate that the proposed approach can effectively achieve the balance between the TEE and MEE, thus realizing a tradeoff between fairness and system EE performance. It is also indicated that the proposed robust approach outperforms the conventional baselines in terms of EE performance.

Narrowband internet of things (NB-IoT) technology is widely used in data communications for a large number of low-speed and low-power devices, but it is diff cult to provide services for remote areas that cannot be covered by terrestrial networks.With its global coverage and low cost, the LEO satellite constellation can supplement and expand the terrestrial NB-IoT infrastructure, providing an eff ective solution for the space-based internet of things.Facing the application requirements of space-based internet of things, on the basis of reviewing the NB-IoT system architecture, the challenges of channel environment high dynamic delay and frequency off set faced by the application of NB-IoT technology in the LEO satellite constellation scenario were analyzed.For the uplink random access process, an eff ective user detection and timing synchronization method was designed, which had the advantages of high performance and low complexity, and provided an eff cient receiving method for the LEO satellite NB-IoT uplink random access synchronization.

Abstract To validate the accuracy of Cone beam computed tomography (CBCT) cervical spine modeling with three dimensional (3D)-3D registration for in vivo measurements of cervical spine kinematics. CBCT model accuracy was validated by superimposition with computed tomography (CT) models in 10 healthy young adults, and then cervical vertebrae were registered in six end positions of functional movements, versus a neutral position, in 5 healthy young adults. Registration errors and six degrees of freedom (6-DOF) kinematics were calculated and reported. Relative to CT models, mean deviations of the CBCT models were

BackgroundSeveral studies have revealed a positive correlation between a Helicobacter pylori (HP) infection and the risk of non-alcoholic fatty liver disease (NAFLD). This meta-analysis was conducted to explore further the relationship between HP infection and NAFLD in the Asian and non-Asian populations.MethodsRelevant studies published from inception to July 22, 2021, in the following databases: PubMed, EMBASE, the Cochrane library, and Web of Science were comprehensively searched. The odds ratio (OR) and hazard ratio (HR) with a 95% confidence interval (95%CI) were pooled by the random-effects model or fixed-effects model. Additionally, subgroup and sensitivity analyses were performed. The funnel plot and the Egger test were used to estimate publication bias.ResultsThis meta-analysis included 25 studies involving 107,306 participants. Positive associations between HP infection and NAFLD were found both for the Asian (OR = 1.30, 95% CI: 1.13–1.49, P < 0.01; I2 = 94.30%, P < 0.01) and non-Asian populations (OR = 1.42, 95% CI: 1.04–1.94, P = 0.03; I2 = 44.90%, P = 0.09). Moreover, similar results were observed in the Asian female group (OR = 1.31, 95% CI: 1.17–1.46, P < 0.01; I2 = 46.30%, P = 0.07) but not for the Asian male group. Subgroup analyses for the Asian population showed that there were differences in the association among NAFLD diagnosis methods (P < 0.01) and the study design (P < 0.01). However, subgroup and sensitivity analyses results showed that the association for the non-Asian population was not stable enough.ConclusionsThe data obtained in this systematic review and meta-analysis suggested that an HP infection was associated with an increased risk of NAFLD for Asian and non-Asian populations. However, the association was not found for Asian males. Further studies are required to establish the causal association, especially for the non-Asian population.Systematic review registrationIdentifier: CRD42021266871.

Objectives: The subjectivity of the Physician Global Assessment (PGA) is a limitation of the Mayo score in assessing severity of ulcerative colitis (UC). We compared treatment efficacy using endpoint definitions based on modified Mayo (mMayo) score, versus those based on Mayo score, using data from the tofacitinib OCTAVE program. Design: This post hoc analysis included data from two 8-week induction studies (OCTAVE Induction 1 and 2) and a 52-week maintenance study (OCTAVE Sustain). Methods: Remission and clinical response [with nonresponder imputation (NRI)] were assessed using mMayo (without PGA) and Mayo scores, and further stratified by prior tumor necrosis factor inhibitor (TNFi) failure status. Results: At week 8 of OCTAVE Induction 1 and 2, remission rates with placebo and tofacitinib 10 mg twice daily (BID), respectively, were 7.7% and 24.8% (mMayo) and 6.0% and 17.6% (Mayo). At week 52 of OCTAVE Sustain, remission rates with placebo, tofacitinib 5 and 10 mg BID, respectively, were 12.1%, 35.9%, and 42.1% (mMayo) and 11.1%, 34.3%, and 40.6% (Mayo). A statistically significant ( p

BackgroundFOSL1, a key component of the Activating protein-1 (AP-1) transcriptional complex, plays an important role in cancer cell migration, invasion, and proliferation. However, the impact of FOSL1 in ameloblastoma (AM) has not been clarified. Herein, we aimed to assess the expression of FOSL1 and investigate its functional role in AM.MethodsThe expression of FOSL1 was examined based on an immunohistochemistry analysis of 96 AM samples. Cell proliferation, migration, invasion, and tumorigenesis were assessed using Cell Counting Kit-8 (CCK-8), colony formation, Transwell, and sphere formation assays. RNA sequencing (RNA-seq) was employed to investigate the molecular alterations of AM cells upon FOSL depletion. Microarrays of AMs were downloaded from the Gene Expression Omnibus (GEO) database for bioinformatics analysis. In addition, patient-derived AM organoids were used to evaluate the therapeutic value of the AP-1 inhibitor.ResultsFOSL1 was detected in the nuclei of AMs and upregulated in conventional AMs compared to unicystic AMs and normal oral epithelium. Compared with primary AM, FOSL1 expression was significantly increased in recurrent AM. Genetic knockdown of FOSL1 suppressed the proliferation, migration, invasion, and sphere formation of AMs. Similar results were also observed by pharmacological inhibition of AP-1 activity. Moreover, the AP-1 inhibitor T5224 impeded the growth of organoids derived from AM patients. Mechanistically, our Ingenuity Pathway Analysis (IPA) and gene set enrichment analysis (GSEA) results revealed that depletion of FOSL1 inactivated kinetochore metaphase signaling and the epithelial–mesenchymal transition pathway and then impaired the aggressiveness of AM cells accordingly.ConclusionFOSL1 promotes tumor recurrence and invasive growth in AM by modulating kinetochore metaphase signaling and the epithelial–mesenchymal transition pathway; thus, it represents a promising therapeutic target for AM treatment.

When observing the Earth from space, the synthetic aperture radiometer antenna array is sometimes set as a non-uniform array. In non-uniform synthetic aperture radiometer image reconstruction, the existing brightness temperature image reconstruction methods include the grid method and array factor forming (AFF) method. However, when using traditional methods for imaging, errors are usually introduced or some prior information is required. In this article, we propose a new IASR imaging method with deep convolution neural network (CNN). The frequency domain information is extracted through multiple convolutional layers, global pooling layers, and fully connected layers to achieve non-uniform synthetic aperture radiometer imaging. Through extensive numerical experiments, we demonstrate the performance of the proposed imaging method. Compared to traditional imaging methods such as the grid method and AFF method, the proposed method has advantages in image quality, computational efficiency, and noise suppression.