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To evaluate the efficacy of radiomics features extracted from preoperative high-resolution computed tomography (HRCT) scans in distinguishing benign and malignant pulmonary pure ground-glass nodules (pGGNs), a retrospective study of 395 patients from 2016 to 2020 was conducted. All nodules were randomly divided into the training and validation sets in the ratio of 7:3. Radiomics features were extracted using MaZda software (version 4.6), and the least absolute shrinkage and selection operator (LASSO) was employed for feature selection. Significant differences were observed in the training set between benign and malignant pGGNs in sex, mean CT value, margin, pleural retraction, tumor–lung interface, and internal vascular change, and then the mean CT value and the morphological features model were constructed. Fourteen radiomics features were selected by LASSO for the radiomics model. The combined model was developed by integrating all selected radiographic and radiomics features using logistic regression. The AUCs in the training set were 0.606 for the mean CT value, 0.718 for morphological features, 0.756 for radiomics features, and 0.808 for the combined model. In the validation set, AUCs were 0.601, 0.692, 0.696, and 0.738, respectively. The decision curves showed that the combined model demonstrated the highest net benefit.

BackgroundPrevious studies have suggested that repetitive transcranial magnetic stimulation (rTMS) may be an effective and safe alternative treatment for post-stroke cognitive impairment (PSCI). Similarly, the application of transcranial direct current stimulation (tDCS) during stroke rehabilitation has been shown to improve cognitive function in PSCI patients. However, there have been conflicting results from some studies. Therefore, this study aims to conduct a meta-analysis to evaluate the effects of tDCS and rTMS on PSCI.MethodsThe meta-analysis search for articles published from the initial availability date to 5 February 2024 in databases. The extracted study data were entered into STATA 12.0 software for statistical analysis.ResultsThis meta-analysis provides evidence that both rTMS and tDCS have a positive impact on general cognitive function in PSCI patients [immediate effect of rTMS: standard mean difference (SMD) = 2.58, 95% confidence interval (CI) = 1.44 to 3.71; long-term effect of rTMS: SMD = 2.33, 95% CI = 0.87–3.78; immediate effect of tDCS: SMD = 2.22, 95% CI = 1.31–3.12]. Specifically, rTMS was found to significantly improve attention, language, memory, and visuospatial functions, while it did not show a significant therapeutic effect on executive function (attention: SMD = 3.77, 95% CI = 2.30–5.24; executive function: SMD = −0.52, 95% CI = −3.17–2.12; language: SMD = 3.43, 95% CI = 1.50–5.36; memory: SMD = 3.52, 95% CI = 1.74–5.30; visuospatial function: SMD = 4.71, 95% CI = 2.61–6.80). On the other hand, tDCS was found to significantly improve executive and visuospatial functions but did not show a significant improvement in attention function and memory (attention: SMD = 0.63, 95% CI = −0.30–1.55; executive function: SMD = 2.15, 95% CI = 0.87–3.43; memory: SMD = 0.99, 95% CI = −0.81–2.80; visuospatial function: SMD = 2.64, 95% CI = 1.04–4.23).ConclusionIn conclusion, this meta-analysis demonstrates that both rTMS and tDCS are effective therapeutic techniques for improving cognitive function in PSCI. However, more large-scale studies are needed to further investigate the effects of these techniques on different cognitive domains in PSCI.

AbstractIn this study, the mitochondrial genome was sequenced in a new commercial species, spotted knifejaw (O. punctatus), using next-generation sequencing and PCR-based methods. The overall length of the female O. punctatus mitochondrial genome was 16,508 bp. It contained 13 PCGs, 2 r-RNA genes, 22 t-RNA genes, and a displacement loop locus (a control region). The total nucleotide composition was 28.75% A, 25.69% T, 29.70% C, and 15.86% G, with a total A + T content of 54.44%. The results demonstrated that the mitochondrial genome of O. punctatus has a high sequence identity with that of another species of Perciformes. This finding provides a deeper understanding of mitogenomic diversity and evolution in marine fish.

Objective To describe the health care resource use (HCRU) and costs of patients with systemic sclerosis (SSc) prior to and after diagnosis. Methods This retrospective study used a claims data set (Merative MarketScan; 2015‐2019). Eligible patients with SSc were identified by diagnosis codes and required at least 24 months of enrollment without an SSc diagnosis before their first SSc claim and at least 12 months of enrollment thereafter. Total HCRU and costs were reported for three intervals: 2 years and 1 year before and 1 year after index diagnosis. A general population cohort without SSc was matched 1:1 to the SSC cohort on age and sex for comparison. Results Eligibility criteria identified 902 patients with SSc (mean age: 54 years old; 85% female). Mean per‐member per year costs increased each year from $22,383 to $29,708 to $47,095, 2 years before, 1 year before, and 1 year after index diagnosis versus $10,232 to $9656 to $9714 in the general population cohort. Outpatient settings represented the largest proportion of cost 1 year after SSc diagnosis ($16,392), followed by prescription drugs ($10,692), physician office ($10,523), and inpatient ($9448) settings. Conclusion Patients with SSC accrued greater costs and required more services than a general population cohort. These elevated expenditures and HCRU were observed at least 2 years before an SSc diagnosis and increased over time, reflecting both the progressive, multisystem nature of SSc and potential challenges in diagnosis. These findings suggest that SSc poses a substantial burden on the US health care system and highlights the need for early diagnosis and effective therapies.

Aim: Monitoring treatment of tenosynovial giant cell tumor (TGCT) is complicated by the irregular shape and asymmetrical growth of the tumor. We compared responses to pexidartinib by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 with those by tumor volume score (TVS) and modified RECIST (m-RECIST). Materials & methods: MRIs acquired every two cycles were assessed centrally using RECIST 1.1, m-RECIST and TVS and tissue damage score (TDS). Results: Thirty-one evaluable TGCT patients were treated with pexidartinib. From baseline to last visit, 94% of patients (29/31) showed a decrease in tumor size (median change: -60% [RECIST], -66% [m-RECIST], -79% [TVS]). All methods showed 100% disease control rate. For TDS, improvements were seen in bone erosion (32%), bone marrow edema (58%) and knee effusion (46%). Conclusion: TVS and m-RECIST offer potentially superior alternatives to conventional RECIST for monitoring disease progression and treatment response in TGCT. TDS adds important information about joint damage associated with TGCT.

Abstract Background Insomnia is the most common sleep disorder in the general population, especially among pregnant women, and it is considered a major public health issue. Not only can it cause mental and physical problems in pregnant women, but it may also affect the growth of the fetus. However, there are few reports on the prevalence and influencing factors of insomnia symptoms in third-trimester women in China. The objective of this study was to assess the prevalence of insomnia symptoms among pregnant women in the third trimester in a moderately developing region of China and to further explore the associated factors of insomnia symptoms from various aspects. Methods A cross-sectional survey was conducted among eligible pregnant women in the third trimester from December 2022 to February 2023. Data on socio-demographic characteristics, clinical characteristics, and behavioral and psychological characteristics of pregnant women were collected through a structured questionnaire. The Chi-square test and multivariate logistics regression were applied to explore the associated factors of insomnia symptoms. Results A total of 535 pregnant women in the third trimester were included in this study, and the prevalence of insomnia symptoms was 59.8%. Multivariate logistic regression analysis revealed that pregnant women who lived together with elders (OR: 0.58, 95% CI: 0.40–0.86), had low perceived stress (OR: 0.58, 95% CI: 0.35–0.97), had no threatened abortion (OR: 0.55, 95% CI: 0.32–0.93) and had good doctor-patient communication (OR: 0.66, 95% CI: 0.45–0.98) were more likely to stay away from insomnia symptoms. However, pregnant women with anxiety symptoms (OR: 2.27, 95% CI: 1.28–4.03), fear of childbirth (OR: 1.63, 95% CI: 1.11–2.40) and a high experience of COVID-19 fear (OR: 1.61, 95% CI: 1.03–2.54) tended to have insomnia symptoms. Conclusions The prevalence of insomnia symptoms in pregnant women is high in Lianyungang city in eastern China in the third trimester. Insomnia symptoms is influenced by multiple factors. There is an urgent need to develop interventions to reduce the prevalence of insomnia symptoms in the third trimester and to focus on pregnant women with risk factors for insomnia symptoms.

Abstract Background Parkinson’s disease (PD) is a common chronic neurological disorder with a high risk of disability and no cure. Periodontitis is an infectious bacterial disease occurring in periodontal supporting tissues. Studies have shown that periodontitis is closely related to PD. However, direct evidence of the effect of periodontitis on PD is lacking. Here, we demonstrated that ligature-induced periodontitis with application of subgingival plaque (LIP-SP) exacerbated motor dysfunction, microglial activation, and dopaminergic neuron loss in 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mice. Results The 16S rRNA gene sequencing revealed that LIP-SP induced oral and gut dysbiosis. Particularly, Veillonella parvula (V. parvula) and Streptococcus mutans (S. mutans) from oral ligatures were increased in the fecal samples of MPTP + LIP-SP treated mice. We further demonstrated that V. parvula and S. mutans played crucial roles in LIP-SP mediated exacerbation of motor dysfunction and neurodegeneration in PD mice. V. parvula and S. mutans caused microglial activation in the brain, as well as T helper 1 (Th1) cells infiltration in the brain, cervical lymph nodes, ileum and colon in PD mice. Moreover, we observed a protective effect of IFNγ neutralization on dopaminergic neurons in V. parvula- and S. mutans-treated PD mice. Conclusions Our study demonstrates that oral pathogens V. parvula and S. mutans necessitate the existence of periodontitis to exacerbate motor dysfunction and neurodegeneration in MPTP-induced PD mice. The underlying mechanisms include alterations of oral and gut microbiota, along with immune activation in both brain and peripheral regions. Video Abstract

The clay mineral content of Daqing Gulong shale is in the range of about 35%–45%, with particle sizes less than 0.0039 mm. The horizontal fluidity of oil in Gulong shale is poor, with near-zero vertical flowability. As a result, Gulong shale has been considered to lack commercial value. In recent years, however, interdisciplinary research in geoscience, percolation mechanics, thermodynamics, and surface mechanics has demonstrated that Gulong shale oil has a high degree of maturity and a high residual hydrocarbon content. The expulsion efficiency of Gulong shale in the high mature stage is 32%–48%. Favorable storage spaces in Gulong shale include connecting pores and lamellar fractures developed between and within organic matter and clay mineral complexes. The shale oil mainly occurs in micro- and nano-pores, bedding fractures, and lamellar fractures, with a high gas–oil ratio and medium–high movable oil saturation. Gulong shale has the characteristics of high hardness, a high elastic modulus, and high fracture toughness. This study achieves breakthroughs in the exploration and development of Gulong shale, including the theories of hydrocarbon generation and accumulation, the technologies of mobility and fracturing, and recoverability. It confirms the major transition of Gulong shale from oil generation to oil production, which has extremely significant scientific value and application potential for China’s petroleum industry.

The continuous improvement in the seaworthiness of Arctic shipping routes has caused an urgent international demand for meteorological and sea ice information. In view of the diversity of Arctic meteorological and sea ice information websites and the uneven service levels of the websites, and to assist Arctic navigation ships in selecting timely, stable, and reliable meteorological and sea ice information, this paper summarizes the websites providing Arctic meteorological and sea ice information. Constructing an evaluation indicator system for the service level of the Arctic meteorological and sea ice information websites from the two dimensions of data quality and browsing experience, this system integrates the cloud model, the Dempster–Shafer (D-S) evidence theory, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to construct a corresponding service-level evaluation and decision optimization process of Arctic meteorological and sea ice information websites. Finally, through case analysis, the feasibility of this research method is demonstrated.

The signal blockage and multipath effects of the Global Navigation Satellite System (GNSS) caused by urban canyon scenarios have brought great technical challenges to the positioning and navigation of autonomous vehicles. In this paper, an improved factor graph optimization algorithm enhanced by a resilient noise model is proposed. The measurement noise is resilient and adjusted based on an approximate Gaussian distribution-based estimation. In estimating and adjusting the noise parameters of the measurement model, the error covariance matrix of the multi-sensor fusion positioning system is dynamically optimized to improve the system accuracy. Firstly, according to the approximate Gaussian statistical property of the GNSS/odometer velocity residual sequence, the measured data are divided into an approximate Gaussian fitting region and an approximate Gaussian convergence region. Secondly, the interval is divided according to the measured data, and the corresponding variational Bayesian network and Gaussian mixture model are used to estimate the innovation online. Further, the noise covariance matrix of the adaptive factor graph-based model is dynamically optimized using the estimated noise parameters. Finally, based on low-cost inertial navigation equipment, GNSS, odometer, and vision, the algorithm is implemented and verified using a simulation platform and real-vehicle road test. The experimental results show that in a complex urban road environment, compared with the traditional factor graph fusion localization algorithm, the maximum improvement in accuracy of the proposed algorithm can reach 65.63%, 39.52%, and 42.95% for heading, position, and velocity, respectively.

Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study-the Fort Campbell Cohort study-examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90-180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67-0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78-0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75-0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79-0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.

Abstract Background Fear of childbirth (FOC) is a prevalent issue among pregnant women and significantly relates to adverse outcomes for the mother and child. However, it is not clear the prevalence and risk factors of FOC among pregnant women in a region with a moderate level of economic development in China. The aim of this study was to investigate the prevalence and risk factors of FOC among pregnant women in the third trimester of pregnancy in Lianyungang city, Eastern China. Methods A cross-sectional survey was conducted from December 2022 to February 2023 among pregnant women in the third trimester who met the inclusion criteria and visited Lianyungang Maternal and Child Health Hospital in Jiangsu Province, Eastern China. A structured questionnaire including sociodemographic characteristics, clinical characteristics, FOC, family function, doctor-patient communication, social support, general self-efficacy, anxiety, depression, insomnia symptoms, and quality of life was used to collect data. A multiple linear regression model was used to identify predictors of FOC. Results This study included 535 pregnant women in the third trimester. The mean score of FOC was 30.67 ± 10.18, and the median score was 29.00. The prevalence of FOC was 56.64%. Multiple linear regression analysis revealed that pregnant women with electronic screen exposure time more than 5 h per day (β = 2.02, 95%CI: 0.50–3.53, P

Introduction: Yinchenzhufu decoction (YCZFD) is a traditional Chinese medicine formula with hepatoprotective effects. In this study, the protective effects of YCZFD against cholestatic liver fibrosis (CLF) and its underlying mechanisms were evaluated.Methods: A 3, 5-diethoxycarbonyl-1, 4-dihydro-collidine (DDC)-induced cholestatic mouse model was used to investigate the amelioration of YCZFD on CLF. Data-independent acquisition-based mass spectrometry was performed to investigate proteomic changes in the livers of mice in three groups: control, model, and model treated with high-dose YCZFD. The effects of YCZFD on the expression of key proteins were confirmed in mice and cell models.Results: YCZFD significantly decreased the levels of serum biochemical, liver injury, and fibrosis indicators of cholestatic mice. The proteomics indicated that 460 differentially expressed proteins (DEPs) were identified among control, model, and model treated with high-dose YCZFD groups. Enrichment analyses of these DEPs revealed that YCZFD influenced multiple pathways, including PI3K-Akt, focal adhesion, ECM–receptor interaction, glutathione metabolism, and steroid biosynthesis pathways. The expression of platelet derived growth factor receptor beta (PDGFRβ), a receptor associated with the PI3K/AKT and focal adhesion pathways, was upregulated in the livers of cholestatic mice but downregulated by YCZFD. The effects of YCZFD on the expression of key proteins in the PDGFRβ/PI3K/AKT pathway were further confirmed in mice and transforming growth factor-β-induced hepatic stellate cells. We uncovered seven plant metabolites (chlorogenic acid, scoparone, isoliquiritigenin, glycyrrhetinic acid, formononetin, atractylenolide I, and benzoylaconitine) of YCZFD that may regulate PDGFRβ expression.Conclusion: YCZFD substantially protects against DDC-induced CLF mainly through regulating the PDGFRβ/PI3K/AKT signaling pathway.

Abstract Background Genetic disorders ascribe to half of cases of congenital hearing loss. Hearing screening is significant in detecting hearing loss (HL) but weak at diagnosis, which can be complemented by genetic screening. Methods To find a feasible method to accomplish genetic screening and evaluate its advantage when combined with hearing screening, between 1 January 2022, and 10 December 2023, we performed an observational cohort study based on 2488 neonates from the Han population at three hospitals in Jiangsu province. Genetic screening for 20 variants in four common HL‐associated genes by multicolor melting curve analysis (MMCA) and hearing screening were offered concurrently to all participants. Results In total, 170 (6.8%) of 2488 eligible neonates were detected at least one variant and among them, the proportion of referral was higher (p

With growing concerns about Group B streptococcal (GBS) infections and their adverse effects on perinatal pregnancies, including infection, premature delivery, neonatal septicemia, and meningitis, it is urgent to promote GBS screening at all pregnancy stages. The purpose of this study is to establish a device-independent, fast, sensitive, and visual GBS detection method. Taking advantage of the characteristics of the recombinase polymerase isothermal amplification (RPA), the activity of the nfo nuclease cleavage base analog (tetrahydrofuran, THF) site, and the advantages of visual reading of the lateral flow chromatography strip (LFS), a GBS detection method was developed. This method focused on the conservative region of the Christie–Atkins–Munch–Petersen factor encoded by the cfb gene, a virulence gene specific to GBS. Two forward primers, two biotin-labeled reverse primers, and one fluorescein isothiocyanate (FITC)-labeled and C3spacer-blocked probe were designed. The study involved optimizing the primer pair and probe combination, determining the optimal reaction temperature and time, evaluating specificity, analyzing detection limits, and testing the method on 87 vaginal swabs from perinatal pregnant women. The results showed that the visual detection method of GBS-RPA-LFS, using the cfb-F1/R2/P1 primer probe, could detect GBS within 15 min at the temperature ranging from 39°C to 42°C. Furthermore, the method specifically amplified only GBS, without cross-reacting with pathogens like Lactobacillus iners, Lactobacillus crispatus, Candida albicans, Listeria monocytogenes, Yersinia enterocolitica, Klebsiella Pneumoniae, Enterobacter cloacae, Citrobacter freundii, Vibrio alginolyticus, Vibrio parahaemolyticus, Salmonella typhimurium, Staphylococcus aureus, Pseudomonas aeruginosa, or Trichomonas vaginalis. It could detect a minimum of 100 copies per reaction. In clinical 98 samples of vaginal swabs from pregnant women, the agreement rate between the GBS-RPA-LFS method and TaqMan real-time fluorescence quantification method was 95.92%. In conclusion, this study successfully established a combined RPA and LFS GBS in situ detection platform, with short reaction time, high sensitivity, high specificity, portability, and device independence, providing a feasible strategy for clinical GBS screening.

Background: Ailanthone, a small compound derived from the bark of Ailanthus altissima (Mill.) Swingle, has several anti-tumour properties. However, the activity and mechanism of ailanthone in colorectal cancer (CRC) remain to be investigated. This study aims to comprehensively investigate the mechanism of ailanthone in the treatment of CRC by employing a combination of network pharmacology, bioinformatics analysis, and molecular biological technique.Methods: The druggability of ailanthone was examined, and its targets were identified using relevant databases. The RNA sequencing data of individuals with CRC obtained from the Cancer Genome Atlas (TCGA) database were analyzed. Utilizing the R programming language, an in-depth investigation of differentially expressed genes was carried out, and the potential target of ailanthone for anti-CRC was found. Through the integration of protein-protein interaction (PPI) network analysis, GO and KEGG enrichment studies to search for the key pathway of the action of Ailanthone. Then, by employing molecular docking verification, flow cytometry, Transwell assays, and Immunofluorescence to corroborate these discoveries.Results: Data regarding pharmacokinetic parameters and 137 target genes for ailanthone were obtained. Leveraging The Cancer Genome Atlas database, information regarding 2,551 differentially expressed genes was extracted. Subsequent analyses, encompassing protein–protein interaction network analysis, survival analysis, functional enrichment analysis, and molecular docking verification, revealed the PI3K/AKT signaling pathway as pivotal mediators of ailanthone against CRC. Additionally, the in vitro experiments indicated that ailanthone substantially affects the cell cycle, induces apoptosis in CRC cells (HCT116 and SW620 cells), and impedes the migration and invasion capabilities of these cells. Immunofluorescence staining showed that ailanthone significantly inhibited the phosphorylation of AKT protein and suppressed the activation of the PI3K/AKT signaling pathway, thereby inhibiting the proliferation and metastasis of CRC cells.Conclusion: Therefore, our findings indicate that Ailanthone exerts anti-CRC effects primarily by inhibiting the activation of the PI3K/AKT pathway. Additionally, we propose that Ailanthone holds potential as a therapeutic agent for the treatment of human CRC.

The World Health Organization (WHO) has identified the use of iron cookware as a potential strategy for alleviating iron deficiency anaemia (IDA) and emphasises the need for action-oriented research in this area. In response to this need, our study systematically investigated the patterns of iron release from various types of cookware under different cooking conditions. Among these, nitrided iron pots (NIPs), the most widely used cookware, were selected for the development of kinetic models to predict iron release efficiently across a range of cooking temperatures and pH levels in food materials. Our results demonstrated that iron release from the pots was significantly influenced by cooking conditions such as the type of cookware, cooking temperatures, cooking times, types of acidic substances, and the pH of the cooking environment. Specifically, higher temperatures, longer cooking times, lower pH levels, and the presence of acetic acid were found to maximise iron release into food. We developed a series of kinetic models—Iron Release-Temperature Models (I, II, and III) and Iron Release-pH Models (IV, V, and VI)—to predict iron release from NIPs. The temperature models are applicable for cooking food with a pH of 5.00–6.00 within a temperature range of 50–100 °C, while the pH models are designed for food with a pH of 3.00–6.00 at boiling temperatures. Validation experiments confirmed the relative accuracy of these models. Additionally, when comparing the predicted iron release with the Recommended Nutrient Intake (RNI) guidelines, the findings support the efficacy of iron pots as a viable method for iron supplementation.

The convergence of software-defined networking (SDN) and the Internet of Things (IoT) provides a scalable method for handling the considerable volumes of data produced by IoT devices. However, the lack of appropriate security measures can lead to unauthorized access to sensitive data, potential breaches, and privacy violations, as well as time-consuming and inefficient data retrieval methods in SDN-IoT systems that require decrypting the entire dataset. To address these challenges, this article proposes the time-attribute-based access control scheme in SDN-IoT (TAAC). The TAAC scheme combines ciphertext-policy attribute-based encryption with a novel time-attribute-based access tree to ensure fine-grained access control on time and attributes, enabling secure ciphertext interaction and information sharing across domains. Furthermore, the TAAC scheme also incorporates searchable encryption, which enhances the efficiency of data retrieval. By implementing searchable encryption techniques, the data receiver can generate trapdoors to search and retrieve specific encrypted data without the need to decrypt the entire dataset. In summary, the TAAC scheme improves storage efficiency and computation, enhances scalability, and provides robust security, offering an efficient and secure solution for ciphertext sharing in SDN-IoT environments. Experimental results have demonstrated that the TAAC scheme shows excellent performance and outperforms other attribute-based searchable encryption algorithms.

AbstractObjectives The aims of the study were to explore the potential associations between plasma proprotein convertase subtilisin/kexin type 9 (PCSK9) and coagulation indexes in patients with primary membranous nephropathy (PMN).Methods A total of 87 patients diagnosed with PMN were enrolled in our study. 30 healthy participants were recruited to match PMN participants. Plasma PCSK9 concentrations were tested by enzyme-linked immunosorbent assay (ELISA). Correlations between PCSK9 and coagulation abnormalities in patients with PMN were analyzed using univariate and multiple linear regression analysis.Results Plasma PCSK9 levels in patients with PMN were significantly higher than that in healthy controls [232.0 (143.5, 359.5) ng/mL vs. 166.8 (129.7, 199.7) ng/mL; p = 0.001]. Plasma levels of PCSK9 were positively correlated with factor VIII, factor IX, factor XI, log-transformed tissue factor, protein C and protein S (r = 0.267, p = 0.013; r = 0.496, p

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6-10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819-0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

Abstract With the continuous progress of the Internet of Things (IoT) technology, IoT devices have gradually penetrated all aspects of life. However, due to rapid data growth, IoT devices with limited memory resources cannot store massive data. Cloud computing is an Internet-centric network that can provide security services and data storage. The combination of IoT devices with cloud computing considerably promotes resource sharing, facilitates users’ access to information at any time, and provides users with corresponding cloud computing services on time. Because the information transmitted through public channels is easily intercepted, tampered with, and eavesdropped on by malicious attackers. As a result, users’ and servers’ private information are disclosed. Numerous scholars have proposed different authentication protocols in this environment to protect the communications between users and servers. Amin et al. devised a smart card based authentication protocol. Unfortunately, Kang et al. demonstrated that their protocol was insecure. Huang et al. discovered Kang et al.’s improvement also has security flaws and then designed a protocol to enhance security. In this paper, we first show that Huang et al.’s protocol cannot resist privileged insider and temporary value disclosure attacks. Afterward, we propose an enhanced protocol based on their protocol. Finally, we use formal/informal security analysis to demonstrate the security of the improved protocol. The comparison results are indicated that our protocol has lower computational and communication costs under the same security level.

Considering that laser scan stations are expensive and heavy for the indoor environment reconstruction of unmanned systems, a low-cost and light reconstruction system is proposed in this research. The system consists of a cross-structured light visual (SLV) sensor and an inertial navigation system (INS). The cross-SLV sensor is used to scan the surroundings and to estimate the angle change between two adjacent measurements. To improve the robustness and accuracy of the angle measurement, a Kalman Filter (KF) with simple construction is designed to fuse the inertial information from the INS. The factors which influence ranging accuracy are analyzed and ranging experiments show that the SLV sensor has an accuracy of higher than 2% when the distance is less than 4 m. Then the reconstruction results of a kitchen and corridor show that the error of most points is less than 50 mm for either kitchen (94%) or corridor (85%), and the mean errors and standard deviations of kitchen and corridor are less than 20 mm and 30 mm, respectively.

Activation of brown adipose tissue (BAT) contributes to energy dissipation and metabolic health. Although mineralocorticoid receptor (MR) antagonists have been demonstrated to improve metabolism under obesity, the underlying mechanisms remain incompletely understood. We aimed to evaluate the role of BAT MR in metabolic regulation. After 8 weeks of high-fat diet (HFD) feeding, BAT MR KO (BMRKO) mice manifested significantly increased bodyweight, fat mass, serum fasting glucose, and impaired glucose homeostasis compared with littermate control (LC) mice, although insulin resistance and fasting serum insulin were not significantly changed. Metabolic cage experiments showed no change in O2 consumption, CO2 production, or energy expenditure in obese BMRKO mice. RNA sequencing analysis revealed downregulation of genes related to fatty acid metabolism in BAT of BMRKO-HFD mice compared with LC-HFD mice. Moreover, H&E and immunohistochemical staining demonstrated that BMRKO exacerbated HFD-induced macrophage infiltration and proinflammatory genes in epididymal white adipose tissue (eWAT). BMRKO-HFD mice also manifested significantly increased liver weights and hepatic lipid accumulation, an increasing trend of genes related to lipogenesis and lipid uptake, and significantly decreased genes related to lipolytic and fatty acid oxidation in the liver. Finally, the level of insulin-induced AKT phosphorylation was substantially blunted in eWAT but not liver or skeletal muscle of BMRKO-HFD mice compared with LC-HFD mice. These data suggest that BAT MR is required to maintain metabolic homeostasis, likely through its regulation of fatty acid metabolism in BAT and impacts on eWAT and liver.

Background: Human Cytomegalovirus virus (HCMV) is a worldwide virus that causes no serious symptoms in most adults. However, HCMV infection during pregnancy, it may lead to a series of serious complications, such as hearing loss, mental retardation, visual impairment, microcephaly and developmental retardation. Aim: The aim of this study was to develop a simple, low dependence on equipment and accurate method for HCMV detection based on the recombinase polymerase amplification (RPA) and lateral flow chromatography strip (LFS) reading. Methods: In order to meet the feasibility of HCMV early screening, three pairs of RPA primers were designed based on the UL123 gene encoding IE1, which was expressed immediately in the early stage of HCMV. In order to improve the specificity of the reaction and satisfy the visual detection, a specific probe was designed to insert THF site between upstream and downstream primers, fluorescein isothiocyanate (FITC) and C3spacer were used to modify the 5′ end and the 3′ end respectively, and Biotin was used to modify the 5′ end of the reverse primer. HCMV standard strain AD169 was enriched by ARPE-19 cells culture, and its genome was extracted. The primers and probes were screened by RPA-LFS test, and the optimal reaction temperature and time were determined The specificity was verified in different viruses, bacteria and parasites. The standard curve was drawn based on the constructed recombinant plasmid of pMD18T-HCMV-UL123 and used for HCMV genomic DNA quantification and determination of the detection sensitivity. Urine samples from artificial HCMV contamination or clinical collection were prepared to evaluate the consistency with the results of real-time quantitative PCR. Results: The results showed that the primers and probes for HCMV RPA-LFS detection based on UL123 gene were successfully screened, the amplification of HCMV genomic DNA with as low as 30 copies could be completed at 37 °C within 15 min, it did not react with Human herpesvirus 1, Streptococcus pyogenes, Candida albicans, Listeria monocytogenes, Y. enterocolitica, Klebsiella Pneumoniae, Enterobacter cloacae, Citrobacter freundii, Vibrio alginnolyfificus, Vibrio parahaemolyticus, S. typhimurium, Staphylococcus aureus, Pseudomonas aeruginosa and Trichomonas vaginalis. The positive rate of PCR was 96.67 % in 30 simulated urine samples and 100 % in 127 clinical urine samples with the same UL123 gene detection. Conclusions: To sum up, we developed a diagnostic method for HCMV based on UL123 gene combined with RPA and LFS, which is low dependent on equipment, fast, sensitive and specific, provide reference for point-of-care testing HCMV in grass-roots laboratories and remote areas.

Introduction: Obesity has detrimental influences on women reproductive health. There is little experience in optimizing controlled ovarian hyperstimulation (COH) protocols to treat Chinese obese patients who are undergoing in vitro fertilization and embryo transfer (IVF-ET) therapy. Methods: The clinical outcome differences were retrospectively analyzed among obese patients who received gonadotrophin-releasing hormone agonist (GnRH-a), GnRH antagonist (GnRH-ant), micro dose GnRH-a (mGnRH-a) and GnRH-a long protocol in IVF-ET cycle at Chengdu Jinjiang Hospital for Women's and Children's Health from January 2014 to December 2019. Results: The transplantation rate of the GnRH-a long protocol group (59.1%) was higher than that of the GnRH-ant (25.9%) and mGnRH-a (36.7%) groups. The total live birth rate of the GnRH-a long protocol group (46.2%) was higher than that of the GnRH-a group (25.9%) and GnRH-ant group (40.3%). The total number of frozen embryos in the GnRH-ant group was higher than in the other groups (P

Abstract Learning from video lectures is becoming a prevalent learning activity in formal and informal settings. However, relatively little research has been carried out on the interactions of learning strategies and social environment in learning from video lectures. The present study addresses this gap by examining whether learner-generated explanations and co-learner presence with or without nonverbal praise independently and interactively affected learning from a self-paced video lecture about infectious diseases. University students were randomized into viewing either the video with instructor-generated explanations or the same video but generating explanations themselves. Outcomes were assessed by the quality of explanations, learning performance, mental effort, attention allocation, and behavioral patterns. Between-group comparisons showed that, in the absence of a peer co-learner, learning performance was similar in both the instructor-generated and learner-generated explanation groups. However, in the presence of a peer, learner-generated explanation facilitated learning performance. Furthermore, learner-generated explanation in the presence of a co-learner also reduced learners’ mental effort and primed more behaviors related to self-regulation and monitoring. The results lead to the following strong recommendation for educational practice when using video lectures: if students learn by generating their own explanations in the presence of a co-learner, they will show better learning performance even though the learning is not necessarily more demanding, and will engage in more behaviors related to explanation adjustment and self-regulation.

Abstract Preeclampsia (PE) is a multisystemic and placental inflammatory disease that causes maternal and infant health issues. As one of the active components in peony root extract, paeonol (Pae) exerts anti‐apoptosis and anti‐inflammatory effects. Nonetheless, the protective role of Pae in PE has not yet been characterized. A mouse model of PE was constructed through tail vein injection of 1 mg/d phosphatidylserine/dioleoyl‐phosphatidycholine suspension. The levels of inflammatory cytokines in the placenta were examined via enzyme‐linked immunosorbent assay (ELISA). The mRNA levels of inflammatory cytokines (TNF‐α, IL‐6, IFN‐γ, and IL‐4) and apoptosis markers (Bax, Bcl‐2, and caspase‐3) were tested using quantitative reverse transcription‐polymerase chain reaction (qRT–PCR). Western blot analysis was performed to detect the protein levels of apoptosis markers and Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway‐related molecules. Here, Pae repressed the inflammatory response in the placenta of PE‐like mouse models, as demonstrated by the decreased concentrations and mRNA levels of TNF‐α, IL‐6, and IFN‐γ and the increased concentrations and mRNA levels of IL‐4. Apoptosis in the placentas of PE‐like mouse models was attenuated by Pae, as manifested by the downregulated mRNA and protein levels of Bax and cleaved‐caspase‐3 and the upregulated Bcl‐2. Administration of Pae inhibited the phosphorylation of JAK2 and STAT3 in the placental tissues of PE mice. The JAK2/STAT3 pathway agonist (SC‐39100) reversed Pae treatment‐mediated suppression of placental inflammation and apoptosis in PE mice. Overall, Pae inhibits the JAK2/STAT3 signaling pathway to attenuate placental inflammation and apoptosis in PE mice.

Introduction Mesenteric lymph nodes (MLNs) are central in immune anatomy. MLNs are associated with the composition of gut microbiota, affecting the central system and immune system. Gut microbiota was found to differ among individuals of different social hierarchies. Nowadays, excision of MLNs is more frequently involved in gastrointestinal surgery; however, the potential side effects of excision of MLNs on social dominance are still unknown. Methods MLNs were removed from male mice (7–8 weeks old). Four weeks after MLN removal, social dominance test was performed to investigate social dominance; hippocampal and serum interleukin (IL)‐1β, IL‐10, and tumor necrosis factor‐alpha (TNF‐α) were investigated; and histopathology was used to evaluate local inflammation of the ileum. The composition of the gut microbiota was then examined to understand the possible mechanism, and finally intraperitoneal injection of IL‐10 was used to validate the effect of IL‐10 on social dominance. Results There was a decrease in social dominance in the operation group compared to the control group, as well as a decrease in serum and hippocampal IL‐10 levels, but no difference in serum and hippocampal IL‐1β and TNF‐α levels, and no local inflammation of the ileum after MLN removal. 16S rRNA sequencing analysis showed that the relative abundance of the class Clostridia was decreased in the operation group. This decrease was positively associated with serum IL‐10 levels. Furthermore, intraperitoneal injection of IL‐10 in a subset of mice increased social dominance. Conclusions Our findings suggested that MLNs contributed to maintaining social dominance, which might be associated with reduced IL‐10 and the imbalance of specific flora in gut microbiota.

Abstract Fluorescent probes for detection of CN− still have many limitations, such as small Stokes shift, irreversible, and background interference, which hamper their applications for on‐site detection and bioimaging of CN−. In this work, we design a new CN−‐activatable fluorescent probe (named AHMM) containing an ESIPT (excited‐state intramolecular proton transfer) and hydrogen bond features, which show a large Stokes shift (225 nm) and molecular structural reversible detection. The probe AHMM exhibits an excellent selectivity for CN− without any interference from other anions in aqueous DMSO system. Furthermore, the mechanism of the interaction of AHMM with CN− is concluded by various experiments. The limit of detection of AHMM for CN− is calculated as low as 4.47 × 10−8 M, lower than the concentration of CN− deemed acceptable by WHO (World Health Organization). AHMM can recognize CN− in tap water quantitatively and on‐site by a smartphone APP. Moreover, food samples such as almond and cassava including CN− are visualized by fluorescence imaging. In addition, the probe shows practical applications of CN− imaging in cells and mice. This concept can be applied for designing multifunctional fluorescent probes with ESIPT and reversible characteristics for detection of CN−.

IntroductionDepression commonly occurs during pregnancy and has become a major public health concern. Depression not only affects the individual but also causes adverse consequences for families and children. However, little is known regarding the depression status and its influencing factors in women during late pregnancy in China. This study aimed to assess the prevalence of maternal depressive symptoms in late pregnancy during the coronavirus disease 2019 (COVID-19) pandemic and further explore the effect of biological, psychological, and social factors on depressive symptoms.MethodsAn institution-based cross-sectional survey was conducted among eligible women in the late pregnancy stage and underwent prenatal examination at Lianyungang Maternal and Child Health Hospital in Jiangsu Province, Eastern China from December 2022 to February 2023. Data regarding depressive symptoms and biological, psychological, and social factors of the pregnant women were collected via a structured questionnaire. Chi-square test, Fisher's exact tests, and binary logistics regression were used to analyze the data.ResultsIn total, 535 women in the late pregnancy stage were included in this study, 75 (14.0%) of whom exhibited depressive symptoms. A binary logistic regression analysis revealed that pregnant women who were multiparous (OR: 2.420, 95% CI: 1.188–4.932) and had moderate or severe insomnia symptoms (OR: 4.641, 95% CI: 1.787–12.057), anxiety (OR: 8.879, 95% CI: 4.387–17.971), high fear of COVID-19 (OR: 2.555, 95% CI: 1.255–5.199), moderate or severe family dysfunction (OR: 2.256, 95% CI: 1.141–4.461), and poor social support (OR: 2.580, 95% CI: 1.050–6.337) tended to show depressive symptoms. Conversely, pregnant women who received regular prenatal care (OR: 0.481, 95% CI: 0.243–0.951) and had good drinking water quality at home (OR: 0.493, 95% CI: 0.247–0.984) were more likely to avoid developing depressive symptoms.ConclusionThis study found that the prevalence of maternal depressive symptoms during late pregnancy was high and had multiple influencing factors. Thus, screening for depressive symptoms in women in the late pregnancy stage and providing special intervention programs are necessary, especially for those with risk factors.

Aurantii Fructus (AF) and Aurantii Fructus Immaturus (AFI) have been used for thousands of years as traditional Chinese medicine (TCM) with sedative effects. Modern studies have shown that Citrus plants also have protective effects on the nervous system. However, the effective substances and mechanisms of action in Citrus TCMs still remain unclear. In order to explore the pharmacodynamic profiles of identified substances and the action mechanism of these herbs, a comprehensive approach combining ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS/MS) analysis and network pharmacology was employed. Firstly, UNIFI 2.1.1 software was used to identify the chemical characteristics of AF and AFI. Secondly, the SwissTargetPrediction database was used to predict the targets of chemical components in AF and AFI. Targets for neuroprotection were also collected from GeneCards: The Human Gene Database (GeneCards-Human Genes|Gene Database|Gene Search). The networks between targets and compounds or diseases were then constructed using Cytoscape 3.9.1. Finally, the Annotation, Visualization and Integrated Discovery Database (DAVID) (DAVID Functional Annotation Bioinformatics Microarray Analysis) was used for GO and pathway enrichment analysis. The results showed that 50 of 188 compounds in AF and AFI may have neuroprotective biological activities. These activities are associated with the regulatory effects of related components on 146 important signaling pathways, derived from the KEGG (KEGG: Kyoto Encyclopedia of Genes and Genomes), such as neurodegeneration (hsa05022), the Alzheimer’s disease pathway (hsa05010), the NF-kappa B signaling pathway (hsa04064), the hypoxia-inducible factor (HIF)-1 signaling pathway (hsa04066), apoptosis (hsa04210), the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance signaling pathway (hsa01521), and others, by targeting 108 proteins, including xanthine dehydrogenase (XDH), glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B), and glucose-6-phosphate dehydrogenase (G6PD), among others. These targets are thought to be related to inflammation, neural function and cell growth.

Although the catalytic pyrolysis of low-density polyethylene (LDPE) to produce light olefin has shown potential industrial application advantages, it has generally suffered when using higher pyrolysis temperatures. In this work, Mg-modified Fe-ZSM-5 was used for catalytic conversion of LDPE to obtain light olefin in a fixed bed reactor. The effects of catalyst types, pyrolysis temperatures, and Mg loading on the yield of light olefin were investigated. The 1 wt% Mg loading slightly improved the yield of light olefin to 38.87 wt% at 395 °C, lowering the temperature of the pyrolysis reaction. We considered that the higher light olefin yield of Fe-Mg-ZSM-5 was attributed to the introduction of Mg, where Mg regulated the surface acidity of the catalyst, inhibited the secondary cracking reaction, and reduced coking during the pyrolysis process. Furthermore, the addition of Mg also dramatically reduced the average particle size of Fe oxides from 40 nm to 10 nm, which is conducive to a lower catalytic reaction temperature. Finally, the spent catalyst could be easily regenerated at the conditions of 600 °C in airflow with a heating rate of 10 °C/min for 1 h, and the light olefin yield remained higher than 36.71 wt% after five cycles, indicating its excellent regeneration performance.

Abstract Background Insect metamorphosis from larvae to pupae is one of the most important stages of insect life history. Relatively comprehensive information related to gene transcription profiles during lepidopteran metamorphosis is required to understand the molecular mechanism underlying this important stage. We conducted transcriptional profiling of the brain and fat body of the cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) during its transition from last instar larva into pupa to explore the physiological processes associated with different phases of metamorphosis. Results During metamorphosis, the differences in gene expression patterns and the number of differentially expressed genes in the fat body were found to be greater than those in the brain. Each stage had a specific gene expression pattern, which contributed to different physiological changes. A decrease in juvenile hormone levels at the feeding stage is associated with increased expression levels of two genes (juvenile hormone esterase, juvenile hormone epoxide hydrolase). The expression levels of neuropeptides were highly expressed at the feeding stage and the initiation of the wandering stage and less expressed at the prepupal stage and the initiation of the pupal stage. The transcription levels of many hormone (or neuropeptide) receptors were specifically increased at the initiation of the wandering stage in comparison with other stages. The expression levels of many autophagy-related genes in the fat body were found to be gradually upregulated during metamorphosis. The activation of apoptosis was probably related to enhanced expression of many key genes (Apaf1, IAP-binding motif 1 like, cathepsins, caspases). Active proliferation might be associated with enhanced expression levels in several factors (JNK pathway: jun-D; TGF-β pathway: decapentaplegic, glass bottom boat; insulin pathway: insulin-like peptides from the fat body; Wnt pathway: wntless, TCF/Pangolin). Conclusions This study revealed several vital physiological processes and molecular events of metamorphosis and provided valuable information for illustrating the process of insect metamorphosis from larvae to pupae.

Abstract Multipath interference seriously degrades the performance of Global Navigation Satellite System (GNSS) positioning in an urban canyon. Most current multipath mitigation algorithms suffer from heavy computational load or need external assistance. We propose a multipath mitigation algorithm based on the steepest descent approach, which has the merits of less computational load and no need for external aid. A new ranging code tracking loop is designed based on the steepest descent method, which can save an early branch or a late branch compared with the narrow-spacing correlation method. The power of the Non-Line-of-Sight (NLOS) signal is weaker than that of the Line-of-Sight (LOS) signal when the LOS signal is not obstructed and with a relatively high Carrier Noise Ratio (CNR). The peak position in the X-axis of the ranging code autocorrelation function does not move with the NLOS interference. Meanwhile, the cost function is designed according to this phenomenon. The results demonstrate that the proposed algorithm outperforms the narrow-spacing correlation and the Multipath Estimated Delay Locked Loop (MEDLL) in terms of the code multipath mitigation and computation time. The Standard Deviation (STD) of the tracking error with the proposed algorithm is less than 0.016 chips. Moreover, the computation time of the proposed algorithm in a software defined receiver is shortened by 24.21% compared with the narrow-spacing correlation.

Plutella xylostella granulovirus (PlxyGV) biopesticide is an effective tool to control the long-term damage of Plutella xylostella (Linnaeus) to cruciferous vegetables. In China, PlxyGV can be produced on a large scale using host insects, and its products have been registered in 2008. In experiments and biopesticide production, the routine enumeration method of PlxyGV virus particles is to use the Petroff-Hausser counting chamber in dark field microscope. However, the accuracy and repeatability of granulovirus (GV) counting are affected due to the small particle size of GV occlusion bodies (OBs), the limitations of optical microscope, the judgment of different operators, host impurities, the addition of biological products. This limits the convenience of its production, product quality, trading and field application. Here we use PlxyGV as an example, the method based on Real-time fluorescence quantitative PCR (qPCR) was optimized from two aspects of sample treatment and specific primers design, which improved the repeatability and accuracy of absolute quantitative OBs of GV. This study provides basic information for accurate quantitative PlxyGV by qPCR method.

Abstract Background Antibodies against the 65-kDa isoform of glutamic acid decarboxylase (GAD65) are biomarkers of autoimmune disorders and are more common in non-neurological autoimmune diseases than in neurological disorders. As for the central nervous system (CNS), it is well known that GAD65 is primarily associated with stiff-person syndrome, cerebellar ataxia, epilepsy, and paraneoplastic neurological syndrome. However, GAD65 antibodies have not been reported in patients with brain tumors. Case presentation This study presents the case of a 62-year-old man who manifested rapidly progressive dizziness with gradually worsening physical disturbance and unstable gait in the 2 months prior to consultation. Antibodies against GAD65 were detected in his serum. Brain magnetic resonance imaging (MRI) showed abnormal signals in the corpus callosum, the semi-oval center in both hemispheres, and the area below the frontal cortex, along with enhanced intracranial lesions in the same regions. Positron emission tomography–computed tomography (PET–CT) showed high metabolism in the corpus callosum, which protruded into both ventricles. Due to signs of malignancy, the patient was diagnosed with a malignant glioma. Conclusions This case raises awareness on the fact that anti-GAD65 antibodies may be associated with CNS neoplastic lesions. Early recognition of anti-GAD antibodies could be of great importance for the early diagnosis and targeted treatment of neoplastic lesions, and could lead to better prognosis.

Abstract Background In frozen embryo transfer (FET), there is limited consensus on the best means of endometrial preparation in terms of the reproductive outcomes in women with polycystic ovary syndrome (PCOS). The present study aimed to compare the pregnancy and neonatal outcomes following artificial cycle FET (AC-FET) with or without gonadotropin-releasing hormone agonist (GnRH-a) pretreatment among women with PCOS. Methods A total of 4503 FET cycles that satisfied the inclusion criteria were enrolled in this retrospective cohort study between 2015 and 2020. The GnRH-a group received GnRH-a pretreatment while the AC-FET group did not. Propensity score matching (PSM) method and multivariate logistic regression analysis were performed to adjust for potential confounding factors. Results After PSM, women in the GnRH-a group suffered a significantly lower miscarriage rate (11.2% vs. 17.1%, P = 0.033) and a higher live birth rate (LBR) compared with those in the AC-FET group (63.1% vs. 56.8%, P = 0.043). No differences were observed in the rates of biochemical pregnancy, clinical pregnancy and ectopic pregnancy between the two groups. A higher mean gestational age at birth was observed in the GnRH-a group than in the AC-FET group (39.80 ± 2.01 vs. 38.17 ± 2.13, P = 0.009). The incidence of neonatal preterm birth (PTB) in the GnRH-a group was lower than that in the AC-FET group (7.4% vs. 14.9%, P = 0.009). Singleton newborns conceived after GnRH-a group were more likely to be small for gestational age (SGA) than those born after AC-FET group (16.4% vs. 6.8%, P = 0.009). However, no significant differences were found between the two groups in terms of mean birthweight, apgar score, the rates of macrosomia, large for gestational age and low birth weight. Conclusion(s) In women with PCOS who underwent AC-FET, GnRH-a pretreatment was significantly associated with a higher live birth rate and a reduced risk of neonatal PTB. However, there was a concomitant increase in the risk of developing SGA babies.

The management of dysfunctional intestinal epithelium by promoting mucosal healing and modulating the gut microbiota represents a novel therapeutic strategy for inflammatory bowel disease (IBD). As a convenient and well‐tolerated method of drug delivery, intrarectal administration may represent a viable alternative to oral administration for the treatment of IBD. Here, a biomimetic supramolecular assembly of hyaluronic acid (HA) and β‐cyclodextrin (HA‐β‐CD) for the delivery of the C domain peptide of insulin‐like growth factor‐1 (IGF‐1C), which gradually releases IGF‐1C, is developed. It is identified that the supramolecular assembly of HA‐β‐CD enhances the stability and prolongs the release of IGF‐1C. Furthermore, this biomimetic supramolecular assembly potently inhibits the inflammatory response, thereby restoring intestinal barrier integrity. Following HA‐β‐CD‐IGF‐1C administration, 16S rDNA sequencing reveals a significant increase in the abundance of the probiotic Akkermansia, suggesting enhanced intestinal microbiome homeostasis. In conclusion, the findings demonstrate the promise of the HA‐based mimicking peptide delivery platform as a therapeutic approach for IBD. This biomimetic supramolecular assembly effectively ameliorates intestinal barrier function and intestinal microbiome homeostasis, suggesting its potential for treating IBD. [ABSTRACT FROM AUTHOR]

Ophiocordyceps sinensis exhibits more than 5 months of vegetative growth in Thitarodes xiaojinensis hemocoel. The peculiar development process of O. sinensis has been elucidated through morphological observation and omics technology; however, little information has been reported regarding the changes that occur in the host T. xiaojinensis. The RNA sequencing data showed that when O. sinensis blastospores were in the proliferative stage, the greatest change in the infected larval fat body was the selectively upregulated immune recognition and antimicrobial peptide genes. When O. sinensis blastospores were in the stationary stage, the immune pathways of T. xiaojinensis reverted to normal levels, which coincides with the successful settlement of O. sinensis. Pathway enrichment analysis showed a higher expression of genes involved in energy metabolism pathway in this stage. Metabolomic analyses revealed a reduction of amino acids and lipids in hemolymph, but an upregulation of lipids in the fat body of the host larvae after O. sinensis infection. We present the first transcriptome integrated with the metabolome study of T. xiaojinensis infected by O. sinensis. It will improve our understanding of the interaction mechanisms between the host and entomopathogenic fungi, and facilitate future functional studies of genes and pathways involved in these interactions.

Since traditional matrix factorization algorithms are mostly based on shallow linear models,it is difficult to learn latent factors of users and items at a deep level.When the dataset is sparse,it is inclined to overfitting.To deal with the problem,this paper proposes a biased deep distance factorization algorithm,which can not only solve the data sparse problem,but also learn the distance feature vectors with stronger characterization capabilities.Firstly,the interaction matrix is constructed through the explicit and implicit data of the user and the item.Then the interaction matrix is converted into the corresponding distance matrix.Secondly,the distance matrix is input into the depth of the bias layer by row and column respectively.The neural network learns the distance feature vectors of users and items with non-linear features.Finally,the distance between the user and the item is calculated according to the distance feature vectors.Top-N item recommended list is generated according to the distance value.The experimental results show that Precision,Recall,MAP,MRR and NDCG of this algorithm are significantly improved compared to other mainstream recommendation algorithms on four different datasets.