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Abstract This study examines the nexus between external shocks and micro-transmission aspects of volatility persistence and market efficiency for the Malawian Foreign exchange market. Garch-type models are employed on monthly data stretching back to June 2011 through to October 2021. Results of the study show the presence of two structural breaks for the volatility series and one structural break for the return series that fall within the rolling window for external shock associated with the Russia-Ukrainian war. The negative nature of the shock leads to a significant additive impact on volatility persistence, asymmetry, and threshold at different levels of significance in the three models of Garch, E-Garch and T-Garch respectively. Relaxing the models confirms the presence of domestic influence. However, the external influence remains significant especially for the negative shock. As such, the leverage and volatility feedback effects of external shocks are corroborated. Augmenting the approach with a FRUH analysis reveals that the foreign exchange market does not follow a random walk as it departs from the 1:1 relationship between the spot and forward rate thus being weak-form inefficient.

Background The implementation of standardized teaching clinic activities by the faculty of standardized training of general practice residents (hereinafter referred to as residency training) is a key link in the cultivation of qualified general practitioners. And in July 2021, the Chinese Physicians' Association organized experts to revise the Specification for General Practice Teaching Clinic for Standardized Training of Residents in the Specialty of General Practice (for Trial Implementation), which is referenced by all the residency training bases of general practice across the country to carry out the teaching clinic. However, at this stage, the implementation of teaching clinic in each residency training base is still in the exploratory stage, and the degree of attention is insufficient, and the phenomenon of low quality and irregularity in the form of teaching clinic prevails. Objective To understand the current situation and influencing factors on the willingness of general practice residency faculty to conduct teaching clinics, not only to analyze the difficulties and confusions in conducting teaching clinics, but also provide reflections and recommendations. Methods From October 2021 to November 2023, a survey was conducted among general practitioners who participated in the provincial-level general practice residency training programs for regular and key instructors in Guangdong Province. A self-designed questionnaire was used to collect data from the included instructors, covering their basic information, work situation, and their willingness to teach. The electronic questionnaire was created using the "Questionnaire Star" platform, which also facilitated the online distribution and collection of the survey. Results The average age of general practice faculty was (40.7±14.1) years, 724 (72.18%) faculty members' institutions had general practice teaching clinics, 792 (78.96%) had a desire to teach, 710 (70.79%) had no experience in teaching, 904 (90.13%) had self-assessed their competence in teaching as a score of 60-89, and 583 (58.13%) had received no general practice teaching clinic faculty training, 462 (46.06%) expected faculty training to be conducted in the form of a combination of multiple types of training, 417 (41.58%) and 309 (30.81%), respectively, believed that the teaching difficulty of general practice teaching clinics was to instruct general practice residents to independently receive patients in the general practice clinic and to teach in a tiered manner, and 377 (37.59%) believed that the most difficult teaching objective to achieve was to instruct general practice residents in general practice clinical thinking and improve their clinical decision-making skills, 216 (21.54%) believed that the most needed training component for general practice residents was consultation skills, and 456 (45.46%) believed that the reason their institution did not/would not conduct a teaching clinic was lack of time. Also, the results of the multifactorial logistic regression analysis showed that the availability of general practice teaching clinics at the institution where they are located, experience in teaching, self-assessment of teaching competence, and acceptance of faculty training in general practice teaching clinics were the factors influencing the willingness to teach in general practice faculty teaching clinics (P

Abstract In this paper, we propose an efficient target detection algorithm, ASF-Sim-YOLO, to address issues encountered in escalator step defect detection, such as an excessive number of parameters in the detection network model, poor adaptability, and difficulties in real-time processing of video streams. Firstly, to address the characteristics of escalator step defects, we designed the ASF-Sim-P2 structure to improve the detection accuracy of small targets, such as step defects. Additionally, we incorporated the SimAM (Similarity-based Attention Mechanism) by combining SimAM with SPPF (Spatial Pyramid Pooling-Fast) to enhance the model’s ability to capture key information by assigning importance weights to each pixel. Furthermore, to address the challenge posed by the small size of step defects, we replaced the traditional CIoU (Complete-Intersection-over-Union) loss function with NWD (Normalized Wasserstein Distance), which alleviated the problem of defect missing. Finally, to meet the deployment requirements of mobile devices, we performed channel pruning on the model. The experimental results showed that the improved ASF-Sim-YOLO model achieved an average accuracy (mAP50) of 96.8% on the test data set, which was a 22.1% improvement in accuracy compared to the baseline model. Meanwhile, the computational complexity (in GFLOPS) of the model was reduced to a quarter of that of the baseline model, while the frame rate (FPS) was improved to 575.1. Compared with YOLOv3-tiny, YOLOv5s, YOLOv8s, Faster-RCNN, TOOD, RTMDET and other deep learning-based target recognition algorithms, ASF-Sim-YOLO has better detection accuracy and real-time processing capability. These results demonstrate that ASF-Sim-YOLO effectively balances lightweight design and performance improvement, making it highly suitable for real-time detection of step defects, which can meet the demands of escalator inspection operations.

Abstract Digital Micromirror Devices, extensively employed in projection displays offer rapid, polarization-independent beam steering. However, they are constrained by microelectromechanical system limitations, resulting in reduced resolution, limited beam steering angle and poor stability, which hinder further performance optimization. Liquid Crystal on Silicon technology, employing liquid crystal (LC) and silicon chip technology, with properties of high resolution, high contrast and good stability. Nevertheless, its polarization-dependent issues lead to complex system and low efficiency in device applications. This paper introduces a hybrid integration of metallic metasurface with nematic LC, facilitating a polarization-independent beam steering device capable of large-angle deflections. Employing principles of geometrical phase and plasmonic resonances, the metallic metasurface, coupled with an electronically controlled LC, allows for dynamic adjustment, achieving a maximum deflection of ± 27.1°. Additionally, the integration of an LC-infused dielectric grating for dynamic phase modulation and the metasurface for polarization conversion ensures uniform modulation effects across all polarizations within the device. We verify the device’s large-angle beam deflection capability and polarization insensitivity effect in simulations and propose an optimization scheme to cope with the low efficiency of individual diffraction stages.

Abstract Background Muscle atrophy is a typical affliction in patients affected by knee Osteoarthritis (KOA). This study aimed to examine the potential pathogenesis and biomarkers that coalesce to induce muscle atrophy, primarily through the utilization of bioinformatics analysis. Methods Two distinct public datasets of osteoarthritis and muscle atrophy (GSE82107 and GSE205431) were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA) to probe for common differentially expressed genes (DEGs) and conduct transcription factor (TF) enrichment analysis from such genes. Venn diagrams were used to identify the target TF, followed by the construction of a protein-protein interaction (PPI) network of the common DEGs governed by the target TF. Hub genes were determined through the CytoHubba plug-in whilst their biological functions were assessed using GSEA analysis in the GTEx database. To validate the study, reverse transcriptase real-time quantitative polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and Flow Cytometry techniques were employed. Results A total of 138 common DEGs of osteoarthritis and muscle atrophy were identified, with 16 TFs exhibiting notable expression patterns in both datasets. Venn diagram analysis identified early growth response gene-1 (EGR1) as the target TF, enriched in critical pathways such as epithelial mesenchymal transition, tumor necrosis factor-alpha signaling NF-κB, and inflammatory response. PPI analysis revealed five hub genes, including EGR1, FOS, FOSB, KLF2, and JUNB. The reliability of EGR1 was confirmed by validation testing, corroborating bioinformatics analysis trends. Conclusions EGR1, FOS, FOSB, KLF2, and JUNB are intricately involved in muscle atrophy development. High EGR1 expression directly regulated these hub genes, significantly influencing postoperative muscle atrophy progression in KOA patients.

Thermal-hydraulic phenomenon of coolant in the primary circuit of pool type fast reactor under accident decay heat removal conditions is complicated because the layout of direct heat exchanger. In order to further understand the behavior natural circulation of coolant in primary circuit system of pool type fast reactor under accident decay heat removal conditions, a visual slab water model was established to simulate main component in primary circuit system and natural circulation experiments had been carried out on this model. Temperature response and flow field of coolant in core, pool and inlet and outlet of each heat exchanger were obtained. According to the transient temperature at the inlet and outlet of core assembly, in the initial stage of establish of natural circulation, the temperature at outlet remained relatively stable for a short period of time without increasing. After the temperature of cold pool rise, the temperature at outlet of core started to increase. So the cold pool has a significant impact on the temperature rise rate of short term natural circulation. In this experiment, the natural circulation flow in the intermediate heat exchanger and inter-wrapper space of core was observed. The higher temperature fluid from outlet of core floats directly to the top of hot pool and lower temperature fluid in the hot pool sinks, which forming a local circulation flow in hot pool. Due to the intermediate heat exchanger loses its ability of heat transfer, the temperature of cold pool becomes higher and higher, with the development of natural circulation, and finally, temperatures of inlet and outlet of intermediate heat exchanger and cold pool are relatively close when the flow reaches to a stable state. Under influence of hot water form core and cold water from outlet of direct heat exchanger, a thermal stratification is formed and the position of interface of hot water and cold water is near top of the core. In this experiment, mixing of hot water and cold water is observed in the top of core, which forms significant temperature fluctuations, even in the place 20 mm below the outlet in the core assembly, this fluctuation still exists, indicating that the mixing effect can penetrate into the interior of the core assembly, which may cause a disadvantage to the establishing and maintaining of natural circulation through the core. All this result can enable us to fully understand the mechanism of natural circulation and provide support for the improvement of models in system analysis code.

The aim of this study was to compare the accuracies of cognitive fusion-guided targeted biopsy (TB), systematic biopsy (SB), and combined TB+SB for the detection of prostate cancer (PCa) and clinically significant PCa (csPCa) in males with lesions detected by magnetic resonance imaging (MRI). We conducted a retrospective analysis of individuals who underwent prostate biopsy at Peking University People’s Hospital (Beijing, China), with an emphasis on patients with both transrectal TB and SB. The main objective was to determine the precisions of SB, TB, and TB+SB for diagnosing PCa and csPCa. We also evaluated the detection rates of TB, SB, TB+ipsilateral-SB (ipsi-SB), TB+contralateral-SB (contra-SB), and TB+SB for PCa and csPCa in patients with unilateral MRI lesions. We compared the diagnostic yields of the various biopsy schemes using the McNemar’s test. A total of 180 patients were enrolled. The rates of PCa detection using TB, SB, and TB+SB were 52.8%, 62.2%, and 66.7%, respectively, and the corresponding rates for csPCa were 46.1%, 56.7%, and 58.3%, respectively. Among patients with unilateral MRI lesions, the PCa detection rates for TB, SB, TB+ipsi-SB, TB+contra-SB, and TB+SB were 53.3%, 64.8%, 65.6%, 61.5%, and 68.0%, respectively. TB+ipsi-SB detected 96.4% of PCa and 95.9% of csPCa cases. These findings suggest that the combination of TB+SB has better diagnostic accuracy compared with SB or TB alone. For patients with unilateral MRI lesions, the combination of TB+ipsi-SB may be suitable in clinical settings.

Vitamin B2 is an essential water-soluble vitamin. For most prokaryotes, a bifunctional enzyme called FAD synthase catalyzes the successive conversion of riboflavin to FMN and FAD. In this study, the plasmid pNEW-AZ containing six key genes for the riboflavin synthesis was transformed into strain R2 with the deleted FMN riboswitch, yielding strain R5. The R5 strain could produce 540.23 ± 5.40 mg/L riboflavin, which was 10.61 % higher than the R4 strain containing plasmids pET-AE and pAC-Z harboring six key genes. To further enhance the production of riboflavin, homology matching and molecular docking were performed to identify key amino acid residues of FAD synthase. Nine point mutation sites were identified. By comparing riboflavin kinase activity, mutations of T203D and N210D, which respectively decreased by 29.90 % and 89.32 % compared to wild-type FAD synthase, were selected for CRISPR/Cas9 gene editing of the genome, generating engineered strains R203 and R210. pNEW-AZ was transformed into R203, generating R6. R6 produced 657.38 ± 47.48 mg/L riboflavin, a 21.69 % increase compared to R5. This study contributes to the high production of riboflavin in recombinant E. coli BL21.

Abstract Electrochemical methods with tissue-implantable microelectrodes provide an excellent platform for real-time monitoring the neurochemical dynamics in vivo due to their superior spatiotemporal resolution and high selectivity and sensitivity. Nevertheless, electrode implantation inevitably damages the brain tissue, upregulates reactive oxygen species level, and triggers neuroinflammatory response, resulting in unreliable quantification of neurochemical events. Herein, we report a multifunctional sensing platform for inflammation-free in vivo analysis with atomic-level engineered Fe single-atom catalyst that functions as both single-atom nanozyme with antioxidative activity and electrode material for dopamine oxidation. Through high-temperature pyrolysis and catalytic performance screening, we fabricate a series of Fe single-atom nanozymes with different coordination configurations and find that the Fe single-atom nanozyme with FeN4 exhibits the highest activity toward mimicking catalase and superoxide dismutase as well as eliminating hydroxyl radical, while also featuring high electrode reactivity toward dopamine oxidation. These dual functions endow the single-atom nanozyme-based sensor with anti-inflammatory capabilities, enabling accurate dopamine sensing in living male rat brain. This study provides an avenue for designing inflammation-free electrochemical sensing platforms with atomic-precision engineered single-atom catalysts.

Abstract Background Colorectal cancer is the third most common cancer and the second leading cause of cancer death. There are limited therapeutic options for the treatment of locally advanced or metastatic colorectal cancers which fail first-line chemotherapy. Phase I/II studies showed that the combined application of the raltitrexed and irinotecan has significant synergistic effect and acceptable toxicity. However, most of these previous studies have relatively small sample size. Methods This is a prospective open-label, single-arm, multi-center, Phase II trial. Brief inclusion criteria: patients were aged 18 to 75 years with locally advanced or metastatic colorectal cancer after failure of 5-FU and oxaliplatin therapy. Enrolled patients received raltitrexed (3 mg/m2, d1) and irinotecan (180 mg/m2, d1) each 21-day cycle until disease progression or unacceptable toxicity. The primary endpoint was progression-free survival, and the secondary endpoints were disease control rate, objective response rate, overall survival and safety. Results A total of 108 patients were enrolled between September 2016 and May 2020. The median age was 61 years, ECOG 1 score accounts for 67.6%, the rest were ECOG 0. A total of 502 cycles were completed, with an average of 4.6 cycles and a median of 4 cycles. 108 patients were evaluated, with an objective response rate of 17.6%, and disease control rate of 76.9%. The median follow-up time was 27 months (range:3.1–61.0 m) at data cut-off on March 2023. Median progression-free survival was 4.9 months (95% CI 4.1–5.7) and median overall survival was 13.1 months (95% CI 12.2–15.5). The most common adverse events that were elevated are alanine aminotransferase increased, aspartate aminotransferase increased, fatigue, diarrhoea, neutrocytopenia, thrombocytopenia, hypohemoglobin, and leukocytopenia. Most of the adverse events were Grade I/II, which were relieved after symptomatic treatment, and there were no treatment-related cardiotoxicities and deaths. Conclusions The combination of raltitrexed and irinotecan as second-line treatment for mCRC could be a reliable option after failure of standard 5-Fu-first-line chemotherapy in locally advanced or metastatic colorectal cancers, especially for patients with 5-FU intolerance (cardiac events or DPD deficiency patients). Trial registration ClinicalTrials.gov identifier: NCT03053167, registration date was 14/2/2017.

Academic development usually focuses on individuals, with activities bounded by institutional strategy. There is a lack of research exploring the emergence of cross-institutional communities of practice and their ability to offer opportunities for professional collaboration, particularly for underrepresented or marginalised groups. Our study highlights how, after a formal program, individuals from different institutions facilitated deeper connections, transcending hierarchical boundaries and nurturing a sense of trust. Drawing from our experiences, we examine the emergence of a collegiate group of academic women as a community of practice. Co-development through community-based relationships enable personal and professional growth outcomes including, but not limited to, promotion and esteem recognition.

In most practical applications, the feature space of the training datasets and the target domain datasets are inconsistent, or the data distribution between them is inconsistent, which leads to the problem of data starvation and makes it difficult for terminal devices to obtain high accurate results. Aiming at the problems of limited terminal device resources, low accuracy of data processing results, and unsatisfactory processing speed, a Heterogeneous Multi-access Edge Computing (MEC) Framework based on Transfer Learning (TL) is proposed, abbreviated as HMECF-TL. This framework adopts a cloud-edge-end three-layer architecture. It uses model transfer to optimize the Convolutional Neural Networks (CNN) model at each layer to achieve the goal of improving data processing speed and accuracy. Furthermore, a multi-agent Deep Reinforcement Learning Algorithm having Attention Mechanism (DRLAAM) is designed to further increase the timeliness performance of computation-intensive applications. The performance of HMECSF-TL framework is verified by simulation experiments, which not only reduces the delay by more than 24.66 %, but also improves the accuracy by more than 8.34 %. The framework not only increase the computing capacity to solve the shortage of terminal device resources, but also improve the quality of data processing to solve the problem of data starvation.

ABSTRACTBackground Recombinant protein vaccines are vital for broad protection against SARS-CoV-2 variants. This study assessed ReCOV as a booster in two Phase 2 trials.Research design and methods Study-1 involved subjects were randomized (1:1:1) to receive 20 μg ReCOV, 40 μg ReCOV, or an inactivated vaccine (COVILO®) in the United Arab Emirates. Study-2 participating individuals were randomized (1:1:1) to receive 20 μg ReCOV (pilot batch, ReCOV HA), 20 μg ReCOV (commercial batch, ReCOV TC), or 30 μg BNT162b2 (COMIRNATY®) in the Philippines. The primary immunogenicity objectives was to compare the geometric mean titer (GMT) and seroconversion rate (SCR) of neutralizing antibodies induced by one ReCOV booster dose with those of inactivated vaccine and BNT162b2, respectively, at 14 days post-booster.Results Heterologous ReCOV booster doses were safe and induced comparable immune responses to inactivated vaccines and BNT162b2 against Omicron variants and the prototype. They showed significant advantages in cross-neutralization against multiple SARS-CoV-2 variants, surpassing inactivated vaccines and BNT162b2, with good immune persistence.Conclusions Heterologous ReCOV boosting was safe and effective, showing promise in combating COVID-19. The study highlights ReCOV’s potential for enhanced protection, supported by strong cross-neutralization and immune persistence.Clinical Trial Registration Study-1, www.clinicaltrials.gov, identifier is NCT05323435; Study-2, www.clinicaltrials.gov, identifier is NCT05084989.

Abstract Background The impact of acrylamide (ACR) on learning and memory has garnered considerable attention. However, the targets and mechanisms are still unclear. Results Elongation factor 2 (eEF2) was significantly upregulated in the results of serum proteomics. Results from in vitro and in vivo experiments indicated a notable upregulation of Eukaryotic elongation factor 2 kinase (eEF2K), the sole kinase responsible for eEF2 phosphorylation, following exposure to ACR (P

Abstract Background The congenital ventricular outflow tract malformations (CVOTMs) is a major congenital heart diseases (CHDs) subtype, and its pathogenesis is complex and unclear. Lipid metabolic plays a crucial role in embryonic cardiovascular development. However, due to the limited types of detectable metabolites in previous studies, findings on lipid metabolic and CHDs are still inconsistent, and the possible mechanism of CHDs remains unclear. Methods The nest case-control study obtained subjects from the multicenter China Teratology Birth Cohort (CTBC), and maternal serum from the pregnant women enrolled during the first trimester was utilized. The subjects were divided into a discovery set and a validation set. The metabolomics of CVOTMs and normal fetuses were analyzed by targeted lipid metabolomics. Differential comparison, random forest and lasso regression were used to screen metabolic biomarkers. Results The lipid metabolites were distributed differentially between the cases and controls. Setting the selection criteria of P value 1.2 or

Abstract Background DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist. Results Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences’ AVITI and Illumina’s NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina’s NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms’ respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate. Conclusion These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Feature extraction and classification is a difficult area in motor imagery electroencephalogram (EEG) signal processing. In order to improve the classification accuracy of EEG signals, both a feature extraction method based on the combination of LMD-CSP and a classification algorithm based on the fusion of PSO-SVM are proposed. Firstly, the extended informax ICA algorithm is used to denoise the signal and reduce the influence of noise on the signal. Then, the pre-processed EEG signals are decomposed into multiple Product Function (PF) components by Local Mean Decomposition (LMD), and the most discriminative PF component is selected. Next, feature extraction is carried out from the selected PF components using the Common Space Pattern (CSP). Finally, the obtained features are input into a Support Vector Machine (SVM) classifier improved by Particle Swarm Optimization (PSO) for classification recognition. The experimental results show that compared with the traditional CSP-SVM method, CapsNet method, WPT-CSP+CNN method, FDCSP-SVM method, and EMD-CNN method, the classification accuracy of the proposed method is increased by 26.94 %, 14.9 %, 13.34 %, 8.34 % and 4.04 %, respectively. This further proves the superiority of the proposed method for EEG signal processing technology.

Abstract Background Owing to the widespread use of chemical pesticides to control agricultural pests, pesticide tolerance has become a serious problem. In recent years, it has been found that symbiotic bacteria are related to pesticides tolerance. To investigate the potential role of microorganisms in the pesticide tolerance of Chilo suppressalis, this study was conducted. Results The insect was fed with tetracycline and cefixime as the treatment group (TET and CFM, respectively), and did not add antibiotics in the control groups (CK). The 16S rDNA sequencing results showed that antibiotics reduced the diversity of C. suppressalis symbiotic microorganisms but did not affect their growth and development. In bioassays of the three C. suppressalis groups (TET, CFM, and CK), a 72 h LC50 fitting curve was calculated to determine whether long-term antibiotic feeding leads to a decrease in pesticide resistance. The CK group of C. suppressalis was used to determine the direct effect of antibiotics on pesticide tolerance using a mixture of antibiotics and pesticides. Indirect evidence suggests that antibiotics themselves did not affect the pesticide tolerance of C. suppressalis. The results confirmed that feeding C. suppressalis cefixime led to a decrease in the expression of potential tolerance genes to chlorantraniliprole. Conclusions This study reveals the impact of antibiotic induced changes in symbiotic microorganisms on the pesticide tolerance of C. suppressalis, laying the foundation for studying the interaction between C. suppressalis and microorganisms, and also providing new ideas for the prevention and control of C. suppressalis and the creation of new pesticides.

Abstract Background Primary ciliary dyskinesia (PCD) is an autosomal recessive hereditary disease characterized by recurrent respiratory infections. In clinical manifestations, DNAH5 (NM_001361.3) is one of the recessive pathogenic genes. Primary familial brain calcification (PFBC) is a neurodegenerative disease characterized by bilateral calcification in the basal ganglia and other brain regions. PFBC can be inherited in an autosomal dominant or recessive manner. A family with PCD caused by a DNAH5 compound heterozygous variant and PFBC caused by a MYORG homozygous variant was analyzed. Methods In this study, we recruited three generations of Han families with primary ciliary dyskinesia combined with primary familial brain calcification. Their clinical phenotype data were collected, next-generation sequencing was performed to screen suspected pathogenic mutations in the proband and segregation analysis of families was carried out by Sanger sequencing. The mutant and wild-type plasmids were constructed and transfected into HEK293T cells instantaneously, and splicing patterns were detected by Minigene splicing assay. The structure and function of mutations were analyzed by bioinformatics analysis. Results The clinical phenotypes of the proband (II10) and his sister (II8) were bronchiectasis, recurrent pulmonary infection, multiple symmetric calcifications of bilateral globus pallidus and cerebellar dentate nucleus, paranasal sinusitis in the whole group, and electron microscopy of bronchial mucosa showed that the ciliary axoneme was defective. There was also total visceral inversion in II10 but not in II8. A novel splice variant C.13,338 + 5G > C and a frameshift variant C.4314delT (p. Asn1438lysfs *10) were found in the DNAH5 gene in proband (II10) and II8. c.347_348dupCTGGCCTTCCGC homozygous insertion variation was found in the MYORG of the proband. The two pathogenic genes were co-segregated in the family. Minigene showed that DNAH5 c.13,338 + 5G > C has two abnormal splicing modes: One is that part of the intron bases where the mutation site located is translated, resulting in early translation termination of DNAH5; The other is the mutation resulting in the deletion of exon76. Conclusions The newly identified DNAH5 splicing mutation c.13,338 + 5G > C is involved in the pathogenesis of PCD in the family, and forms a compound heterozygote with the pathogenic variant DNAH5 c.4314delT lead to the pathogenesis of PCD.

Abstract Whether the anesthesia technique, inhalational general anesthesia (IGA) or propofol-based anesthesia (PBA), influences the long-term survival of non-metastatic breast cancer (eBC) remain unclear and controversial. We carried out a literature search on 16thJuly, 2022 for studies comparing IGA and PBA in eBC undergoing standard surgery, according to PRISMA 2020. The major endpoint in our study was overall survival (OS). Seventeen studies including four randomized clinical trials and thirteen retrospective cohort studies were included in the meta-analysis. Ten studies provided data for crude OS in unweighted eBC patients (imbalance in baseline characteristics). The summarized estimate HRs of the PBA group versus the IGA group (ten studies, N = 127,774, IGA group: 92,592, PBA group: 35,182.) was 0.83 (95%CI: 0.78–0.89). Compared with IGA, PBA was associated with both better 1-year OS (two studies, N = 104,083, IGA group: 84,074, PBA group: 20,009. Pooled HR = 0.80, 0.73–0.89) and 5-year OS (six studies, N = 121,580, IGA group: 89,472, PBA group: 32,108. HR = 0.80, 0.74–0.87). Ten studies applied PSM method to balance the baseline characteristics. In these weighted patients, PBA still showed a better OS (ten studies, N = 105,459, IGA group: 79,095, PBA group: 26,364. HR = 0.93, 0.87–1.00), a better 1-year OS (two studies, N = 83,007, IGA group: 67,609, PBA group: 15,398. HR = 0.88, 0.78–0.98) and a trend towards a better 5-year OS (nine studies, N = 121,580, IGA group: 76,797, PBA group: 24,066. HR = 0.95, 0.88–1.03). Loco-regional recurrence-free survival (LRRFS) was also better in PBA group (HR = 0.73, 0.61–0.86). The present study is the first comprehensive meta-analysis to demonstrate that propofol-based anesthesia could significantly improve OS and LRRFS in non-metastatic breast cancer patients, compared with inhalational anesthesia.

Insufficient therapeutic strategies for acute kidney injury (AKI) necessitate precision therapy targeting its pathogenesis. This study reveals the new mechanism of the marine-derived anti-AKI agent, piericidin glycoside S14, targeting peroxiredoxin 1 (PRDX1). By binding to Cys83 of PRDX1 and augmenting its peroxidase activity, S14 alleviates kidney injury efficiently in Prdx1-overexpression (Prdx1-OE) mice. Besides, S14 also increases PRDX1 nuclear translocation and directly activates the Nrf2/HO-1/NQO1 pathway to inhibit ROS production. Due to the limited druggability of S14 with low bioavailability (2.6%) and poor renal distribution, a pH-sensitive kidney-targeting dodecanamine-chitosan nanoparticle system is constructed to load S14 for precise treatment of AKI. l-Serine conjugation to chitosan imparts specificity to kidney injury molecule-1 (Kim-1)-overexpressed cells. The developed S14-nanodrug exhibits higher therapeutic efficiency by improving the in vivo behavior of S14 significantly. By encapsulation with micelles, the AUC0‒t, half-life time, and renal distribution of S14 increase 2.5-, 1.8-, and 3.1-fold, respectively. The main factors contributing to the improved druggability of S14 nanodrugs include the lower metabolic elimination rate and UDP-glycosyltransferase (UGT)-mediated biotransformation. In summary, this study identifies a new therapeutic target for the marine-derived anti-AKI agent while enhancing its ADME properties and druggability through nanotechnology, thereby driving advancements in marine drug development for AKI.

In the era of Education 4.0, the development of smart schools represents a significant step forward. Learning spaces are critical to the success of smart school construction in primary and secondary schools, due to their significant impact on school-age children. This study focuses on identifying key spatial factors that influence students’ psychological preferences and learning utility in smart learning spaces. To achieve this, a visual stated preference method was employed to design a questionnaire, which was used to survey primary and secondary school students in Harbin, China. The resulting data was analyzed using a discrete choice model, which enabled the measurement of the utility levels of different learning space factors. The results show that students’ learning space preferences are significantly influenced by a variety of spatial factors, with the combination mode of classrooms and outdoors having the highest level of influence, followed by a completely open interface, U-shape seating layout, zoned color tone, and the combination mode of classrooms and corridors; the students surveyed show a significant negative preference for heteromorphic spaces compared to rectangular spaces. The discussion recommends the design of smart learning spaces around key spatial factors to enhance the utility of student learning.

Abstract Previous research has produced inconsistent findings concerning the connection between metabolic syndrome and prostate cancer. It is challenging for observational studies to establish a conclusive causal relationship between the two. However, Mendelian randomization can provide stronger evidence of causality in this context. To examine the causal link between a metabolic composite and its components with prostate cancer, we performed a two-sample Mendelian randomization (MR) study utilizing aggregated data from genome-wide association studies, followed by meta-analyses. In our study, we employed inverse variance weighting as the primary method for MR analysis. Additionally, we assessed potential sources of heterogeneity and horizontal pleiotropy through the Cochran’s Q test and MR-Egger regression. Moreover, we used multivariate MR to determine whether smoking versus alcohol consumption had an effect on the outcomes. We found no causal relationship between metabolic syndrome and its components and prostate cancer(MetS, odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.738–1.223, p = 0.691; TG, [OR] = 1.02, 95%[CI] = 0.96–1.08, p = 0.59); HDL, [OR] = 1.02, 95% [CI] = 0.97–1.07, p = 0.47; DBP, [OR] = 1.00, 95%[CI] = 0.99–1.01, p = 0.87; SBP, [OR] = 1.00, 95%[CI] = 0.99–1.00, p = 0.26; FBG [OR] = 0.92, 95%[CI] = 0.81–1.05, p = 0.23; WC, [OR] = 0.93, 95%[CI] = 0.84–1.03, p = 0.16). Finally, the MVMR confirms that the metabolic syndrome and its components are independent of smoking and alcohol consumption in prostate cancer. We didn’t find significant evidence to determine a causal relationship between the metabolic syndrome and its components and prostate cancer through MR analysis. Further research is necessary to explore the potential pathogenesis between the two diseases.

Abstract Drug exposure during pregnancy lacks global fetal safety data. The maternal drug exposure birth cohort (DEBC) study, a prospective longitudinal investigation, aims to explore the correlation of maternal drug exposure during pregnancy with pregnancy outcomes, and establish a human biospecimen biobank. Here we describe the process of establishing DEBC and show that the drug exposure rate in the first trimester of pregnant women in DEBC (n = 112,986) is 30.70%. Among the drugs used, dydrogesterone and progesterone have the highest exposure rates, which are 11.97% and 10.82%, respectively. The overall incidence of adverse pregnancy outcomes is 13.49%. Dydrogesterone exposure during the first trimester is correlated with higher incidences of stillbirth, preterm birth, low birth weight, and birth defects, along with a lower incidence of miscarriage/abortion. Due to the limitations of this cohort study, causative conclusions cannot be drawn. Further follow-up and in-depth data analysis are planned for future studies.

Digestive inflammation is a widespread global issue that significantly impacts quality of life. Recent advances have highlighted the unique potential of therapeutic peptides for treating this condition, owing to their specific bioactivity and high specificity. By specifically targeting key proteins involved in the pathological process and modulating biomolecular functions, therapeutic peptides offer a novel and promising approach to managing digestive inflammation. This review explores the development history, pharmacological characteristics, clinical applications, and regulatory mechanisms of therapeutic peptides in treating digestive inflammation. Additionally, the review addresses pharmacokinetics and quality control methods of therapeutic peptides, focusing on challenges such as low bioavailability, poor stability, and difficulties in delivery. The role of modern biotechnologies and nanotechnologies in overcoming these challenges is also examined. Finally, future directions for therapeutic peptides and their potential impact on clinical applications are discussed, with emphasis placed on their significant role in advancing medical and therapeutic practices.

Papillary thyroid carcinoma is a differentiated thyroid cancer that arises from thyroid follicular epithelial cells. Sarcoidosis is a multisystem disease of unknown cause, characterized by monocytic infiltration and granuloma formation. We herein report a case of thyroid carcinoma complicated by sarcoidosis. When thyroid nodules and lymph node lesions are suspected, it is essential to avoid fixed thinking, conduct a comprehensive preoperative evaluation, and select the appropriate surgical approach. This can help reduce the likelihood of postoperative complications and improve the patient’s quality of life. Therefore, comprehensive diagnosis of the coexistence of papillary thyroid carcinoma and sarcoidosis is crucial.

Abstract Study objective The aim of our study was to elucidate differences in brain activity patterns among obstructive sleep apnea (OSA) patients, OSA patients with depressive symptoms, and healthy controls (HCs). We also investigated the relationship between brain function and depression in OSA patients. Methods A total of 95 subjects were included in the study, including 34 OSA patients without depressive symptoms, 31 OSA patients with depressive symptoms, and 30 HCs. The 53‐channel functional near‐infrared spectroscopy (fNIRS) was used to monitor the concentration of oxy‐hemoglobin (Oxy‐Hb) in the brain, whereas the participants performed the verbal fluency task, and the degree of depression was scored using the 17‐item Hamilton Rating Scale for Depression (HAMD‐17). Hierarchical regression models were conducted to analyze the association of fNIRS features with depressive symptom. Results The Oxy‐Hb changes of the three groups were significantly different in Channels 25 (H = 9.878, p = .007) and 43 (H = 6.957, p = .031). Inter‐group comparisons showed that the Oxy‐Hb change of Channel 25 (located in the dorsolateral prefrontal cortex [DLPFC]) in OSA group was less than that in HC group (p = .006), and the Oxy‐Hb change of Channel 43 (located in the right frontal polar region) in OSA group with depression was less than that in OSA group (p = .025). Spearman's test showed that there was a significant negative correlation between HAMD‐17 scores and mean Oxy‐Hb changes in Channel 43 (r = −.319, p

PurposeThis study aimed to assess the causal relationships between vitamin D levels and ocular disorders.MethodsIndependent genetic variables were obtained from genome-wide association studies (GWAS) and publicly available databases. The summary statistics for 25-hydroxyvitamin D (25(OH)D) were obtained from two large-scale GWAS studies, with sample sizes of 324,105 and 417,580 European individuals. The genetic variants of myopia, primary open angle glaucoma (POAG), anterior iridocyclitis, senile cataract, diabetic retinopathy (DR), retinal vein occlusion (RVO), wet age-related macular degeneration (WAMD) and optic neuritis were extracted from the latest release of FinnGen consortium, which contains genome data from Finnish participants. Subsequently, Mendelian randomization (MR) analyses were conducted to obtain effect estimates. Additionally, we performed multivariable MR analysis and mediation analysis to validate the results.ResultsIn the discovery dataset, genetically predicted vitamin D concentration was found to be causally associated with an increased risk of WAMD, (odd ratio (OR) = 1.35, 95% confidence interval (CI) = 1.09–1.67, PIVW = 0.005). However, no causal effects of genetically predisposed vitamin D levels on the risk of most types of ocular disorders were observed. Reverse MR revealed no causal relationships between the ocular diseases and vitamin D concentrations. The MR analyses of the validation dataset yielded consistent results. Additionally, the causal effect of vitamin D levels on the risk of WAMD remained significant after adjusting for potential confounders in the multivariable MR analysis (OR = 1.86, 95% CI = 1.26–2.73, PIVW = 0.002).ConclusionOur MR analysis results provide robust evidence of a causal relationship between genetically predicted 25(OH)D levels and an increased risk of WAMD in European population. These findings offer important insights into the management and control of ocular disorders.

Glioma is a common primary malignant brain tumor with low survival rate. Immunotherapy with immune checkpoints inhibitors (ICI) can be a choice for glioma management, and extracellular vesicles (EVs) are recognized as a potential drug delivery system for various disease management due to their enhanced barrier permeation ability and immunomodulatory effect. The aim of this study is to develop ICI-loaded EVs (ICI/EV) that have sufficient efficacy in managing glioma. Calcium phosphate particles (CaP) were used to stimulate the secretion of EVs from murine macrophage cells. CaP conditioning of cells showed an enhanced amount of EVs secretion and macrophage polarization toward a proinflammatory phenotype. The CaP-induced EVs were shown to polarize macrophages into proinflammatory phenotype in vitro, as correlated with the conditioning method. ICI/EVs were successfully prepared with high loading efficiency using the sonication method. The EVs can be distributed throughout the entire brain upon intranasal administration and facilitate ICIs distribution into glioma lesion. Combinatory treatment with ICI/EVs showed benefit in glioma-bearing mice by reducing their tumor volume and prolonging their survival. Cytotoxic T cell infiltration, polarization of tumor-associated macrophage, and lower tumor proliferation were observed in ICI/EVs-treated mice. The developed ICI/EVs showed promise in immunotherapeutic management of glioma.

Abstract Conductive fillers‐embedded plastic polymer hybrid composites are crucial electronic materials in modern technologies owing to their tunable conductive properties, low density, and corrosion resistance. However, the application of traditional rigid inorganic conductive fillers‐embedded plastic composites is constrained by their subpar electrical conductivity and mechanical properties. Consequently, liquid metals (LMs) including gallium and gallium‐based alloys, have recently emerged as the preferred conductive flexible fillers over traditional rigid fillers. This work employs a solvent evaporation method and phase separation‐induced conductivity mechanism. The resulting flexible and electrically conductive LM‐polycarbonate (PC) film circuits demonstrate ultrahigh metallic conductivity, robust mechanical performance, excellent solvent recyclability, and notable processability. The fluidic nature of LMs and the superior mechanical properties of the PC polymer confer high electrical stability and durability to the LM‐PC film circuits under diverse mechanical forces and environmental conditions. The LM‐PC film circuits are exceedingly promising and apt for use as flexible conductors in contemporary electrical applications, including electricity transmission and underwater working.

BackgroundBreast cancer is a leading global health concern, necessitating advancements in recurrence prediction and management. The development of an artificial intelligence (AI)–based clinical decision support system (AI-CDSS) using ChatGPT addresses this need with the aim of enhancing both prediction accuracy and user accessibility. ObjectiveThis study aims to develop and validate an advanced machine learning model for a web-based AI-CDSS application, leveraging the question-and-answer guidance capabilities of ChatGPT to enhance data preprocessing and model development, thereby improving the prediction of breast cancer recurrence. MethodsThis study focused on developing an advanced machine learning model by leveraging data from the Tri-Service General Hospital breast cancer registry of 3577 patients (2004-2016). As a tertiary medical center, it accepts referrals from four branches—3 branches in the northern region and 1 branch on an offshore island in our country—that manage chronic diseases but refer complex surgical cases, including breast cancer, to the main center, enriching our study population’s diversity. Model training used patient data from 2004 to 2012, with subsequent validation using data from 2013 to 2016, ensuring comprehensive assessment and robustness of our predictive models. ChatGPT is integral to preprocessing and model development, aiding in hormone receptor categorization, age binning, and one-hot encoding. Techniques such as the synthetic minority oversampling technique address the imbalance of data sets. Various algorithms, including light gradient-boosting machine, gradient boosting, and extreme gradient boosting, were used, and their performance was evaluated using metrics such as the area under the curve, accuracy, sensitivity, and F1-score. ResultsThe light gradient-boosting machine model demonstrated superior performance, with an area under the curve of 0.80, followed closely by the gradient boosting and extreme gradient boosting models. The web interface of the AI-CDSS tool was effectively tested in clinical decision-making scenarios, proving its use in personalized treatment planning and patient involvement. ConclusionsThe AI-CDSS tool, enhanced by ChatGPT, marks a significant advancement in breast cancer recurrence prediction, offering a more individualized and accessible approach for clinicians and patients. Although promising, further validation in diverse clinical settings is recommended to confirm its efficacy and expand its use.

The temporal component of episodic memory has been recognized as a sensitive behavioral marker in early stage of Alzheimer's disease (AD) patients. However, parallel studies in AD animals are currently lacking, and the underlying neural circuit mechanisms remain poorly understood. Using a novel AppNL-G-F knock-in (APP-KI) rat model, the developmental changes of temporal order memory (TOM) and the relationship with medial prefrontal cortex and perirhinal cortex (mPFC-PRH) circuit were determined through in vivo electrophysiology and microimaging technique. We observed a deficit in TOM performance during the object temporal order memory task (OTOMT) in APP-KI rats at 6 month old, which was not evident at 3 or 4 months of age. Alongside behavioral changes, we identified a gradually extensive and aggravated regional activation and functional alterations in the mPFC and PRH during the performance of OTOMT, which occurred prior to the onset of TOM deficits. Moreover, coherence analysis showed that the functional connectivity between the mPFC and PRH could predict the extent of future behavioral performance. Further analysis revealed that the aberrant mPFC-PRH interaction mainly attributed to the progressive deterioration of synaptic transmission, information flow and network coordination from mPFC to PRH, suggesting the mPFC dysfunction maybe the key area of origin underlying the early changes of TOM. These findings identify a pivotal role of the mPFC-PRH circuit in mediating the TOM deficits in the early stage of AD, which holds promising clinical translational value and offers potential early biological markers for predicting AD memory progression.

Abstract This study presents a pioneering investigation into the complex Holocene paleo-morphologies of the Yilan Plain, located at the southwestern edge of the Okinawa Trough. We employed a novel approach that synergized resistivity measurements with machine learning techniques to unlock valuable insights into the geological history, sedimentary patterns, and seismic activity of this dynamic region. Our methodology involved the creation of an Apparent Geological Model (AGM) through the interpolation of inverted resistivity data and the application of supervised machine learning algorithms. Classification criteria, derived from the relationship between resistivity values and sediment types found in nearby boreholes, were developed using the random forest machine-learning method. The resultant 3D resistivity model was transformed into a clay-sand-gravel model, offering a comprehensive depiction of sediment distribution within the Yilan Plain. Notably, our findings revealed distinct sedimentary patterns. Gravel-dominated regions, characterized by resistivity values above 140 Ohm-m, were identified alongside areas dominated by sand and clay sediments. The Carbon-14 dating ages in the sand sediments exhibited remarkable consistency, shedding light on the depositional history of the region. Furthermore, our research unveiled a previously unknown phenomenon of rapid subsidence in the Yilan Plain. Through meticulous analysis and correction for sea-level changes, we estimated an average subsidence rate of approximately 8.5 mm/year. This subsidence was punctuated by abrupt events around 6000–7000 years BP and 2000–3000 years BP, associated with a sudden increase. These events suggested a potential link to prehistoric seismic activity, with variable subsidence rates between episodes hinting at recurrent active seismic periods every 4000–5000 years. In conclusion, our multidisciplinary approach has provided unprecedented insights into the Holocene paleo-morphologies of the Yilan Plain. By combining resistivity measurements, machine learning, and geological analysis, we have enriched our understanding of the region's geological history, sedimentary dynamics, and seismic behavior. These findings not only contribute to the knowledge of Yilan’s past but also offer vital data for future environmental and geological studies in similarly dynamic regions.

Abstract Objectives Ottelia Pers. is in the Hydrocharitaceae family. Species in the genus are aquatic, and China is their centre of origin in Asia. Ottelia alismoides (L.) Pers., which is distributed worldwide, is a distinguishing element in China, while other species of this genus are endemic to China. However, O. alismoides is also considered endangered due to habitat loss and pollution in some Asian countries. Ottelia alismoides is the only submerged macrophyte that contains three carbon dioxide-concentrating mechanisms, i.e. bicarbonate (HCO3 −) use, crassulacean acid metabolism and the C4 pathway. In this study, we present its first genome assembly to help illustrate the various carbon metabolism mechanisms and to enable genetic conservation in the future. Data description Using DNA and RNA extracted from one O. alismoides leaf, this work produced ∼ 73.4 Gb HiFi reads, ∼ 126.4 Gb whole genome sequencing short reads and ∼ 21.9 Gb RNA-seq reads. The de novo genome assembly was 6,455,939,835 bp in length, with 11,923 scaffolds/contigs and an N50 of 790,733 bp. Genome assembly completeness assessment with Benchmarking Universal Single-Copy Orthologs revealed a score of 94.4%. The repetitive sequence in the assembly was 4,875,817,144 bp (75.5%). A total of 116,176 genes were predicted. The protein sequences were functionally annotated against multiple databases, facilitating comparative genomic analysis.