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Abstract Background Effective mentorship is an important component of medical education with benefits to all stakeholders. In recent years, conceptualization of mentorship has gone beyond the traditional dyadic experienced mentor-novice mentee relationship to include group and peer mentoring. Existing theories of mentorship do not recognize mentoring’s personalized, evolving, goal-driven, and context-specific nature. Evidencing the limitations of traditional cause-and-effect concepts, the purpose of this review was to systematically search the literature to determine if mentoring can be viewed as a complex adaptive system (CAS). Methods A systematic scoping review using Krishna’s Systematic Evidence-Based Approach was employed to study medical student and resident accounts of mentoring and CAS in general internal medicine and related subspecialties in articles published between 1 January 2000 and 31 December 2023 in PubMed, Embase, PsycINFO, ERIC, Google Scholar, and Scopus databases. The included articles underwent thematic and content analysis, with the themes identified and combined to create domains, which framed the discussion. Results Of 5,704 abstracts reviewed, 134 full-text articles were evaluated, and 216 articles were included. The domains described how mentoring relationships and mentoring approaches embody characteristics of CAS and that mentorship often behaves as a community of practice (CoP). Mentoring’s CAS-like features are displayed through CoPs, with distinct boundaries, a spiral mentoring trajectory, and longitudinal mentoring support and assessment processes. Conclusion Recognizing mentorship as a CAS demands the rethinking of the design, support, assessment, and oversight of mentorship and the role of mentors. Further study is required to better assess the mentoring process and to provide optimal training and support to mentors.

Achieving a balance between accuracy and efficiency in target detection applications is an important research topic. To detect abnormal targets on power transmission lines at the power edge, this paper proposes an effective method for reducing the data bit width of the network for floating-point quantization. By performing exponent prealignment and mantissa shifting operations, this method avoids the frequent alignment operations of standard floating-point data, thereby further reducing the exponent and mantissa bit width input into the training process. This enables training low-data-bit width models with low hardware-resource consumption while maintaining accuracy. Experimental tests were conducted on a dataset of real-world images of abnormal targets on transmission lines. The results indicate that while maintaining accuracy at a basic level, the proposed method can significantly reduce the data bit width compared with single-precision data. This suggests that the proposed method has a marked ability to enhance the real-time detection of abnormal targets in transmission circuits. Furthermore, a qualitative analysis indicated that the proposed quantization method is particularly suitable for hardware architectures that integrate storage and computation and exhibit good transferability.

To explore the impact of ursodeoxycholic acid (UDCA) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and clinical outcomes in patients with autoimmune liver disease (AILD). Patients diagnosed with AILD were enrolled and divided into a UDCA group and a non-UDCA group based on whether they received UDCA treatment. Relevant data were collected regarding AILD diagnosis, treatment, biochemical indicators, and imaging examination. The incidence of SARS-CoV-2 infection and the prognosis of AILD patients were observed. A total of 1,138 patients completed follow-up. The usage rate of hormone (P = 0.003) and immunosuppressant (P = 0.001) used for treating AILD in the non-UDCA group was markedly lower than in the UDCA group. The UDCA usage rate was markedly lower in SARS-CoV-2 infected patients than in uninfected patients (P = 0.003). The rate of SARS-CoV-2 infection in the non-UDCA group was significantly higher than in the UDCA group (P = 0.018). Logistic regression analysis showed that UDCA use (P = 0.003) was correlated to a lower incidence of SARS-CoV-2, while immunosuppressant use (P = 0.017) increased the incidence. Recovery time from SARS-CoV-2 infection was markedly longer for those receiving UDCA treatment than those in the non-UDCA group (P = 0.018). UDCA is associated with low SARS-CoV-2 incidence in AILD patients, while immunosuppressant increases its incidence instead. Patients receiving UDCA treatment have a longer recovery time after being infected.

Abstract To improve the thermal and combustion properties of nanothermites, a design theory of changing the state of matter and structural state of the reactants during reaction was proposed. The Al/MoO3/KClO4 (Kp) nanothermite was prepared and the Al/MoO3 nanothermite was used as a control. SEM and XRD were used to characterize the nanothermites; DSC was used to test thermal properties; and constant volume and open combustion tests were performed to examine their combustion performance. Phase and morphology characterization of the combustion products were performed to reveal the mechanism of the aluminothermic reaction. The results show that the Al/MoO3/Kp nanothermite exhibited excellent thermal properties, with a total heat release of 1976 J·g− 1, increasing by approximately 33% of 1486 J·g− 1 of the Al/MoO3 nanothermite, and activation energy of 269.66 kJ·mol− 1, which demonstrated higher stability than the Al/MoO3 nanothermite (205.64 kJ·mol− 1). During the combustion test, the peak pressure of the Al/MoO3/Kp nanothermite was 0.751 MPa, and the average pressure rise rate was 25.03 MPa·s− 1, much higher than 0.188 MPa and 6.27 MPa·s− 1 of the Al/MoO3 nanothermite. The combustion products of Al/MoO3 nanothermite were Al2O3, MoO, and Mo, indicating insufficient combustion and incomplete reaction, whereas, the combustion products of Al/MoO3/Kp nanothermite were Al2O3, MoO, and KCl, indicating complete reaction. Their “coral-like” morphology was the effect of reactants solidifying after melting during the combustion process. The characterization of reactants and pressure test during combustion reveals the three stages of aluminothermic reaction in thermites. The excellent thermal and combustion performance of Al/MoO3/Kp nanothermite is attributed to the melt and decomposition of Kp into O2 in the third stage. This study provides new ideas and guidance for the design of high-performance nanothermites.

Abstract Background Circular RNAs (circRNAs) play critical roles in the tumorigenesis and radiosensitivity of multiple cancers. Nevertheless, the biological functions of circRNA periostin (circ‐POSTN) in esophageal cancer (EC) progression and radiosensitivity have not been well elucidated. Methods The expression of circ‐POSTN, microRNA‐876‐5p (miR‐876‐5p), and proto‐oncogene tyrosine‐protein kinase (FYN) was analyzed by quantitative reverse transcription PCR (RT‐qPCR). Cell proliferation was assessed by MTT, colony formation, and 5‐ethynyl‐2′‐deoxyuridine (EDU) assays. All protein levels were detected by western blot assay. Cell apoptosis and invasion were assessed by flow cytometry analysis and transwell assay, respectively. Dual‐luciferase reporter and RNA immunoprecipitation (RIP) assays were used to validate the interaction between miR‐876‐5p and circ‐POSTN or FYN. The role of circ‐POSTN in vivo was explored by establishing mice xenograft model. Results Circ‐POSTN was overexpressed in EC tissues and cells. Knockdown of circ‐POSTN inhibited cell proliferation and invasion and elevated apoptosis and radiosensitivity in EC cells. MiR‐876‐5p was a direct target of circ‐POSTN, and its knockdown reversed the role of sh‐circ‐POSTN in EC cells. FYN was a direct target of miR‐876‐5p, and FYN elevation weakened the effects of miR‐876‐5p overexpression on the progression and radiosensitivity of EC cells. Moreover, circ‐POSTN acted as a miR‐876‐5p sponge to regulate FYN expression. Circ‐POSTN interference also suppressed tumor growth and enhanced radiosensitivity in vivo. Conclusion Circ‐POSTN knockdown inhibited proliferation and invasion, but increased apoptosis and enhanced radiosensitivity in EC cells via modulating miR‐876‐5p/FYN axis, which might be a potential diagnostic and therapeutic target for EC.

Abstract The emerging monkeypox virus (MPXV) has raised global health concern, thereby highlighting the need for rapid, sensitive, and easy-to-use diagnostics. Here, we develop a single-step CRISPR-based diagnostic platform, termed SCOPE (Streamlined CRISPR On Pod Evaluation platform), for field-deployable ultrasensitive detection of MPXV in resource-limited settings. The viral nucleic acids are rapidly released from the rash fluid swab, oral swab, saliva, and urine samples in 2 min via a streamlined viral lysis protocol, followed by a 10-min single-step recombinase polymerase amplification (RPA)-CRISPR/Cas13a reaction. A pod-shaped vest-pocket analysis device achieves the whole process for reaction execution, signal acquisition, and result interpretation. SCOPE can detect as low as 0.5 copies/µL (2.5 copies/reaction) of MPXV within 15 min from the sample input to the answer. We validate the developed assay on 102 clinical samples from male patients / volunteers, and the testing results are 100% concordant with the real-time PCR. SCOPE achieves a single-molecular level sensitivity in minutes with a simplified procedure performed on a miniaturized wireless device, which is expected to spur substantial progress to enable the practice application of CRISPR-based diagnostics techniques in a point-of-care setting.

Background: This retrospective analysis aims to investigate the clinical characteristics of students infected with the SARS-CoV-2 Omicron variant in three Beijing schools. Additionally, we explore the dynamic trends of nucleic acid cycle threshold values (Ct values) and serum antibody titers throughout the disease course. Methods: Demographic, clinical, nucleic acid Ct values, and antibody titer data were collected from cases in a COVID-19 cluster in Beijing Ditan Hospital, Capital Medical University, spanning from September 6 to October 1, 2022. Results: A total of 107 students infected with Omicron (BA.5.2 and BA.2.76) were identified across three schools. Primary clinical manifestations included fever and upper respiratory symptoms (85/107, 79.4 %), with the majority being classified as mild cases (96/107, 89.7 %). Notably, middle school students in the second school exhibited a higher peak body temperature compared to college students in the first and third schools (39.5 °C vs. 38.4 °C, adjusted P = 0.005; 39.5 °C vs. 38.6 °C, adjusted P = 0.002). Analysis of dynamic changes in Ct values revealed the lowest median Ct value in nasopharyngeal swabs on the third day of illness, reaching 35 after 9–11 days. Oropharyngeal swab nucleic acid median Ct value reached 35 approximately 3–5 days post-onset. Serum antibody detection showed continuous negativity of IgM antibody titers from days 1–10, while IgG antibody titers were positive on the first day and increased rapidly after one week. Conclusions: The three COVID-19 cluster school outbreaks primarily resulted from Omicron infections, with no severe or fatal cases observed. Clinically, the selection of different types of SARS-CoV-2 nucleic acid swabs for virus detection can be tailored based on the infection's course.

Gastric carcinoma (GC) is one of the most common malignant tumors worldwide, and ranks fifth in incidence and top 5 in tumor-associated mortality. Unfortunately, the molecular mechanisms contributing to GC development are still unclear, urgently requiring more studies. It has been proposed that the multifunctional regulator receptor-interacting protein 2 (RIPK2) is both a regulator that induces stomach cancer and its complications such as cachexia. However, the potential molecular function of RIPK2 on regulation of GC is largely unknown. Moreover, 3,9-di-O-methylnissolin, a flavonoid derived from the roots of Astragalus membranaceus, exhibits protective effects against cancer, inflammation, and bacterial infections. Unfortunately the antineoplastic mechanism of oral exposure of such flavonoid are poorly understood. It remains unknown whether 3,9-di-O-methylnissolin is capable of mitigating GC progression, and potential molecular mechanism. This study aims to provide mechanistic evidence that the 3,9-di-O-methylnissolin-triggered mitigation of GC by repressing RIPK2 activity and its downstream ASK1 signaling. The TCGA database, GEO database, subjects with GC phenotype and GC cell lines were used in this work. 3,9-di-O-methylnissolin intervention reduces stomach cancer cell migration, proliferation and invasion in vitro. Also, 3,9-di-O-methylnissolin confers protection against tumor growth in xenograft model in vivo. Mechanistically, on the other hand, in the para-carcinoma tissue, overexpression of RIPK2 reduces lipogenesis and disturbs lipid homeostasis. Overexpression of RIPK2 activates downstream signaling of ASK1, which in turn downregulates PPARα, a master regulator of lipid metabolism. This process results in lower lipogenesis and downregulation of a set of PPARα target genes. Astragalus membranaceus naturally produces 3,9-di-O-methylnissolin, a bioactive substance that when suppression of ASK1 by methylnissolin reduces RIPK2-induced GC and its related cachexia and restores lipid homeostasis. These findings offer important new understandings of stomach cancer and could aid in the development of treatment plans for gastric carcinoma and cachexia related to cancer.

Whispering gallery mode (WGM) microcavities are excellent platforms for ultra-sensitive sensing due to high-quality factor and small mode volume. However, the conventional sensing method by tracking single-mode changes is difficult to fully utilize the sensing information, which limits the measurement precision and dynamical range. Here, we demonstrate a high-precision temperature sensor based on the multimode sensing method in a packaged microbubble resonator (PMBR). Remarkably, a low-cost broadband spectrum source is used as probe light to provide more sensing modes for high-precision measurement. Empowered by a machine learning method, the multimode spectral information are fully utilized, and the true temperature is precisely readout with mean-squared error (MSE) of 0.0138. The detection limit is lower three times than single-mode sensing method, capable of reaching 0.117 °C. In addition, the correlation coefficient (R2) between predictions and truth is as high as 0.9996 within the measurement range of 25–45 °C. With the low-cost laser source and high detection precision, this work provides a new perspective for intelligent optical microcavity sensors and their engineering applications.

Niclosamide (NIC) is a commonly used insecticide and molluscicide in the prevention and treatment of parasitic diseases in fish. The utilization of NIC has the potential to disrupt the microbial community present on the mucosal tissue of fish, leading to localized inflammatory responses. The objective of this study was to evaluate the impact of NIC on the immune system and bacterial populations within the gill and gut of Mylopharyngodon piceus. Fish were subjected to varying concentrations of NIC, including a control group (0 μg/L), a low NIC group (15% 96 h LC50, LNG, 9.8 μg/L), and a high NIC group (80% 96 h LC50, HNG, 52.5 μg/L). Gill and gut samples were collected 28 days post-exposure for analysis. The findings revealed that the 96-h LC50 for NIC was determined to be 65.7 μg/L, and histopathological examination demonstrated that exposure to NIC resulted in gill filament subepithelial edema, exfoliation, degeneration, and a decrease in gill filament length. Furthermore, the gut exhibited apical enterocyte degeneration and leucocyte infiltration following NIC exposure. Additionally, NIC exposure led to a significant elevation in the levels of immunoglobulin M (IgM), complement component 3 (C3), and complement component 4 (C4) in both gill and gut tissues. Moreover, the activity of lysozyme (LYZ) was enhanced in the gill, while the activities of peroxidase (POD) and immunoglobulin T (IgT) were increased in gut tissue. The exposure to NIC resulted in enhanced mRNA expression of c3, c9, tnfα, il6, il8, and il11 in the gill tissue, while decreasing c3 and il8 expression in the gut tissue. Furthermore, the natural resistance-associated macrophage protein (nramp) mRNA increased, and liver-expressed antimicrobial peptide 2 (leap2) mRNA decreased in gill and gut tissues. And hepcidin (hepc) mRNA levels rose in gill but fell in gut tissue. NIC exposure also led to a decrease in gill bacterial richness and diversity, which significantly differed from the control group, although this separation was not significant in the gut tissue. In conclusion, the administration of NIC resulted in alterations in both the immune response and mucosal microbiota of fish. Furthermore, it was noted that gills displayed a heightened vulnerability to sublethal effects of NIC in comparison to gut tissues.

Abstract With the ongoing mutation of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) leading to various variants, there is an urgent need for new diagnostic methods for SARS‐CoV‐2 infection. The existing nucleic acid test and antigen test suffer from long assay time and low sensitivity, respectively. Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS)‐based nasal swabs analysis have been demonstrated as a promising technique in SARS‐CoV‐2 infection screening. However, the applicability of the technique in the different variants of SARS‐CoV‐2 is uncertain. Given the prevalence of the Omicron variant since 2022, we developed a MALDI‐TOF‐based diagnosis method with nasal swab samples to detect the infection by this variant. We collected 325 SARS‐CoV‐2‐positive and 221 SARS‐CoV‐2‐negative nasal swab samples, and the molecular mass fingerprints were acquired from the samples by MALDI‐TOF MS. Using a random forest machine learning classification model to analyze the molecular mass fingerprints MALDI‐TOF mass spectra, the accuracy of 97%, false negative rate of 0%, and false positive rate of 7.6% were achieved for the diagnosis of SARS‐CoV‐2 infection. Combining the MALDI‐TOF analysis with top‐down proteomics, we identified four potential protein biomarkers, that is, humanin‐like 4, thymosin beta‐10, thymosin beta‐4 and statherin, in the nasal swab for the diagnosis of coronavirus disease 2019. It was further found that the four protein biomarkers can also differentiate the SARS‐CoV‐2 original strains infection and Omicron strains infection. These results suggest that the MALDI‐TOF MS‐based nasal swab analysis holds effective diagnostic capabilities of SARS‐CoV‐2 infection, and shows promising potential for global application and extension to other infectious diseases.

Closed-loop neuromodulation with intelligence methods has shown great potentials in providing novel neuro-technology for treating neurological and psychiatric diseases. Development of brain-machine interactive neuromodulation strategies could lead to breakthroughs in precision and personalized electronic medicine. The neuromodulation research tool integrating artificial intelligent computing and performing neural sensing and stimulation in real-time could accelerate the development of closed-loop neuromodulation strategies and translational research into clinical application. In this study, we developed a brain-machine interactive neuromodulation research tool (BMINT), which has capabilities of neurophysiological signals sensing, computing with mainstream machine learning algorithms and delivering electrical stimulation pulse by pulse in real-time. The BMINT research tool achieved system time delay under 3 ms, and computing capabilities in feasible computation cost, efficient deployment of machine learning algorithms and acceleration process. Intelligent computing framework embedded in the BMINT enable real-time closed-loop neuromodulation developed with mainstream AI ecosystem resources. The BMINT could provide timely contribution to accelerate the translational research of intelligent neuromodulation by integrating neural sensing, edge AI computing and stimulation with AI ecosystems.

Summary: The game between therapeutic monoclonal antibodies (mAbs) and continuously emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has favored the virus, as most therapeutic mAbs have been evaded. Addressing this challenge, we systematically explored a reproducible bispecific antibody (bsAb)-dependent synergistic effect in this study. It could effectively restore the neutralizing activity of the bsAb when any of its single mAbs is escaped by variants. This synergy is primarily attributed to the binding angle of receptor-binding domain (RBD)-5, facilitating inter-spike cross-linking and promoting cryptic epitope exposure that classical antibody cocktails cannot achieve. Furthermore, RBD-5 with RBD-2, RBD-6, and RBD-7, alongside RBD-8, also exhibit significantly enhanced effects. This study not only shifts the paradigm in understanding antibody interactions but paves the way for developing more effective therapeutic antibodies against rapidly mutating SARS-CoV-2, with Dia-19 already showing promise against emerging variants like BA.2.86, EG.5.1, and JN.1.

Abstract The high-altitude imaging capabilities of Unmanned Aerial Vehicles (UAVs) offer an effective solution for maritime Search and Rescue (SAR) operations. In such missions, the accurate identification of boats, personnel, and objects within images is crucial. While object detection models trained on general image datasets can be directly applied to these tasks, their effectiveness is limited due to the unique challenges posed by the specific characteristics of maritime SAR scenarios. Addressing this challenge, our study leverages the large-scale benchmark dataset SeaDronesSee, specific to UAV-based maritime SAR, to analyze and explore the unique attributes of image data in this scenario. We identify the need for optimization in detecting specific categories of difficult-to-detect objects within this context. Building on this, an anchor box optimization strategy is proposed based on clustering analysis, aimed at enhancing the performance of the renowned two-stage object detection models in this specialized task. Experiments were conducted to validate the proposed anchor box optimization method and to explore the underlying reasons for its effectiveness. The experimental results show our optimization method achieved a 45.8% and a 10% increase in average precision over the default anchor box configurations of torchvision and the SeaDronesSee official sample code configuration respectively. This enhancement was particularly evident in the model’s significantly improved ability to detect swimmers, floaters, and life jackets on boats within the SeaDronesSee dataset’s SAR scenarios. The methods and findings of this study are anticipated to provide the UAV-based maritime SAR research community with valuable insights into data characteristics and model optimization, offering a meaningful reference for future research.

Abstract Permeability assessment of naturally fractured rocks and fractured rocks after fracturing is critical to the development of oil and gas resources. In this paper, based on the discrete fracture network (DFN) modeling method, the conventional discrete fracture network (C-DFN) and the rough discrete fracture network (R-DFN) models are established. Through the seepage numerical simulation of the fractured rocks under different DFN, the differences in permeability of the fractured rocks under different parameters and their parameter sensitivity are analyzed and discussed. The results show that unconnected and independent fractures in the fracture network may weaken the seepage capacity of the fractured rocks. The fractured rock permeability increases with increase in connectivity and porosity and decreases with increase in maximum branch length and fracture dip. The use of C-DFN to equate the fracture network in the fractured rocks may underestimate the connectivity of the fracture network. For the more realistic R-DFN, the promotion of gas flow by connectivity is dominant when connectivity is high, and the hindrance of gas flow by fracture roughness is dominant when connectivity is low or when it is a single fracture. The permeability of the fractured rocks with R-DFN is more sensitive to the parameters than that of the fractured rocks with C-DFN. The higher the connectivity and porosity of the fractured rocks, the more obvious the difference between the permeability of the fractured rocks evaluated by C-DFN and R-DFN.

ObjectiveTo explore the Therapeutic effect of synchronous Integrated intensity modulated radiotherapy combined with chemotherapy in stage IIIc of Cervical CancerMethodsA total of 58 patients with stage IIIC cervical cancer (KPS ≥ 80) were analyzed in this study. They were admitted to our hospital between August 2017 and August 2022. Synchronous integrated boost intensity-modulated radiotherapy (SIB-IMRT) and sequential boost intensity-modulated radiotherapy (LCB-IMRT) were used to treat pelvic and/or para-aortic metastatic lymph nodes, with 30 cases in the SIB group and 28 cases in the LCB group. Comparison of short-term and long-term efficacy. Comparison of recurrence and metastasis rates, radiation dose to organs at risk and incidence of adverse drug reactions.Result30 patients were treated with simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT), and 28 patients were treated with sequential boost intensity-modulated radiotherapy (LCB-IMRT). At the completion of radiotherapy and 3 months after radiotherapy, there was no significant difference in clinical efficacy observed between the two treatment groups. The median overall survival (OS), progression-free survival (PFS), and disease-free survival (DMR) in the SIB-IMRT group were significantly higher compared to the LCB-IMRT group. The SIB-IMRT group demonstrated significantly lower rates compared to the LCB-IMRT group. Furthermore, within 3 years and 5 years, the rates of lymph node recurrence, cervical and vaginal local recurrence, and distant metastasis within the radiotherapy field were significantly lower in the SIB-IMRT group compared to the LCB-IMRT group. There were no significant differences observed between the two groups in terms of the maximum dose to the small intestine (Dmax), dose received by 2cc of the small intestine (D2cc), maximum dose to the rectum (Dmax), and dose received by 1cc of the bladder (D1cc). The incidence of bone marrow toxicity in the SIB-IMRT group was significantly lower compared to the LCB-IMRT group. Moreover, the occurrence of grade III and IV bone marrow toxicity was also significantly lower in the SIB-IMRT group compared to the LCB-IMRT group.ConclusionThe study has concluded that there is no significant differences in in terms of bladder associated adverse events and gastrointestinal toxicity in both Simultaneous Integrated Boost Intensity-Modulated Radiotherapy and Layered Conical Beam Intensity-Modulated Radiation Therapy.

The specificity of scenarios and tasks in Unmanned Aerial Vehicles (UAV)-based maritime rescue poses challenges for detecting targets within images captured by drones in such environments. This study focuses on leveraging heuristic methods to extract data features from specific UAV maritime rescue images to optimize the generation of anchor boxes in detection models. Experiments conducted on the large-scale SeaDronesSee maritime rescue dataset, using the MMDetection object detection framework, demonstrated that the optimized anchor boxes, improved model performance by 48.9% to 62.8% compared to the framework's default configuration, with the most proficient model surpassing the official highest SeaDronesSee baseline by over 49.3%. Further analysis of the results revealed the variation in detection difficulty for different objects within the dataset and identified the reasons behind these differences. The methodology and analysis presented in this study hold promise for optimizing UAV-based maritime rescue object detection models as well as refining data analysis and enhancement.

Chronic obstructive pulmonary disease (COPD) and other respiratory diseases frequently present with airway mucus hypersecretion, which not only affects the patient's quality of life but also poses a constant threat to their life expectancy. Ubiquitin-specific protease 7 (USP7), a deubiquitinating enzyme, affects cell differentiation, tissue growth, and disease development. However, its role in airway mucus hypersecretion induced by COPD remains elusive. In this study, USP7 expression was significantly upregulated in airway epithelial samples from patients with COPD, and USP7 was also overexpressed in mouse lung and human airway epithelial cells in models of airway mucus hypersecretion. Inhibition of USP7 reduced the expression of nuclear factor kappa B (NF-κB), phosphorylated-NF-κB (p-NF-κB), and phosphonated inhibitor of nuclear factor kappa B (p-IκBα), and alleviated the airway mucus hypersecretion in vivo and in vitro. Further research revealed that USP7 stimulated airway mucus hypersecretion through the activation of NF-κB nuclear translocation. In addition, the expression of mucin 5AC (MUC5AC) was suppressed by the NF-κB inhibitor erdosteine. These findings suggest that USP7 stimulates the NF-κB signaling pathway, which promotes airway mucus hypersecretion. This study identifies one of the mechanisms regulating airway mucus secretion and provides a new potential target for its prevention and treatment.

BackgroundMalnutrition, despite being a common complication, is often neglected in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). The objective of this study was to develop a simplified nutritional prognostic score to accurately predict mortality in HBV-ACLF patients.MethodsIn this multicenter retrospective study, clinical data from 530 HBV-ACLF patients were used to create a new prognostic score, which was then validated in two external cohorts (n = 229 and 248).ResultsFour independent factors were significantly associated with 28-day mortality in HBV-ACLF patients, forming a novel prognostic score (ALTA score = 0.187 × age—0.849 × lymphocyte count—2.033 × total cholesterol—0.148 × albumin—0.971). Notably, the AUROC of ALTA score for 28/90-day mortality (0.950/0.967) were significantly higher than those of three other ACLF prognostic scores (COSSH-ACLF II, 0.864/0.734; MELD, 0.525/0.488; MELD-Na, 0.546/0.517; all P < 0.001), and three known nutritional scores (CONUT, 0.739/0.861; OPNI, 0.279/0.157; NRS-2002, 0.322/0.286; all P < 0.001). The prediction error rates of ALTA score for 28-day mortality were significantly lower than COSSH-ACLF II (7.3%), MELD (14.4%), MELD-Na (12.7%), CONUT (9.0%), OPNI (30.6%), and NRS2002 (34.1%) scores. Further classifying ALTA score into two strata, the hazard ratios of mortality at 28/90 days were notably increased in the high-risk groups compared to the low-risk group (15.959 and 5.740). These results were then validated in two external cohorts.ConclusionALTA, as a simplified nutritional prognostic score for HBV-ACLF, demonstrates superiority over the COSSH-ACLF II and other scores in predicting short-term mortality among HBV-ACLF patients. Therefore, it may be used to guide clinical management, particularly in primary care settings.

Abstract The quantum mechanisms how life efficiently utilizes energy and transmits information remain unclear yet. Frequency medicine, an emerging cross‐discipline of both quantum mechanics and biomedicine, is a promising turning point for biomaterials and medicine developing from the matter level to the energy level. Recognizing the pivotal role of molecular vibrational frequencies in resonant energy coupling and transmission underscores the potential of frequency medicine to precisely regulate biomaterial vibrations, influencing interactions and reactions in living organisms. At present, scientists have unveiled sophisticated phototherapeutics; nevertheless, their advancement necessitates the precise mapping of the life energy. In contrast to genomics, proteomics, and metabolomics studied on the matter level, omics of frequencies related to medicine should be on the energy level. Herein, starting from the history of frequency medicine, and followed by the introduction of vibrational strong coupling applications in life sciences, we emphasize the significance, necessity, and urgency of studying spatiotemporal omics of medicine frequencies. By decoding the energy atlas of life, we can acquire profound insights into the quantum mechanisms that govern life processes from an energy standpoint. We anticipate that the integration of biomaterials with spatiotemporal frequency omics related to medical research will contribute significantly to advancing the goals of precision medicine, potentially revolutionizing pharmaceuticals, such as terahertz drugs.

Abstract The search for topological superconductivity (TSC) is currently an exciting pursuit, since non-trivial topological superconducting phases could host exotic Majorana modes. However, the difficulty in fabricating proximity-induced TSC heterostructures, the sensitivity to disorder and stringent topological restrictions of intrinsic TSC place serious limitations and formidable challenges on the materials and related applications. Here, we report a new type of intrinsic TSC, namely intrinsic surface topological superconductivity (IS-TSC) and demonstrate it in layered AuSn4 with T c of 2.4 K. Different in-plane and out-of-plane upper critical fields reflect a two-dimensional (2D) character of superconductivity. The two-fold symmetric angular dependences of both magneto-transport and the zero-bias conductance peak (ZBCP) in point-contact spectroscopy (PCS) in the superconducting regime indicate an unconventional pairing symmetry of AuSn4. The superconducting gap and surface multi-bands with Rashba splitting at the Fermi level (E F ), in conjunction with first-principle calculations, strongly suggest that 2D unconventional SC in AuSn4 originates from the mixture of p-wave surface and s-wave bulk contributions, which leads to a two-fold symmetric superconductivity. Our results provide an exciting paradigm to realize TSC via Rashba effect on surface superconducting bands in layered materials.

Abstract With the deepening of the construction of the new type power system, the grid has become increasingly complex, and its safe and stable operation is facing more challenges. In order to improve the quality and efficiency of power grid management, State Grid Corporation continues to promote the digital transformation of the grid, proposing concepts such as cloud-edge-end collaborative architecture and power Internet of Things, for which comprehensive sensing of the grid is an important foundation. Power equipment is widely distributed and has a wide variety of types, and online monitoring of them involves the deployment and application of a large number of power sensors. However, there are various problems in implementing active power supplies for these sensors, which restrict their service life. In order to collect and utilize the vibration energy widely present in the grid to provide power for sensors, this paper proposes an electromagnetic vibration energy harvester and its design methodology based on a four-straight-beam structure, and carries out a trial production of prototype. The vibration pickup unit of the harvester is composed of polyimide cantilevers, a permanent magnet and a mass-adjusting spacer. The mass-adjusting spacer can control the vibration frequency of the vibration unit to match the target frequency. In this paper, a key novel method is proposed to increase the number of turns in a limited volume by stacking flexible coils, which can boost the output voltage of the energy harvester. A test system is built to conduct a performance test for the prototype harvester. According to the test results, the resonant frequency of the device is $$100\ Hz$$ 100 H z , the output peak-to-peak voltage at the resonant frequency is $$2.56\ V$$ 2.56 V at the acceleration of $$1\ g$$ 1 g , and the maximum output power is around $$151.7\ \mu W$$ 151.7 μ W . The proposed four-straight-beam electromagnetic vibration energy harvester in this paper has obvious advantages in output voltage and power compared with state-of-the-art harvesters. It can provide sufficient power for various sensors, support the construction of cloud-edge-end architecture and the deployment of a massive number of power sensors. In the last part of this article, a self-powered transformer vibration monitor is presented, demonstrating the practicality of the proposed vibration energy harvester.

Abstract Sanding production of the underground gas storage (UGS) in the depleted reservoir will cause the decline of effective storage capacity, and the erosion of well string and auxiliary equipment, and other engineering problems. A deep understanding of the sanding production contributes to maintaining the injection and production capacity of gas storage and the long‐term safety of the UGS. In this paper, core samples of five main sedimentary microfacies were drilled from the UGS in middle China. The mechanical properties with different conditions of the moisture content in multi‐cycling injection–production process were tested. The critical drawdown pressure (CDP) calculation methods for the UGS were established based on the stress analysis near the wellbore and the Mogi–Coulomb criterion. Adopting the finite element method simulation on the geological model of the target UGS, the geo‐stress of the formation was calculated by inversed analysis and validated based on the Kaiser effect of rock. Then, the CDP of two target wells of the UGS were investigated. The effects of the water moisture and the cycling times of the injection–production process on the CDP were also analyzed. The geo‐stress distribution shows that the horizontal maximum principal stress ranges from 53 to 68 MPa, and the horizontal minimum principal stress is 46–58 MPa in the target reservoir section, and the vertical minimum principal stress is 69–77 MPa in the target reservoir. The calculated CDP changed with the types of the sedimentary microfacies in the range of [6.27, 8.77] MPa, in which the CDP of the mixed mud and sand flat sedimentary facies was the lowest. The weakness of the CDP with the increasing of the moisture content and the cycling times were analyzed quantitively.

Physical dormancy (PY) commonly present in the seeds of higher plants is believed to be responsible for the germination failure by impermeable seed coat in hard seeds of legume species, instead of physiological dormancy (PD). In this study, a non-destructive approach involving multispectral imaging was used to successfully identify hard seeds from non-hard seeds in Medicago sativa, with accuracy as high as 96.8%–99.0%. We further adopted multiple-omics strategies to investigate the differences of physiology, metabolomics, methylomics, and transcriptomics in alfalfa hard seeds, with non-hard seeds as control. The hard seeds showed dramatically increased antioxidants and 125 metabolites of significant differences in non-targeted metabolomics analysis, which are enriched in the biosynthesis pathways of flavonoids, lipids and hormones, especially with significantly higher ABA, a hormone known to induce dormancy. In our transcriptomics results, the enrichment pathway of “response to abscisic acid” of differential expressed genes (DEG) supported the key role of ABA in metabolomics results. The methylome analysis identified 54,899, 46,216 and 54,452 differential methylation regions for contexts of CpG, CHG and CHH, and 344 DEGs might be regulated by hypermethylation and hypomethylation of promoter and exon regions, including four ABA- and JA-responsive genes. Among 8% hard seeds in seed lots, 24.5% still did not germinate after scarifying seed coat, and were named as non-PY hard seeds. Compared to hard seeds, significantly higher contents of ABA/IAA and ABA/JA were identified in non-PY hard seeds, which indicated the potential presence of PD. In summary, the significantly changed metabolites, gene expressions, and methylations all suggested involvement of ABA responses in hard seeds, and germination failure of alfalfa hard seeds was caused by combinational dormancy (PY + PD), rather than PY alone.

Abstract Leaf rust, caused by Puccinia triticina Eriksson (Pt), is one of the most severe foliar diseases of wheat. Breeding for leaf rust resistance is a practical and sustainable method to control this devastating disease. Here, we report the identification of Lr47, a broadly effective leaf rust resistance gene introgressed into wheat from Aegilops speltoides. Lr47 encodes a coiled-coil nucleotide-binding leucine-rich repeat protein that is both necessary and sufficient to confer Pt resistance, as demonstrated by loss-of-function mutations and transgenic complementation. Lr47 introgression lines with no or reduced linkage drag are generated using the Pairing homoeologous1 mutation, and a diagnostic molecular marker for Lr47 is developed. The coiled-coil domain of the Lr47 protein is unable to induce cell death, nor does it have self-protein interaction. The cloning of Lr47 expands the number of leaf rust resistance genes that can be incorporated into multigene transgenic cassettes to control this devastating disease.

Abstract With the emergence of new information and communication technology, mobile‐based ridesharing services have received more attention and have improved. They offer timely and convenient service and exert an enormous influence on pollution and congestion by allowing passengers to share overlapping routes. However, ridesharing services have also been discussed and called into question by people with respect to their attractiveness, their comfort, and passenger safety. This paper proposes a ridesharing algorithm with a perceived mechanism by introducing multiple dimensions of perceived value to overall assess passengers’ perceptions. The approach involved can continuously track the psychological changes in passengers during travel, capture the dynamic and comprehensive perceptions of passengers, and make real‐time adjustments on this basis. Furthermore, the proposed partition‐based parallel strategy can ensure high‐quality services and further enhance computational efficiency. Finally, numerical experiments are conducted based on the urban transportation network and the actual trip data from Manhattan to evaluate the performance of the proposed algorithm. The results show that it is important to effectively capture the passengers’ perception of ridesharing services and apply them to optimization mechanisms, which will contribute to improving the perception of ride experiences and attracting potential passengers.

Abstract Objectives To compare the inter-modality consistency and diagnostic performances of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and contrast-enhanced computed tomography (CECT) LI-RADS in patients at risk for hepatocellular carcinoma (HCC), so as to help clinicians to select a more appropriate modality to follow the focal liver lesions (FLLs). Methods This retrospective study included untreated 277 FLLs from 247 patients who underwent both CEUS and CECT within 1 month. The ultrasound contrast medium used was SonoVue. FLL categories were independently assigned by two ultrasound physicians and two radiologists using CEUS LI-RADS v2017 and CECT LI-RADS v2018, respectively. The diagnostic performances of CEUS and CECT LI-RADS were evaluated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value. Cohen’s Kappa was employed to evaluate the concordance of the LI-RADS category. Results The inter-modality consistency for CEUS and CECT LI-RADS was 0.31 (p