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Abstract Background With the advancement of world population aging, age-related sarcopenia (SP) imposes enormous clinical burden on hospital. Clinical research of SP in non-geriatric wards has not been appreciated, necessitating further investigation. However, observational studies are susceptible to confounders. Mendelian randomization (MR) can effectively mitigate bias to assess causality. Objective To investigate the correlation between SP and comorbidities in orthopedic wards, and subsequently infer the causality, providing a theoretical basis for developing strategies in SP prevention and treatment. Methods Logistic regression models were employed to assess the correlation between SP and comorbidities. The MR analysis was mainly conducted with inverse variance weighted, utilizing data extracted from the UK and FinnGen biobank (Round 9). Results In the cross-sectional analysis, SP exhibited significant associations with malnutrition (P = 0.013) and some comorbidities, including osteoporosis (P = 0.014), body mass index (BMI) (P = 0.021), Charlson Comorbidity Index (CCI) (P = 0.006). The MR result also provided supporting evidence for the causality between SP and hypertension, osteoporosis and BMI. These results also withstood multiple sensitivity analyses assessing the validity of MR assumptions. Conclusion The result indicated a significant association between SP and BMI, CCI, malnutrition, and osteoporosis. We highlighted that SP and comorbidities deserved more attention in non-geriatric wards, urging further comprehensive investigation.

Abstract The window strategy, known for its flexibility and efficiency, is extensively used in dynamic path planning. To further enhance the performance of the Automated Guided Vehicles (AGVs) sorting system, the two processes of AGV movement and path planning can be executed concurrently based on the window strategy. Nonetheless, difficulties in matching the computing time of the planning server with the moving time of AGVs may cause delays or reduced path optimality. To address the problem, this paper proposes an optimal time reuse strategy. The proposed solution controls computing time by managing path length for each planning instance, ensuring alignment with the moving time of AGVs to maximize path optimality and avoid delays. To achieve this, two aspects need to be considered. Firstly, on a systemic level, we control the entry rate of AGVs by adjusting the replanning period, thus avoiding congestion caused by excessive AGVs and maintaining high system efficiency. Secondly, we reversely control the computing time by adjusting the path length that needs to be planned for each single planning, so that it matches the moving time of AGVs. Simulation results show that our method outperforms existing top-performing methods, achieving task completion rates 1.64, 1.57, and 1.12 times faster across various map sizes. This indicates its effectiveness in synchronizing planning and movement times. The method contributes significantly to dynamic path planning methodologies, offering a novel approach to time management in AGV systems.

Abstract Background Language delay affects near- and long-term social communication and learning in toddlers, and, an increasing number of experts pay attention to it. The development of prosody discrimination is one of the earliest stages of language development in which key skills for later stages are mastered. Therefore, analyzing the relationship between brain discrimination of speech prosody and language abilities may provide an objective basis for the diagnosis and intervention of language delay. Methods In this study, all cases(n = 241) were enrolled from a tertiary women’s hospital, from 2021 to 2022. We used functional near-infrared spectroscopy (fNIRS) to assess children’s neural prosody discrimination abilities, and a Chinese communicative development inventory (CCDI) were used to evaluate their language abilities. Results Ninety-eight full-term and 108 preterm toddlers were included in the final analysis in phase I and II studies, respectively. The total CCDI screening abnormality rate was 9.2% for full-term and 34.3% for preterm toddlers. Full-term toddlers showed prosody discrimination ability in all channels except channel 5, while preterm toddlers showed prosody discrimination ability in channel 6 only. Multifactorial logistic regression analyses showed that prosody discrimination of the right angular gyrus (channel 3) had a statistically significant effect on language delay (odd ratio = 0.301, P

Abstract We investigate the entanglement harvesting phenomenon for static detectors that locally interact with massless scalar fields in the cosmic string spacetime, which, though locally flat, features a conical structure defined by a deficit angle. Specifically, we analyze three detector alignments relative to the string: parallel and orthogonal alignments with detectors on the same side of the string, and an orthogonal alignment with detectors on opposite sides of the string. For the alignments on the same side of the string, we observe that the cosmic string’s presence can either aid or hinder entanglement harvesting, affecting both the extent of entanglement harvested and the achievable range of interdetector separation. This effect depends on the distance between the detectors and the string and differs markedly from scenarios in a locally flat spacetime with a reflecting boundary, where the boundary invariably extends the harvesting-achievable range. Conversely, for the alignment with detectors on opposite sides of the string, we find that detectors consistently harvest more entanglement than those in a flat spacetime devoid of a cosmic string. This starkly contrasts the behavior observed with detectors on the same side. Interestingly, the presence of a cosmic string expands the harvesting-achievable range for detectors in orthogonal alignment only when near the string, whereas it invariably reduces the achievable range for detectors in parallel alignment.

Abstract Metal‐enzyme integrated catalysts (MEICs) that combine metal and enzyme offer great potential for sustainable chemoenzymatic cascade catalysis. However, rational design and construction of optimal microenvironments and accessible active sites for metal and enzyme in individual nanostructures are necessary but still challenging. Herein, Pd nanoparticles (NPs) and Candida antarctica lipase B (CALB) are co‐immobilized into the pores and surfaces of covalent organic frameworks (COFs) with tunable functional groups, affording Pd/COF‐X/CALB (X = ONa, OH, OMe) MEICs. This strategy can regulate the microenvironment around Pd NPs and CALB, and their interactions with substrates. As a result, the activity of the COF‐based MEICs in catalyzing dynamic kinetic resolution of primary amines is enhanced and followed COF‐OMe > COF‐OH > COF‐ONa. The experimental and simulation results demonstrated that functional groups of COFs modulated the conformation of CALB, the electronic states of Pd NPs, and the affinity of the integrated catalysts to the substrate, which contributed to the improvement of the catalytic activity of MEICs. Further, the MEICs are prepared using COF with hollow structure as support material, which increased accessible active sites and mass transfer efficiency, thus improving catalytic performance. This work provides a blueprint for rational design and preparation of highly active MEICs.

Abstract Background Cholangiocarcinoma (CCA) is a biliary epithelial malignant tumor with an increasing incidence worldwide. Therefore, further understanding of the molecular mechanisms of CCA progression is required to identify new therapeutic targets. Methods The expression of RPL35A in CCA and para-carcinoma tissues was detected by immunohistochemical staining. IP-MS combined with Co-IP identified downstream proteins regulated by RPL35A. Western blot and Co-IP of CHX or MG-132 treated CCA cells were used to verify the regulation of HSPA8 protein by RPL35A. Cell experiments and subcutaneous tumorigenesis experiments in nude mice were performed to evaluate the effects of RPL35A and HSPA8 on the proliferation, apoptosis, cell cycle, migration of CCA cells and tumor growth in vivo. Results RPL35A was significantly upregulated in CCA tissues and cells. RPL35A knockdown inhibited the proliferation and migration of HCCC-9810 and HUCCT1 cells, induced apoptosis, and arrested the cell cycle in G1 phase. HSPA8 was a downstream protein of RPL35A and overexpressed in CCA. RPL35A knockdown impaired HSPA8 protein stability and increased HSPA8 protein ubiquitination levels. RPL35A overexpression promoted CCA cell proliferation and migration. HSPA8 knockdown inhibited CCA cell proliferation and migration, and reversed the promoting effect of RPL35A. Furthermore, RPL35A promoted tumor growth in vivo. In contrast, HSPA8 knockdown suppressed tumor growth, while was able to restore the effects of RPL35A overexpression. Conclusion RPL35A was upregulated in CCA tissues and promoted the progression of CCA by mediating HSPA8 ubiquitination.

Abstract Pyroptotic cell death, an inflammatory form of programmed cell death (PCD), is emerging as a potential therapeutic opportunity for radiotherapy (RT). RT is commonly used for cancer treatment, but its effectiveness can be limited by tumor resistance and adverse effects on healthy tissues. Pyroptosis, characterized by cell swelling, membrane rupture, and release of pro-inflammatory cytokines, has been shown to enhance the immune response against cancer cells. By inducing pyroptotic cell death in tumor cells, RT has the potential to enhance treatment outcomes by stimulating anti-tumor immune responses and improving the overall efficacy of RT. Furthermore, the release of danger signals from pyroptotic cells can promote the recruitment and activation of immune cells, leading to a systemic immune response that may target distant metastases. Although further research is needed to fully understand the mechanisms and optimize the use of pyroptotic cell death in RT, it holds promise as a novel therapeutic strategy for improving cancer treatment outcomes. This review aims to synthesize recent research on the regulatory mechanisms underlying radiation-induced pyroptosis and to elucidate the potential significance of this process in RT. The insights gained from this analysis may inform strategies to enhance the efficacy of RT for tumors.

Abstract On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities, such as ambiguous boundary, variable thickness, nonuniform material properties. This work develops for the first time a method that uses ultrasound echo groups and artificial neural network (ANN) for reliable on-site real-time identification of material parameters. The use of echo groups allows the use of lower frequencies, and hence more accommodative to structural complexity. To train the ANNs, a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure. The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model. This results in a set of dataset for training the ANN model. Once the ANN is trained, the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN. Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method. The results show that the maximum identification error of numerical example is less than 2%, and the maximum identification error of experimental test is less than 7%. Compared with currently prevailing methods and equipment, the proposefy the density and thickness, in addition to the elastic constants. Moreover, the reliability and accuracy of inverse prediction is significantly improved. Thus, it has broad applications and enables real-time field measurements, which has not been fulfilled by any other available methods or equipment.

Abstract Background Neoadjuvant chemotherapy (NAC) has become a standard treatment strategy for breast cancer (BC). However, owing to the high heterogeneity of these tumors, it is unclear which patient population most likely benefit from NAC. Multi-omics offer an improved approach to uncovering genomic and transcriptomic changes before and after NAC in BC and to identifying molecular features associated with NAC sensitivity. Methods We performed whole-exome and RNA sequencing on 233 samples (including matched pre- and post-treatment tumors) from 50 BC patients with rigorously defined responses to NAC and analyzed changes in the multi-omics landscape. Molecular features associated with NAC response were identified and validated in a larger internal, and two external validation cohorts, as well as in vitro experiments. Results The most frequently altered genes were TP53, TTN, and MUC16 in both pre- and post-treatment tumors. In comparison with pre-treatment tumors, there was a significant decrease in C > A transversion mutations in post-treatment tumors (P = 0.020). NAC significantly decreased the mutation rate (P = 0.006) of the DNA repair pathway and gene expression levels (FDR = 0.007) in this pathway. NAC also significantly changed the expression level of immune checkpoint genes and the abundance of tumor-infiltrating immune and stroma cells, including B cells, activated dendritic cells, γδT cells, M2 macrophages and endothelial cells. Furthermore, there was a higher rate of C > T substitutions in NAC nonresponsive tumors than responsive ones, especially when the substitution site was flanked by C and G. Importantly, there was a unique amplified region at 8p11.23 (containing ADGRA2 and ADRB3) and a deleted region at 3p13 (harboring FOXP1) in NAC nonresponsive and responsive tumors, respectively. Particularly, the CDKAL1 missense variant P409L (p.Pro409Leu, c.1226C > T) decreased BC cell sensitivity to docetaxel, and ADGRA2 or ADRB3 gene amplifications were associated with worse NAC response and poor prognosis in BC patients. Conclusions Our study has revealed genomic and transcriptomic landscape changes following NAC in BC, and identified novel biomarkers (CDKAL1 P409L , ADGRA2 and ADRB3) underlying chemotherapy resistance and poor prognosis, which could guide the development of personalized treatments for BC.

ABSTRACTPaxilline (PAX) is a tremorgenic mycotoxin that is thought to be associated with various syndromes in animals. To facilitate the determination of this toxin, a hapten was chemically synthesized and then respectively conjugated to Bovine Thyroglobulin (BTG) and Bovine serum albumin (BSA) for antibody production. Monoclonal antibody (mAb) 4F8 was finally obtained and used to establish an accurate and sensitive indirect competitive ELISA (icELISA). Various parameters that could impact the performance of icELISA were optimized, including the ion concentration, pH value and organic solvent. Under optimal condition, this assay exhibits an IC50 value as low as 0.84 µg L−1. The limit of detection (LOD) of the established icELISA method for PAX was 0.03–0.3 µg L−1. In conclusion, this study provided a rapid, sensitive, and high-throughput immunoassay for the detection of PAX in grains.

Background Anorexia nervosa (AN) has been characterised as a psychiatric disorder associated with increased control. Currently, it remains difficult to predict treatment response in patients with AN. Their cognitive abilities are known to be resistant to treatment. It has been established that the frontoparietal control network (FPCN) is the direct counterpart of the executive control network. Therefore, the resting-state brain activity of the FPCN may serve as a biomarker to predict treatment response in AN.Aims The study aimed to investigate the association between resting-state functional connectivity (RSFC) of the FPCN, clinical symptoms and treatment response in patients with AN.Methods In this case-control study, 79 female patients with AN and no prior treatment from the Shanghai Mental Health Center and 40 matched healthy controls (HCs) were recruited from January 2015 to March 2022. All participants completed the Questionnaire Version of the Eating Disorder Examination (version 6.0) to assess the severity of their eating disorder symptoms. Additionally, RSFC data were obtained from all participants at baseline by functional magnetic resonance imaging. Patients with AN underwent routine outpatient treatment at the 4th and 12th week, during which time their clinical symptoms were evaluated using the same measures as at baseline.Results Among the 79 patients, 40 completed the 4-week follow-up and 35 completed the 12-week follow-up. The RSFC from the right posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (dlPFC) increased in 79 patients with AN vs 40 HCs after controlling for depression and anxiety symptoms. By multiple linear regression, the RSFC of the PPC to the inferior frontal gyrus was found to be a significant factor for self-reported eating disorder symptoms at baseline and the treatment response to cognitive preoccupations about eating and body image, after controlling for age, age of onset and body mass index. The RSFC in the dlPFC to the middle temporal gyrus and the superior frontal gyrus may be significant factors in the treatment response to binge eating and loss of control/overeating in patients with AN.Conclusions Alterations in RSFC in the FPCN appear to affect self-reported eating disorder symptoms and treatment response in patients with AN. Our findings offer new insight into the pathogenesis of AN and could promote early prevention and treatment.

BackgroundFor patients with hilar cholangiocarcinoma (HC) undergoing hemi-hepatectomy, there are controversies regarding the requirement of, indications for, and timing of preoperative biliary drainage (PBD). Dynamic three-dimensional volume reconstruction could effectively evaluate the regeneration of liver after surgery, which may provide assistance for exploring indications for PBD and optimal preoperative bilirubin value. The purpose of this study was to explore the indications for PBD and the optimal preoperative bilirubin value to improve prognosis for HC patients undergoing hemi-hepatectomy.MethodsWe retrospectively analyzed the data of HC patients who underwent hemi-hepatectomy in the First Affiliated Hospital of China Medical University from 2012 to 2023. The liver regeneration rate was calculated using three-dimensional volume reconstruction. We analyzed the factors affecting the liver regeneration rate and occurrence of postoperative liver insufficiency.ResultsThis study involved 83 patients with HC, which were divided into PBD group (n=36) and non-PBD group (n=47). The preoperative bilirubin level may be an independent risk factor affecting the liver regeneration rate (P=0.014) and postoperative liver insufficiency (P=0.016, odds ratio=1.016, β=0.016, 95% CI=1.003–1.029). For patients whose initial bilirubin level was >200 μmol/L (n=45), PBD resulted in better liver regeneration in the early stage (P=0.006) and reduced the incidence of postoperative liver insufficiency [P=0.012, odds ratio=0.144, 95% confidence interval (CI)=0.031–0.657]. The cut-off value of bilirubin was 103.15 μmol/L based on the liver regeneration rate. Patients with a preoperative bilirubin level of ≤103.15 μmol/L shown a better liver regeneration (P200 μmol/L, PBD may result in better liver regeneration and reduce the incidence of postoperative liver insufficiency. Preoperative bilirubin levels ≤103.15 μmol/L maybe recommended for leading to a better liver regeneration and lower incidence of postoperative hepatic insufficiency.

ContextCabozantinib combined with immune checkpoint inhibitors (ICIs) has brought a new therapeutic effect for the medical treatment of renal cell carcinoma (RCC).ObjectivesWe performed a meta-analysis of randomized controlled trials and single-arm trials to evaluate the efficacy and safety of cabozantinib plus ICIs in RCC.MethodsWe extracted data from PubMed, Cochrane, Medline and Embase databases, and rated literature quality through Cochrane risk of bias tool and MINORS. RevMan5.3 software was used to analyze the results of randomized controlled trials and single-arm trials.ResultsA total of 7 studies were included. Treatment with cabozantinib plus ICIs improved PFS [HR 0.75, (95%CI: 0.52, 1.08), p = 0.12] and the OS [HR 0.80, (95%CI: 0.60, 1.07), p = 0.13] in randomized controlled trials. Meanwhile, the result of the ORR in randomized controlled trials was [risk ratio (RR) 1.37, (95%CI: 1.21, 1.54), p < 0.00001] and in single-arm trials was [risk difference (RD) 0.49, (95%CI: 0.26, 0.71), p < 0.0001].ConclusionCabozantinib plus ICIs prolonged the PFS and OS, and improved ORR in patients with RCC. Our recommendation is to use cabozantinib plus ICIs to treat advanced RCC, and to continuous monitor and manage the drug-related adverse events.Systematic Review Registration:identifier CRD42023455878.

AbstractThe R-spondin protein family comprises four members (RSPO1-4), which are agonists of the canonical Wnt/β-catenin pathway. Emerging evidence revealed that RSPOs should not only be viewed as agonists of the Wnt/β-catenin pathway but also as regulators for tumor development and progression. Aberrant expression of RSPOs is related to tumorigenesis and tumor development in multiple cancers and their expression of RSPOs has also been correlated with anticancer immune cell signatures. More importantly, the role of RSPOs as potential target therapies and their implication in cancer progressions has been studied in the preclinical and clinical settings. These findings highlight the possible therapeutic value of RSPOs in cancer medicine. However, the expression pattern, effects, and mechanisms of RSPO proteins in cancer remain elusive. Investigating the many roles of RSPOs is likely to expand and improve our understanding of the oncogenic mechanisms mediated by RSPOs. Here, we reviewed the recent advances in the functions and underlying molecular mechanisms of RSPOs in tumor development, cancer microenvironment regulation, and immunity, and discussed the therapeutic potential of targeting RSPOs for cancer treatment. In addition, we also explored the biological feature and clinical relevance of RSPOs in cancer mutagenesis, transcriptional regulation, and immune correlation by bioinformatics analysis.KEY MESSAGESAberrant expressions of RSPOs are detected in various human malignancies and are always correlated with oncogenesis.Although extensive studies of RSPOs have been conducted, their precise molecular mechanism remains poorly understood.Bioinformatic analysis revealed that RSPOs may play a part in the development of the immune composition of the tumor microenvironment.

Abstract We explore correlations harvesting by two static detectors locally interacting with vacuum massless scalar fields in the presence of an infinite perfectly reflecting boundary. We study the phenomena of mutual information harvesting and entanglement harvesting for two detector-boundary alignments, i.e., parallel-to-boundary and orthogonal-to-boundary alignments. Our results show that the presence of the boundary generally inhibits mutual information harvesting relative to that in flat spacetime without any boundaries. In contrast, the boundary may play a doubled-edged role in entanglement harvesting, i.e., inhibiting entanglement harvesting in the near zone of the boundary while assisting it in the far zone of the boundary. Moreover, there exists an optimal detector energy gap difference between two nonidentical detectors that makes such detectors advantageous in correlations harvesting as long as the interdetector separation is large enough. The value of the optimal detector energy gap difference depends on both the interdetector separation and the detector-to-boundary distance. A comparison of the correlations harvesting in two different alignments shows that although correlations harvesting share qualitatively the same properties, they also display quantitative differences in that the detectors in orthogonal-to-boundary alignment always harvest comparatively more mutual information than the parallel-to-boundary ones, while they harvest comparatively more entanglement only near the boundary.

Abstract Multiple evidence indicates that perinatal factors make impact on immune development and affect offspring allergic rhinitis (AR) risk. In this systematic review and meta-analysis, we examined available published studies to clarify the relationship between cesarean section (C-section) and offspring AR in children. To explore the relationship between C-section, especially the special attention was paid to different cesarean delivery mode, and the risk of AR in children. Articles were searched using PubMed, Web of Science, EMBASE, Cochrane Library, China knowledge Network, Wanfang, and China Science and Technology Journal databases. A meta-analysis of 22 studies published before August 1, 2022, which included 1,464,868 participants, was conducted for statistical analysis with RevMan5.4. The correlation strength between C-section and offspring AR was determined by combining odds ratio (OR) and 95% confidence interval (95% CI). Meta-regression and subgroup analyses were used to explore potential sources of heterogeneity. Publication bias was detected using the funnel chart and Egger tests. Meta-analysis revealed that there was a significant correlation between C-section and children AR (OR = 1.19, 95% CI: 1.12–1.27, P

Abstract Cold surge events in the South China Sea (over 110–117.5° E longitude at 15° N latitude) from 1979 to 2019 are divided into four types depending on their correlation with North Pacific extratropical cyclones (ECs). Climatologic relationships between the two phenomena reveal that 92% (39%) of all cold surges are accompanied by ECs (explosive extratropical cyclones, abbreviated as EC‐E), while 31% of ECs are accompanied by cold surges. The occurrence and development of ECs favour eruptions of cold air from higher latitudes, which in turn produce conditions conducive to cold surges. In the North Pacific, ECs travel in a northeastward direction, ultimately contributing to the Aleutian low. Meanwhile, the westerly jet is observed to strengthen following cold surge events. Both actions drive further EC activity, which in turn facilitates subsequent cold surges. Therefore, when ECs occur before and after cold surges, the cold surge event itself tends to be relatively strong and long lived. The transmission of energy by ECs is a primary link between the high and middle latitudes and contributes to the impact of cold surges on low latitudes. This study also explores the respective influences of the Siberia High and Aleutian Low on cold surges. The majority of cold surges that do not involve ECs occur in the context of the weaker Siberia High and Aleutian Low. Cold surges accompanied with ECs can be even stronger and longer lasting when the Siberia High and Aleutian Low strengthen.

Accurate identification of apple leaf diseases is of great significance for improving apple yield. The lesion area of the apple leaf disease image is small and vulnerable to background interference, which easily leads to low recognition accuracy. To solve this problem, a lightweight bilinear convolutional neural network (CNN) model named BLSENet based on attention mechanism is designed. The model consists of two subnetworks, and each subnetwork is embedded with a Squeeze-and-Excitation (SE) module. By using the feature extraction ability of the two subnetworks and combining the bilinear feature CONCAT operation, the multiscale features of the image are obtained. Compared with the unimproved model LeNet-5 (84.63%), BLSENet has higher accuracy in the test set, which indicates that SE module and bilinear feature fusion have a positive effect on the performance of the model, and BLSENet has the ability to identify apple leaf diseases. The model has achieved the expected goal and can provide technical support for accurate identification and real-time monitoring of apple disease images.

In the original publication [...]

In the wake of the dual-carbon objective, the call for low-carbon attributes in integrated energy systems is ascending, with an amplified imperative to integrate wind and solar power efficiently. This study introduces an advanced low-carbon optimization framework for integrated energy systems, incorporating a sophisticated time-differentiated carbon accounting mechanism attentive to consumer emissions. A nuanced carbon accounting model is crafted to assess consumer emissions with greater accuracy. Predicated on these emissions, a refined low-carbon demand response model is articulated, factoring in the influence of carbon emission factors pertinent to electricity and heat procurement on user conduct. This model integrates the consideration of heat reclaimed from methanation processes, which in turn informs the carbon emission factors associated with purchased heat, and evaluates the subsequent optimization impact on the system. The proposed model is designed to curtail the system’s operational expenditures and is operationalized via the CPLEX solver. Through the establishment of various scenarios for evaluative comparison, the model is corroborated to substantially augment the system’s proficiency in assimilating wind and solar energy, markedly curtail carbon emissions, and facilitate a sustainable and cost-efficient operation of the integrated energy system.

The applications of adjuvant chemotherapy and targeted drugs have greatly improved the prognosis of patients with advanced cancer, however the rapid emergence of drug resistance and the subsequent rapid progress of the disease have always been the unmet challenges in the field of cancer treatment. Adaptive therapy (AT) combined with Darwinian evolutionary dynamics is a new treatment concept different from the traditional maximum tolerated dose (MTD), which is expected to overturn the treatment paradigm of advanced cancer and achieve long-term low load tumor bearing survival. This paper reviewed the theory of AT and the important role of mathematical models in optimizing adaptive treatment strategies, then briefly described other tumor treatment strategies based on Darwinian dynamics, in order to provide new ideas for clinicians in the game with advanced cancer.

Polyinosinic-polycytidylic acid (poly I:C) is a synthesized analogue of viral double-strand RNA and considered as a potential immunostimulant in aquaculture. MicroRNAs (miRNAs) have been reported to play important roles in the development of the immune system and in regulation of host antiviral responses. In our earlier study, it was found that poly I:C pre-treatment could stimulate the resistance against cyprinid herpesvirus 2 (CyHV-2) infection and enhance the antiviral immune response in gibel carp. To understand the role of miRNAs in regulating the host response to poly I:C treatment, we investigated the expression profiles of miRNAs in the head kidney of poly I:C-treated gibel carp with small RNA sequencing technology. When compared with the untreated group, a total of 24 differentially expressed miRNAs were identified in the poly I:C-stimulated fish, among which, 7 and 17 miRNAs were upregulated and downregulated, respectively. Analysis of target genes of these differentially expressed miRNAs found that most targeted mRNAs were involved in catalytic activity, peptidase activity and endopeptidase activity, and were enriched in the metabolic, protein processing in endoplasmic reticulum and oxidative phosphorylation signaling pathways, suggesting that poly I:C could alter the expression of metabolism-related miRNAs in the kidney of gibel carp. Besides, it was noted that some immune-related miRNAs, including inflammation-related miRNAs (miR-192 and miR-731) and interferon-related miRNAs (miR-194a and miR-122), were downregulated after poly I:C treatment. In summary, it was found that poly I:C could regulate the cellular levels of specific miRNAs involved in metabolism and immune responses in the head kidney of gibel carp, which may increase the capacity of the immune cells to fight against pathogens infection.

Streamer discharge theory does not consider the influence of airflow on discharge. However, it is found experimentally that the airflow causes a great change in the breakdown process, especially in a nonuniform field. In this paper, a physical model of spark discharge in airflow is established considering the combined effect of the decrease in airflow density and the blowing away of positive ions and electrons on the breakdown process. Furthermore, the classic streamer breakdown criteria both in uniform field and nonuniform field are modified. This model extends the classic streamer breakdown criterion for static gases to the airflow environment.

Abstract We study the Lamb shift of a two-level atom arising from its coupling to the conformal massless scalar field, which satisfies the Dirichlet boundary condition, in the Hartle-Hawking vacuum in the BTZ spacetime, and find that the Lamb shift in the BTZ spacetime is structurally similar to that of a uniformly accelerated atom near a perfectly reflecting boundary in (2+1)-dimensional flat spacetime. Our results show that the Lamb shift is suppressed in the BTZ spacetime as compared to that in the flat spacetime as long as the transition wavelength of the atom is much larger than AdS radius of the BTZ spacetime while it can be either suppressed or enhanced if the transition wavelength of the atom is much less than AdS radius, depending on the location of the atom. In contrast, the Lamb shift is always suppressed very close to the horizon of the BTZ spacetime and remarkably it reduces to that in the flat spacetime as the horizon is approached although the local temperature blows up there.

Abstract Objective The purpose of this study was to provide evidence for early life care by meta-analyzing the relationship between infection during pregnancy and up to 2 years of age and the risk of subsequent allergic rhinitis (AR). Methods Published studies up to April 2022 were systematically searched in PubMed, Embase, Web of Science, Cochrane Library, SinoMed, CNKI, Wanfang Database, and VIP. Literature screening, including quality assessment, was performed, and the effect values (OR, HR, RR) and 95% confidence intervals (95% CI) of infection during pregnancy and up to 2 years of age and allergic rhinitis were extracted from each qualified study. Results In total, 5 studies with a sample size of 82,256 reported the relationship between infection during pregnancy and offspring AR. Meta-analysis showed that maternal infection during pregnancy was associated with an increased risk of childhood AR in offspring (OR = 1.34, 95% CI: 1.08–1.67). Altogether, 13 studies with a sample size of 78,426 reported evidence of an association between infection within 2 years of age and subsequent AR in children. A pooled meta-analysis of all studies showed that early infection within 2 years of age was closely associated with childhood AR (OR = 1.25, 95% CI: 1.12–1.40), especially upper respiratory tract infection (OR = 1.32, 95% CI: 1.06–1.65) and gastrointestinal infections (OR = 1.37, 95% CI: 1.01–1.86), but ear infection showed similar results in the cohort study (OR = 1.13, 95% CI: 1.04–1.22). Conclusion Current evidence suggests that infection during pregnancy, early upper respiratory infection, gastrointestinal infections and ear infection within 2 years of age would increase the risk of AR in children. Therefore, the prevention of infection during pregnancy and in infancy and young children needs to be emphasized.

While the doubly fed induction generator (DFIG) is widely applied in the new power system, its decoupled control and fluctuation of output power have led to serious problems in frequency stability. Inertia response control (IRC) of DFIG has attracted significant attention, while its impact has not been clearly researched. In this study, a low-order model of DFIG focusing on frequency stability is proposed. Firstly, the simplified model of DFIG considering the IRC is introduced through Taylor series expansion. The frequency response model considering the energy storage system (ESS) is proposed. Taking the rate of change of frequency (RoCoF) and steady-state frequency deviation (SFD) as the constraint, an analytical solution for the maximum proportion of DFIGs is deduced to reflect the impact of IRC on the system frequency stability. Finally, the accuracy of the proposed method and the effectiveness of IRC is verified on the modified IEEE-9 system.

Automated exercise assessment is of great importance for patients under rehabilitation exercise who require professional guidance. Among the existing approaches, the skeleton-based assessment model that classifies the correctness of the exercise has attracted much attention due to its relative ease of implementation and convenience in use. However, there are two problems with this approach. The first problem is its sensitivity to the orientation of the human skeleton. To solve this problem, we propose a novel rotation-invariant descriptor, the dot product matrix of the human skeleton, and prove mathematically that this descriptor discards only the orientation message that we do not expect while preserving all other useful information. Lack of feedback from the system is the second problem, because the exercisers do not know which parts of their exercises are incorrect. Therefore, we develop a visualization method for our system based on Gradient-Weighted Class Activation Mapping (Grad-CAM) and an quantitative metric called Overlap Ratio (OvR) to measure the quality of the visualization result. To demonstrate the effect of our method, we conduct experiments on two public datasets and a self-generated push-up dataset. The experimental results show that our rotation-invariant descriptor can achieve absolute robustness to orientation even under severe angle perturbations. In terms of accuracy and OvR, our method even outperforms previous works in most cases, indicating that the rotation-invariant descriptor helps the assessment model to extract more stable features. The visualization results are also informative to correct the movements; some examples are presented in this paper. The code of this paper and our push-up dataset are publicly available at https://github.com/Kelly510/RehabExerAssess.

The main purpose of this study was to investigate the composition, characterization and antioxidant activity of rice bran fermentation broth, and provide a new way for high-value utilization of rice bran. Firstly, we fermented rice bran with Hypsizigus marmoreus and purified fermentation broth with macroporous resins. We took feruloyl oligosaccharides (FOs) concentration as the measure index, and the results showed that the maximum concentration of FOs was 0.72 mmol/L on the 6th day of rice bran fermentation. We took D101 macroporous resin as adsorption resin for rice bran fermentation broth, and the result showed that FOs concentration reached 2.38 mmol/L with the optimal purification process at pH 4.5, temperature 29 °C, ethanol concentration 55%, sample flow rate 1.5 mL/min, sample concentration 1.7 mL/min and elution flow rate 2.0 mmol/L. Secondly, the characters of rice bran fermentation broth were identified by high-performance liquid chromatography (HPLC) and Fourier-transform infrared spectroscopy (FTIR). These methods showed the presence of ferulic acid (FA), arabinose, xylose and glucose in rice bran fermentation broth. Finally, the in vitro antioxidant activities of rice bran fermentation broth were tested and the result showed that fermentation broth had good antioxidant activities and significantly improved after purification.

We present a simulation of Jupiter’s quasi-quadrennial oscillation (QQO) in a 2D radiative-dynamical model. Launching an eastward Kelvin wave and a westward Rossby-gravity wave in the lower boundary, we successfully generate a 4 yr-period oscillation in the equatorial stratosphere. The momentum flux of waves initiates overlying easterly–westerly wind jets descending in altitude with the maximum temperature variation of ±5 K near 10 hPa at the equator. The tropical stratospheric region is dominated by upwelling and downwelling circulation cells induced by the QQO, affecting the midlatitude where stratospheric aerosols enrich. The simulation results are consistent with the previous satellite and ground-based observations in the low latitudes and provide the ability to examine the QQO’s influence in Jupiter’s extratropical stratosphere. The QQO influence further extends into the upper troposphere, forming a weak anticorrelation with the stratosphere oscillation in agreement with the result from 40 yr of telescope observations.

Abstract A systematic solution is developed to improve the autonomous capability of the quadruped robot with a manipulator, such as navigation, recognition and operation. The developed system adopts novel software, hardware system and system architecture, including a specially designed environment awareness system (EAS). Based on the camera and LiDAR on the EAS, the recognition of multiple common targets, such as the leader, door, window and bag, is achieved. In terms of navigation, a location method is built, that combines the laser odometer and global positioning system. A mapping and path planning module is designed by the Robot‐centric Elevation Mapping algorithm and the rapidly exploring rand tree algorithm. For operation, a real‐time target grasp detection system is proposed based on the You Only Look Once v5 algorithm to improve the success rate of tasks. The whole system is integrated based on the task relevance scheduling strategy to reduce the computational complexity. The tightly integrated system and the subsystems are evaluated by conducting simulations and physical experiments in robot recognition, navigation and operation. Extensive experiments show that the proposed framework can better achieve the autonomous navigation and operation of the quadruped robot with a manipulator. Notably, the proposed framework is still effective when facing dynamic objects. In addition, the system can be easily extended to other forms of mobile robot.

The most widely applied doubly-fed induction generator (DFIG) leads to insufficient frequency regulation ability of power system. The virtual inertia control can adjust the active power of DFIG according to frequency fluctuation. However, the frequent changes in power flow and operating point bring great challenges to traditional virtual inertia controller with fixed parameters. Direct Heuristic Dynamic Programming (Direct HDP) based control parameter regulator is proposed in this paper to obtain the optimal control parameters when the operation condition changes. Compared with the initial parameters, the response has been significantly improved after adaptive optimization by the proposed method when the system operating point changes.

Abstract Due to the strong coupling among the conductors of 10 kV three‐core armored cables and the difficulty in identifying its defects and fault types, a method is proposed based on the input impedance spectrum. Firstly, the phase mode transformation matrix of a three‐core cable is obtained by combining the multi‐conductor transmission line theory with the loop analysis method to realize decoupling between conductors. Secondly, the input impedance matrices of a cable under different situations are derived. Based on this, a method is proposed to identify the local defects and fault types. The capacitive defects and inductive defects are identified according to the left or right offset of the amplitude spectrum; the short circuit and break faults of the cable can be identified according to the number of resonant points in the amplitude spectrum and the initial phase angle of the phase spectrum. Finally, to verify the correctness of the proposed method, a 10 kV three‐core cable is taken as an example to carry out PSCAD circuit simulation and practical test. The results show that the proposed method can effectively identify the local defects and fault types of the three‐core cable.

The demands for machine learning and knowledge extraction methods have been booming due to the unprecedented surge in data volume and data quality. Nevertheless, challenges arise amid the emerging data complexity as significant chunks of information and knowledge lie within the non-ordinal realm of data. To address the challenges, researchers developed considerable machine learning and knowledge extraction methods regarding various domain-specific challenges. To characterize and extract information from non-ordinal data, all the developed methods pointed to the subject of Information Theory, established following Shannon’s landmark paper in 1948. This article reviews recent developments in entropic statistics, including estimation of Shannon’s entropy and its functionals (such as mutual information and Kullback–Leibler divergence), concepts of entropic basis, generalized Shannon’s entropy (and its functionals), and their estimations and potential applications in machine learning and knowledge extraction. With the knowledge of recent development in entropic statistics, researchers can customize existing machine learning and knowledge extraction methods for better performance or develop new approaches to address emerging domain-specific challenges.

Bi2O2Se holds potential for the realization of 2D optical modulators due to its broadband nonlinear response, air stability and carrier mobility. Here, the authors report the realization of defect-engineered Bi2O2Se nanoplates as saturable absorbers for femtosecond solid-state lasers, showing improved output power and pulse duration.

Neuropsychiatric systemic lupus erythematosus (NPSLE) is the diagnosis that rheumatologists most often need to consider when a patient with lupus presents with neurologic symptoms. However, neurological involvement is rare in systemic sclerosis (SSc), and high doses of steroids tend to trigger scleroderma renal crisis (SRC). When a patient with SSc overlapping SLE presents with epilepsy and renal crisis, the exact diagnosis and whether to initiate high-dose glucocorticoid therapy are questions to ponder. Here, we report a patient with overlap syndrome (SSc overlapping SLE), who developed CNS symptoms, and improved after treatment against SRC after excluding NPSLE. We report this case with the aim of arousing the attention of rheumatologists to SSc and SRC-related encephalopathy when SSc was overlapped with SLE.

Gastric cancer remains the fourth most frequently diagnosed malignancy and the fifth leading cause of cancer-related mortality worldwide owning to the lack of efficient drugs and targets for therapy. Accumulating evidence indicates that UPS, which consists of E1, E2, and E3 enzymes and proteasome, plays an important role in the GC tumorigenesis. The imbalance of UPS impairs the protein homeostasis network during development of GC. Therefore, modulating these enzymes and proteasome may be a promising strategy for GC target therapy. Besides, PROTAC, a strategy using UPS to degrade the target protein, is an emerging tool for drug development. Thus far, more and more PROTAC drugs enter clinical trials for cancer therapy. Here, we will analyze the abnormal expression enzymes in UPS and summarize the E3 enzymes which can be developed in PROTAC so that it can contribute to the development of UPS modulator and PROTAC technology for GC therapy.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an emerging porcine intestinal coronavirus that can cause acute diarrhea, vomiting, rapid weight loss, and high mortality in newborn piglets. Cholesterol 25-hydroxylase (CH25H) is a molecular mediator of innate antiviral immunity and converts cholesterol to 25-hydroxycholesterol (25HC). Previous studies have reported that CH25H and 25HC have an antiviral effect against multiple viruses. However, the interplay between SADS-CoV infection and CH25H or 25HC is still uncertain. Here, we found that CH25H and its enzymatic product 25HC restrained SADS-CoV replication by blocking membrane fusion. Our results show that CH25H was upregulated by SADS-CoV infection in vitro and in vivo, and that it was an IFN-stimulated gene in porcine ileum epithelial cells. Moreover, CH25H and CH25H mutants lacking catalytic activity can inhibit SADS-CoV replication. Furthermore, 25HC significantly suppressed SADS-CoV infection by inhibiting virus entry. Notably, we confirmed that CH25H and 25HC blocked SADS-CoV spike protein-mediated membrane fusion. Our data provide a possible antiviral therapy against SADS-CoV and other conceivable emerging coronaviruses in the future.

Abstract It has been shown that the vacuum state of a free quantum field is entangled and such vacuum entanglement can be harvested by a pair of initially uncorrelated detectors interacting locally with the vacuum field for a finite time. In this paper, we examine the entanglement harvesting phenomenon of two non-identical inertial detectors with different energy gaps locally interacting with massless scalar fields via a Gaussian switching function. We focus on how entanglement harvesting depends on the energy gap difference from two perspectives: the amount of entanglement harvested and the harvesting-achievable separation between the two detectors. In the sense of the amount of entanglement, we find that as long as the inter-detector separation is not too small with respect to the interaction duration parameter, two non-identical detectors could extract more entanglement from the vacuum state than the identical detectors. There exists an optimal value of the energy gap difference when the inter-detector separation is sufficiently large that renders the harvested entanglement to peak. Regarding the harvesting-achievable separation, we further find that the presence of an energy gap difference generally enlarges the harvesting-achievable separation range. Our results suggest that the non-identical detectors may be advantageous to extracting entanglement from vacuum in certain circumstances as compared to identical detectors.

Autophagy plays an important role in the infectious processes of diverse pathogens. For instance, cellular autophagy could be harnessed by viruses to facilitate replication. However, it is still uncertain about the interplay of autophagy and swine acute diarrhea syndrome coronavirus (SADS-CoV) in cells. In this study, we reported that SADS-CoV infection could induce a complete autophagy process both in vitro and in vivo, and an inhibition of autophagy significantly decreased SADS-CoV production, thus suggesting that autophagy facilitated the replication of SADS-CoV. We found that ER stress and its downstream IRE1 pathway were indispensable in the processes of SADS-CoV-induced autophagy. We also demonstrated that IRE1-JNK-Beclin 1 signaling pathway, neither PERK-EIF2S1 nor ATF6 pathways, was essential during SADS-CoV-induced autophagy. Importantly, our work provided the first evidence that expression of SADS-CoV PLP2-TM protein induced autophagy through the IRE1-JNK-Beclin 1 signaling pathway. Furthermore, the interaction of viral PLP2-TMF451-L490 domain and substrate-binding domain of GRP78 was identified to activate the IRE1-JNK-Beclin 1 signaling pathway, and thus resulting in autophagy, and in turn, enhancing SADS-CoV replication. Collectively, these results not only showed that autophagy promoted SADS-CoV replication in cultured cells, but also revealed that the molecular mechanism underlying SADS-CoV-induced autophagy in cells.

Visual detection technology is essential for an unmanned surface vehicle (USV) to perceive the surrounding environment; it can determine the spatial position and category of the object, which provides important environmental information for path planning and collision prevention of the USV. During a close-in reconnaissance mission, it is necessary for a USV to swiftly navigate in a complex maritime environment. Therefore, an object detection algorithm used in USVs should have high detection s peed and accuracy. In this paper, a YOLOv5 lightweight object detection algorithm using a Ghost module and Transformer is proposed for USVs. Firstly, in the backbone network, the original convolution operation in YOLOv5 is upgraded by convolution stacking with depth-wise convolution in the Ghost module. Secondly, to exalt feature extraction without deepening the network depth, we propose integrating the Transformer at the end of the backbone network and Feature Pyramid Network structure in the YOLOv5, which can improve the ability of feature expression. Lastly, the proposed algorithm and six other deep learning algorithms were tested on ship datasets. The results show that the average accuracy of the proposed algorithm is higher than that of the other six algorithms. In particular, in comparison with the original YOLOv5 model, the model size of the proposed algorithm is reduced to 12.24 M, the frames per second reached 138, the detection accuracy was improved by 1.3%, and the mean of average precision (0.5) reached 96.6% (from 95.3%). In the verification experiment, the proposed algorithm was tested on the ship video collected by the “JiuHang 750” USV under different marine environments. The test results show that the proposed algorithm has a significantly improved detection accuracy compared with other lightweight detection algorithms.

Abstract Background Salt stress is often associated with excessive production of reactive oxygen species (ROS). Oxidative stress caused by the accumulation of ROS is a major factor that negatively affects crop growth and yield. Root is the primary organ that senses and transmits the salt stress signal to the whole plant. How oxidative stress affect redox sensitive proteins in the roots is not known. Results In this study, the redox proteome of sugar beet M14 roots under salt stress was investigated. Using iTRAQ reporters, we determined that salt stress caused significant changes in the abundance of many proteins (2305 at 20 min salt stress and 2663 at 10 min salt stress). Using iodoTMT reporters, a total of 95 redox proteins were determined to be responsive to salt stress after normalizing again total protein level changes. Notably, most of the differential redox proteins were involved in metabolism, ROS homeostasis, and stress and defense, while a small number play a role in transport, biosynthesis, signal transduction, transcription and photosynthesis. Transcription levels of 14 genes encoding the identified redox proteins were analyzed using qRT-PCR. All the genes were induced by salt stress at the transcriptional level. Conclusions Based on the redox proteomics results, we construct a map of the regulatory network of M14 root redox proteins in response to salt stress. This study further refines the molecular mechanism of salt resistance at the level of protein redox regulation.

Abstract An increase in apoptosis and/or defects in the clearance of apoptotic cells resulting in massive secondary necrosis have been recognized as the main causes of systemic lupus erythematosus (SLE). Recent findings have revealed that gasdermin E (GSDME)-mediated pyroptosis is a mechanism associated with secondary necrosis. We aimed to investigate the effects of GSDME-mediated pyroptosis on disease activity in lupus mice. In vivo, high levels of GSDME expression were observed in the renal tubules of pristane-induced lupus (PIL) mice and SLE patients. In lupus mice, GSDME knockout or SP600125 administration effectively ameliorated lupus-like features by inhibiting GSDME-mediated renal tubular epithelial cell pyroptosis. In vitro, treatment with tumour necrosis factor-α (TNF-α) plus cycloheximide (CHX) or SLE sera induced HK2 cells to undergo pyroptosis in a caspase-3- and GSDME-dependent manner. Likewise, SP600125 significantly reduced GSDME expression and decreased pyroptosis in HK2 cells. GSDME-mediated pyroptosis may be associated with SLE pathogenesis, and targeting GSDME may be a potential strategy for treating SLE.

As an important part of soil and water conservation, ecological stability, and climate regulation, vegetation is sensitive to climate change and human disturbance. At present, there is a lack of research on the dynamic changes to vegetation in river basins and sub-basins from a holistic and partial perspective, which limits our ability to understand the spatial heterogeneity of vegetation changes and their influencing factors. In this study, the spatial and temporal variations of vegetation and their influencing factors in the Songliao River Basin (SLB) from 2000 to 2020 were analyzed using Sen’s trend method, the Mann–Kendall test, the coefficient of variation method, and the Geodetector method. The results showed that the NDVI (normalized difference vegetation index) in the SLB exhibited an increasing trend of 0.003 yr−1, indicating that the vegetation was greening. In general, climatic factors and soil type were the dominant factors affecting the spatial differentiation of the NDVI in the SLB and sub-basin units. The interactions between the influencing factors were all enhanced, and the population density highlighted its influence on reflected vegetation changes. We also focused on analyzing the spatial differentiation of vegetation changes and influencing factors in the sub-basins. The research results provide a basis for the ecological restoration and stability of the basin.

An open-set recognition scheme for tree leaves based on deep learning feature extraction is presented in this study. Deep learning algorithms are used to extract leaf features for different wood species, and the leaf set of a wood species is divided into two datasets: the leaf set of a known wood species and the leaf set of an unknown species. The deep learning network (CNN) is trained on the leaves of selected known wood species, and the features of the remaining known wood species and all unknown wood species are extracted using the trained CNN. Then, the single-class classification is performed using the weighted SVDD algorithm to recognize the leaves of known and unknown wood species. The features of leaves recognized as known wood species are fed back to the trained CNN to recognize the leaves of known wood species. The recognition results of a single-class classifier for known and unknown wood species are combined with the recognition results of a multi-class CNN to finally complete the open recognition of wood species. We tested the proposed method on the publicly available Swedish Leaf Dataset, which includes 15 wood species (5 species used as known and 10 species used as unknown). The test results showed that, with F1 scores of 0.7797 and 0.8644, mixed recognition rates of 95.15% and 93.14%, and Kappa coefficients of 0.7674 and 0.8644 under two different data distributions, the proposed method outperformed the state-of-the-art open-set recognition algorithms in all three aspects. And, the more wood species that are known, the better the recognition. This approach can extract effective features from tree leaf images for open-set recognition and achieve wood species recognition without compromising tree material.

The effect of ZnO nanoparticles (ZnO NPs), with different concentrations in simulated water, on the activity of sulfate-reducing bacteria (SRB) and their adhesion behaviour on stainless-steel surfaces, with and without visible light treatment, were investigated. The results showed that the concentration of ZnO NPs and light treatment greatly influenced the antibacterial performance of the NPs. In the water solution without light treatment, the low concentration (no more than 1 mg/L) of ZnO NPs in the aqueous solution promoted the growth of SRB, and the amount of biofilm attached to the stainless-steel surface increased. As the concentration increased, ZnO NPs exhibited antibacterial effects. In water under visible light irradiation, ZnO NPs showed antibacterial performance at all the concentrations studied (0.5~50 mg/L), and the antibacterial efficiency increased with the increase in the concentration of NPs. The determination results of the reactive oxygen species showed that light treatment can stimulate ZnO NPs in water to generate ·OH and O2·−, which exhibited good antibacterial properties. The adhesion amount of SRB on the stainless-steel surface was inversely proportional to the antibacterial efficiency of ZnO NPs.

To address the increasing energy consumption and serious environmental problems, it is critical to develop efficient and clean energy conversion and storage devices. Among various categories of materials, metal-organic frameworks (MOFs) are one of the promising candidates that can realize the practical application of these devices. Therefore, it has been recognized that revealing the composition-structure-property relationship of MOFs by transmission electron microscopy (TEM) can offer some guidelines for designing novel materials with desirable properties. Nevertheless, owing to their organic parts, MOFs are too beam sensitive to be characterized by high energy electrons. To resolve this problem, various advanced techniques have been developed to accomplish the static and dynamic MOFs characterizations. Herein, we made a brief summary of the updated progress on characterization of MOFs by TEM until now, and revealed the key issues associated with static and dynamic TEM characterization of MOFs.

PurposeWe aimed to ascertain the effectiveness of gonadotropin-releasing hormone (GnRH) agonist co-therapy for the preservation of ovarian function in patients with ovarian malignancy who underwent unilateral salpingo-oophorectomy and platinum-based chemotherapy.MethodsWe enrolled 158 patients with ovarian malignancy who underwent fertility preservation surgery and postoperative platinum-based chemotherapy between January 2018 and December 2020. Patients were divided into two groups based on the use of GnRH agonist (GnRHa) during chemotherapy. Two patients withdrew from the study. Laboratory tests (serum follicle-stimulating hormone [FSH], serum luteinizing hormone [LH], and serum anti-Müllerian hormone [AMH]) were performed pre-chemotherapy and one year post-chemotherapy. Data on menstruation resumption, perimenopausal symptoms (modified Kupperman Menopausal Index [KMI]), health-related quality of life (Medical Outcomes Study Short Form-36 [MOS SF-36]), and obstetric outcomes were collected.ResultsOne year post-chemotherapy, the serum AMH level in the GnRHa group was higher than that in the control group (P