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Round ligament varicosities (RLV) are a very rare cause of an inguinal mass, which is very similar to an inguinal hernia, and should be taken seriously by women, especially in mid-pregnancy. Ultrasound can confirm the diagnosis of the RLV and can prevent unnecessary interventions.We report a case of a patient with bilateral RLV: the primigravida was 31 years old, G1P0, gestation 30+2w. The patient presented to the clinic 1 month ago due to the discovery of bilateral inguinal masses. After the diagnosis was confirmed by ultrasound, this patient received regular reviews during labor and delivery and is currently in good maternal condition.The patient came to the clinic 1 month after the discovery of bilateral inguinal area masses for 1 month.

Highlights A comprehensive review focused on the whole systems of the soft robotics with artificial intelligence, which can feel, think, react and interact with humans, is presented. The design strategies concerning about various aspects of the soft robotics, like component materials, device structures, prepared technologies, integrated method, and potential applications, are summarized. A broad outlook on the future considerations for the soft robots is proposed.

Abstract Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for personalized treatment. This study explored the role of ultrasound-based radiomics of peritumoral tissues for predicting HCC features, focusing on differentiation, cytokeratin 7 (CK7) and Ki67 expression, and p53 mutation status. A cohort of 153 patients with HCC underwent ultrasound examinations and radiomics features were extracted from peritumoral tissues. Subgroups were formed based on HCC characteristics. Predictive modeling was carried out using the XGBOOST algorithm in the differentiation subgroup, logistic regression in the CK7 and Ki67 expression subgroups, and support vector machine learning in the p53 mutation status subgroups. The predictive models demonstrated robust performance, with areas under the curves of 0.815 (0.683–0.948) in the differentiation subgroup, 0.922 (0.785–1) in the CK7 subgroup, 0.762 (0.618–0.906) in the Ki67 subgroup, and 0.849 (0.667–1) in the p53 mutation status subgroup. Confusion matrices and waterfall plots highlighted the good performance of the models. Comprehensive evaluation was carried out using SHapley Additive exPlanations plots, which revealed notable contributions from wavelet filter features. This study highlights the potential of ultrasound-based radiomics, specifically the importance of peritumoral tissue analysis, for predicting HCC characteristics. The results warrant further validation of peritumoral tissue radiomics in larger, multicenter studies.

A series of flavonol derivatives containing piperidine sulfonamide were designed and synthesized. The EC50 values for the curative of tobacco mosaic virus (TMV) by Z6 and Z22 were 108.2 and 102.7 μg/mL, respectively, outperforming the control agent ningenmycin (NNM) with an EC50 value of 253.8 μg/mL. Additionally, the EC50 values for the protective activity of Z6 and Z21 were 100.9 and 123.2 μg/mL, respectively, also surpassing the control agent NNM with an EC50 value of 203.7 μg/mL. Microscale thermophoresis (MST) and molecular docking test showed that Z6 bound well with tobacco mosaic virus coat protein (TMV-CP). The biological safety test showed that Z6 had almost no effect on seed germination and seedling growth. After treatment with Z6, the chlorophyll content and superoxide dismutase (SOD) activity in tobacco leaves increased, while the malondialdehyde (MDA) content decreased. Therefore, Z6 has a high probability as a potential antiviral agent.

In recent decades, the prevalence of myopia has been on the rise globally, attributed to changes in living environments and lifestyles. This increase in myopia has become a significant public health concern. High myopia can result in thinning of the sclera and localized ectasia of the posterior sclera, which is the primary risk factor for various eye diseases and significantly impacts patients' quality of life. Therefore, it is essential to explore effective prevention strategies and programs for individuals with myopia. Collagen serves as the principal molecule in the extracellular matrix (ECM) of scleral tissue, consisting of irregular collagen fibrils. Collagen plays a crucial role in myopia progression and control. During the development of myopia, the sclera undergoes a thinning process which is primarily influenced by collagen expression decreased and remodeled, thus leading to a decrease in its biomechanical properties. Improving collagen expression and promoting collagen crosslinking can slow down the progression of myopia. In light of the above, improving collagen expression or enhancing the mechanical properties of collagen fibers via medication or surgery represents a promising approach to control myopia.

BackgroundVitamins A and D are essential for the health of pregnant women and infants. Nevertheless, the relationship between umbilical cord blood vitamins A and D levels and the physical growth of exclusively breastfed infants remains uncertain.ObjectiveThis cohort study aims to examine the relationship between cord blood vitamins A and D levels and the physical growth of exclusively breastfed infants aged 0–6 months.Methods140 singleton mother–infant pairs were recruited in total. Questionnaires were used to collect maternal and infant information, and liquid chromatography was utilized to quantify the levels of vitamins A and D in the umbilical cord blood. Anthropometric measurements were conducted at birth, at 3 and 6 months of age, and the weight-for-age z-score (WAZ), length-for-age z-score (LAZ), head circumference-for-age z-score (HAZ), and BMI-for-age z-score (BMIZ) were calculated. Univariate and multivariate linear regression models were used for the analysis.ResultsThe average concentration of vitamins A and D in cord blood was 0.58 ± 0.20 μmol/L and 34.07 ± 13.35 nmol/L, both below the normal range for children. After adjusting for confounding factors, vitamin A levels in cord blood positively correlated with HAZ growth in infants aged 3–6 months (β= 0.75, P < 0.01) while vitamin D levels negatively correlated with LAZ growth (β= −0.01, P = 0.01) and positively correlated with BMIZ growth (β= 0.02, P < 0.01).ConclusionHigher Vitamin A levels at birth promote HAZ growth in infants aged 3–6 months while higher vitamin D levels at birth promote BMIZ growth in infants aged 3–6 months.Clinical trial registrationhttps://register.clinicaltrials.gov, identifier NCT04017286.

Highlights Naturally crosslinked carbonaceous liquid metal aqueous printable ink mediated by biopolymers. E-textile with conductivity, stability, wearability, and aesthetic characteristics. Multi-applications in health monitoring, pressure sensing, and energy harvesting.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive disorder, which is caused mostly by frame-disrupting, out-of-frame variation in the dystrophin (DMD) gene. Loss-of- function mutations are the most common type of mutation in DMD, accounting for approximately 60–90% of all DMD variations. In this study, we used adenine base editing to generate a human embryonic stem cell line with splice-site mutations to mimic exon deletion variants in clinical Duchenne muscular dystrophy patients. This cell line has differentiation potential and a normal karyotypic.

Abstract Acute respiratory distress syndrome (ARDS) is a major disease that threatens the life and health of neonates. Vitamin A (VA) can participate in early fetal lung development and affect lung immune function. Researches revealed that the serum VA level in premature infants with ARDS was lower than that in premature infants without ARDS of the same gestational age, and premature infants with VA deficiency (VAD) were more likely to develop ARDS. Moreover, the VA levels can be used as a predictor of the development and severity of neonatal ARDS. However, the critical question here is; Does ARDS develop due to VAD in these systemic diseases? Or does ARDS develop because these diseases cause VAD? We hypothesize that VAD may aggravate neonatal ARDS by affecting immunity, metabolism, barriers and other pathways. In this article, we used multiomics analysis to find that VAD may aggravate ARDS mainly through the Fc epsilon RI signaling pathway, the HIF-1 signaling pathway, glutathione metabolism, and valine, leucine and isoleucine degradation signaling pathways, which may provide the molecular pathogenic mechanism behind the pathology of VAD-aggravated ARDS and can also provide potential molecular targets for subsequent research on ARDS.

Since reservoirs with permeability less than 10 mD are characterized by high injection difficulty, high-pressure drop loss, and low pore throat mobilization during the water drive process, CO2 is often used for development in actual production to reduce the injection difficulty and carbon emission simultaneously. However, microfractures are usually developed in low-permeability reservoirs, which further reduces the injection difficulty of the driving medium. At the same time, this makes the injected gas flow very fast, while the gas utilization rate is low, resulting in a low degree of recovery. This paper conducted a series of studies on the displacement effect of CO2-soluble foaming systems in low-permeability fractured reservoirs (the permeability of the core matrix is about 0.25 mD). For the two CO2-soluble blowing agents CG-1 and CG-2, the effects of the CO2 phase state, water content, and oil content on static foaming performance were first investigated; then, a more effective blowing agent was preferred for the replacement experiments according to the foaming results; and finally, the effects of the blowing agents on sealing and improving the recovery degree of a fully open fractured core were investigated at different injection rates and concentrations, and the injection parameters were optimized. The results show that CG-1 still has good foaming performance under low water volume and various oil contents and can be used in subsequent fractured core replacement experiments. After selecting the injection rate and concentration, the blowing agent can be used in subsequent fractured cores under injection conditions of 0.6 mL/min and 2.80%. In injection conditions, the foaming agent can achieve an 83.7% blocking rate and improve the extraction degree by 12.02%. The research content of this paper can provide data support for the application effect of a CO2-soluble blowing agent in a fractured core.

Background Diacetyl (DC) is widely used in the food flavoring industry and excessive occupational exposure to DC can cause serious respiratory diseases. However, there is no corresponding national standard method for the determination of DC in the air of workplace.Objective To establish a method for the determination of DC in workplace air by high performance liquid chromatography using 4-nitro-o-phenylenediamine (NPDA) as precolumn derivatization.Methods DC in the air of workplace was collected by solution absorption method. This experiment used NPDA as the derivatization reagent. By adjusting acidity of solution and optimizing concentration ration of DC/NPDA, derivatization temperature, and time, a method for the determination of DC in workplace air was proposed, and its performance indexes such as linearity, detection limit, and lower limit of quantification were obtained. Sampling efficiency was evaluated by relative comparison method, and sample stability was evaluated by sample preservation test. Accuracy and precision of the method were evaluated by standard addition recovery test with blank samples, and an interference test was carried out by adding standard samples. The established method was applied to actual samples to evaluate its adaptability.Results A combination of 60 °C for 2 h was selected for derivatization because a higher derivatization reaction temperature and a longer reaction time associated with a higher derivatization efficiency. The solution was separated by SB-C18 column (250 mm×4.6 mm, 5 μm) at 30 ℃, using a mixture of methanol and water (v/v, 65%/35%) as mobile phase with an elution flow rate of 1.0 mL·min−1, and was detected with a variable wavelength detector (λmax=257 nm) by qualitative analysis based on retention time and quantitative analysis based on external standard method. In terms of the proposed method, the linear range of detection was from 5 μg·L−1 to 2000 μg·L−1, with a correlation coefficient of 0.9999, and a detection limit of 1.3 μg·L−1, the quantitative detection of the lower limit was 4.3 μg·L−1, with a sampling volume V0 of 3.0 L, the minimum detection concentration was 4.3 μg·m−3, and the minimum quantitative concentration was 14.3 μg·m−3. The recovery rate was 99.1%-100.8%, the intra-batch precision was 0.5%-3.0%, and the inter-batch precision was 1.2%-2.0%. The average sampling efficiency of this method was 94.5%, and the sample could be stored at 4 °C for at least 14 d. The coexisting components in the air of the workplace did not interfere with the determination of DC. The DC content in the air of a flavor workplace was 5.86-8.85 mg·m−3.ConclusionA determination method for DC in workplace air by high performance liquid chromatography using NPDA as precolumn derivatization after being collected by 1.0% phosphoric acid absorbent is proposed and has the advantages of simple operation, high sensitivity, and good accuracy. With no DC loss and degradation, the method may satisfy the request for DC determination in the air of workplace.

Abstract Background Previous observational studies have reported that delirium has an association with an increased risk of Alzheimer's disease (AD), and that patients with AD have a higher risk of developing delirium. However, due to the limitations of observational study, it is challenging to confirm whether delirium has a causal effect on AD or reverse causation exists. Methods A bidirectional two-sample Mendelian randomization (MR) was performed to investigate the relationship between delirium and AD. Summary statistics from genome-wide association studies of delirium and AD phenotypes were utilized. Inverse-variance weighted (IVW) method was used as the main analysis approach, and additional analyses were performed using MR Egger, weighted median, simple mode and weighted mode to ensure result accuracy. Heterogeneity and horizontal pleiotropy were assessed using Cochran's Q statistics and MR Egger intercept, separately. Results The MR analyses showed that genetically predicted delirium was not associated with AD (IVW: odds ratio [OR] 0.98, 95% CI 0.91–1.05, P = 0.544; MR Egger: OR 0.98, 95% CI 0.83–1.15, P = 0.780; weighted median: OR 0.96, 95% CI 0.88–1.05, P = 0.323; simple mode: OR 0.91, 95% CI 0.80–1.04, P = 0.212; weighted mode: OR 0.93, 95% CI 0.83–1.05, P = 0.277). However, in the reverse direction, AD was associated with delirium (IVW: OR 1.32, 95% CI 1.13–1.54, P = 3.91E-04; MR Egger: OR 1.42, 95% CI 1.02–1.98, P = 5.60E-02; Weighted median: OR 1.39, 95% CI 1.18–1.63, P = 8.22E-05; Simple mode: OR 1.41, 95% CI 1.10–1.80, P = 1.41E−02; Weighted mode: OR 1.39, 95% CI 1.16–1.67, P = 3.23E-03). Conclusion Based on the results of our MR study, there is no bidirectional causality between delirium and AD, delirium is not associated with an increased risk of AD, while genetically predicted AD is a potential causal risk factor for delirium.

Photovoltaic (PV) panels are one of the popular green energy resources and PV panel parameter estimations are one of the popular research topics in PV panel technology. The PV panel parameters could be used for PV panel health monitoring and fault diagnosis. Recently, a PV panel parameters estimation method based in neural network and numerical current predictor methods has been developed. However, in order to further improve the estimation accuracies, a new approach of PV panel parameter estimation is proposed in this paper. The output current and voltage dynamic responses of a PV panel are measured, and the time series of the I–V vectors will be used as input to an artificial neural network (ANN)-based PV model parameter range classifier (MPRC). The MPRC is trained using an I–V dataset with large variations in PV model parameters. The results of MPRC are used to preset the initial particles’ population for a particle swarm optimization (PSO) algorithm. The PSO algorithm is used to estimate the PV panel parameters and the results could be used for PV panel health monitoring and the derivation of maximum power point tracking (MMPT). Simulations results based on an experimental I–V dataset and an I–V dataset generated by simulation show that the proposed algorithms can achieve up to 3.5% accuracy and the speed of convergence was significantly improved as compared to a purely PSO approach.

This study proposes a multi-objective optimization (MOO) strategy with an improved constraint-handling technique to improve the crashworthiness of an excavator rollover protective structure (ROPS). First, the experimental test under the ISO 12117 criteria is conducted and the developed numerical model is verified. Then, the amounts of energy absorption and the cross-sectional forces of components in the ROPS are analyzed. The main energy absorbing and load carrying components are identified. Finally, the thicknesses of the identified components are considered as the design variables. A multi-objective crashworthiness optimization process aims at improving the safety distance and reducing the total mass is designed by the finite element analysis-based surrogate model technique and a modified MOO algorithm. The proposed algorithm modifies the objective function values of an individual with its constraint violations and the true objective function values, of which adaptive penalty weights fed back from the constraint violations are used to keep the balance. Compared with the existing methods, it is found that the optimal solutions obtained by the proposed algorithm show superiority on convergence rate and diversity of distribution. The optimal results show that the safety distance is 27.42% higher while the total mass is 7.06% lower than those of the baseline design when it meets the requirements of ISO 12117. This study provides an alternative crashworthiness design route for the ROPS of the construction machines.

BackgroundSitus inversus totalis (SIT) is an uncommon disorder characterized by mirror-image anatomy, which can present unique challenges and potential vascular anomalies in surgical interventions, particularly in gastric cancer patients.AimsWe aim to delineate a rare case of gastric adenocarcinoma in a SIT patient and conduct a thorough review of the existing literature concerning surgical strategies, vascular anomalies, and outcomes observed across varied geographic locales and technological approaches.MethodsA thorough examination of a case involving a 39-year-old male SIT patient who underwent a successful distal gastrectomy with D2 lymph node dissection is presented alongside an expansive literature review. The review encompasses 47 articles, collating data on surgical approaches and vascular anomalies across 49 patients diagnosed with SIT and gastric cancer.ResultsThe patient underwent curative distal gastrectomy and Billroth II with Braun anastomosis within 95 minutes, incurring minimal intraoperative blood loss (100ml). Postoperative pathology confirmed moderately to poorly differentiated gastric adenocarcinoma (pT3N0M0), with no signs of recurrence or metastasis after 6 months of S-1 adjuvant chemotherapy. The literature review revealed vascular anomalies in approximately 20% of reported cases, accentuating its surgical significance. Noteworthy variations in surgical strategies, operative times, blood loss, and complications across different surgical modalities were observed, providing a comprehensive view into the practical management of such cases.ConclusionDespite the inherent challenges associated with SIT, various surgical techniques can be successfully applied with meticulous preoperative planning and understanding vascular anomalies. This compilation of diverse surgical experiences across numerous documented cases seeks to provide a consolidated resource for refining surgical strategies and enhancing postoperative outcomes for gastric cancer patients with SIT, underscoring the imperativeness of further research in this niche domain.

Somatostatin receptor 2 (SSTR2) represents a therapeutic target of neuroendocrine tumors. Here, authors report two structures of SSTR2 bound to peptide octreotide and small molecule paltusotine, revealing the basis subtype selectivity and signal bias properties.

Developmental coordination disorder (DCD) is a motor learning disability with a prevalence of 5%-6% in school-aged children, which may seriously affect the physical and mental health of affected children. Behavior analysis of children helps explore the mechanism of DCD and develop better diagnosis protocols. In this study, we investigate the behavioral pattern of children with DCD in the gross movement using a visual-motor tracking system. First, visual components of interest are detected and extracted using a series of intelligent algorithms. Then, the kinematic features are defined and calculated to describe the children behavior, including eye movement, body movement, and interacting object trajectory. Finally, statistical analysis is conducted both between groups with different motor coordination abilities and between groups with different task outcomes. The experimental results show that groups of children with different coordination abilities differ significantly both in the duration of eye gaze focusing on the target and in the degree of concentration during aiming, which can serve as behavioral markers to distinguish children with DCD. This finding also provides precise guidance for the interventions for children with DCD. In addition to increasing the amount of time spent on concentrating, we should focus on improving children’s attention levels.

Developing effective trend estimators is the main method to solve the online portfolio selection problem. Although the existing portfolio strategies have demonstrated good performance through the development of various trend estimators, it is still challenging to determine in advance which estimator will yield the maximum final cumulative wealth in online portfolio selection tasks. This paper studies an online ensemble approach for online portfolio selection by leveraging the strengths of multiple trend estimators. Specifically, a return-based loss function and a cross-entropy-based loss function are first designed to evaluate the adaptiveness of different trend estimators in a financial environment. On this basis, a passive aggressive ensemble model is proposed to weigh these trend estimators within a unit simplex according to their adaptiveness. Extensive experiments are conducted on benchmark datasets from various real-world stock markets to evaluate their performance. The results show that the proposed strategy achieves state-of-the-art performance, including efficiency and cumulative return.

The conventional production technique employed for low-permeability tight reservoirs exhibits limited productivity. To solve the problem, an acetate-type supercritical carbon dioxide (scCO2) thickener, PVE, which contains a large number of microporous structures, was prepared using the atom transfer radical polymerization (ATRP) method. The product exhibited an ability to decrease the minimum miscibility pressure of scCO2 during a solubility test and demonstrated a favorable extraction efficiency in a low-permeability tight core displacement test. At 15 MPa and 70 °C, PVE-scCO2 at a concentration of 0.2% exhibits effective oil recovery rates of 5.61% for the 0.25 mD core and 2.65% for the 5 mD core. The result demonstrates that the incorporation of the thickener PVE can effectively mitigate gas channeling, further improve oil displacement efficiency, and inflict minimal damage to crude oil. The mechanism of thickening was analyzed through molecular simulation. The calculated trend of thickening exhibited excellent agreement with the experimental measurement rule. The simulation results demonstrate that the contact area between the polymer and CO2 increases in direct proportion to both the number of thickener molecules and the viscosity of the system. The study presents an effective strategy for mitigating gas channeling during scCO2 flooding and has a wide application prospect.

During the period that COVID-19 pandemic outbreak, Chinese universities have adopted a new teaching method combining online and offline and banned students from entering and leaving campus at will in line with the epidemic prevention policy. As a result, college students’ learning and life styles have been greatly changed. In order to explore how the epidemic and specific prevention policies have influenced the psychology and behavior of Chinese college students, this study used three questionnaires of college students’ subjective well-being, interpersonal relationship and love forgiveness to collect the data after the epidemic and compared with the data of college students before the epidemic. The result showed that before and after the epidemic, college students had obvious changes in their level of interpersonal relationship, subjective well-being and love forgiveness. Relationships among the three variables had changed. Meanwhile, the demographic variables of college students had certain changes in the three questionnaires. College students with and without romantic experience also had significant differences in the three questionnaires. It can be seen that the epidemic and specific prevention policies have a certain impact on the physical and mental health of college students, and there is also a gap in the forgiveness level of college students with and without romantic experience. These findings remind relevant departments that it should give greater consideration to the physical and mental health of college students, provide some references for dealing with new outbreaks and formulating the epidemic prevention policies subsequently, and suggest psychological counselors to change the way of dealing with the intimate relationship of college students.

With the increasing demand of mechanical stiffness performance and electromagnetic performance of maglev planar motor, especially the moving-magnet motor with Halbach array, an integrated optimization with 3D structural optimization and magnet parameter optimization is proposed and executed in this paper. The macroscopic electromagnetic performances consisting of thrust-mass ratio and power dissipation are taken as the optimization objective, which improves the performance more directly and comprehensively than traditional optimization methods. A streamlined dual-loop optimization framework is constructed and proved to be able to reduce the computational consumption by tens of times compared to the initial conventional framework, authentically guaranteeing a smooth integrated optimization. At the outer loop of the optimization framework, this paper proposes an oriented strategy for the individuals of Genetic Algorithm (GA) to quickly meet the strict constraints. The integrated optimization method solves the parameter coupling problem between electromagnet and stiffness. Compared to existing optimized structure, the resulting structure improves the thrust-mass ratio by 7.7%, power dissipation by 12.8% and natural frequency by 16.6%, respectively. Mechatronic experimental results in maglev planar motor systems show that the proposed integrated optimization can significantly improve the control bandwidth and reduce the current consumption, laying the foundation for better performance in practical applications.

Objective: We aimed to identify preoperative and intraoperative factors associated with serious postoperative outcomes, which may help patients and clinicians make better-informed decisions. Methods: We conducted a retrospective study including all patients aged ≥90 years who underwent surgery between January 1, 2011, and January 1, 2021, at Chongqing University Central Hospital. We assessed 30 pre- and intraoperative demographic and clinical variables. Logistic regression was used to identify the independent risk factors for serious postoperative outcomes in patients aged ≥90 years. Results: A total of 428 patients were included in our analysis. The mean age was 92.6 years (SD ± 2.6). There were 240 (56.1%) females and 188 (43.9%) males. The most common comorbidities were hypertension (44.9%) and arrhythmias (34.8%). The 30-day hospital mortality was 5.6%, and severe morbidity was 33.2%. Based on the multivariate logistic regression classification analysis of the American Society of Anesthesiologists (ASA)≥ Ⅳ [odds ratio (OR), 5.39, 95% confidence interval (CI), 2.06–14.16, P = .001], emergency surgery (OR, 5.02, 95% CI, 2.85–15.98, P = .001) and chronic heart failure (OR, 6.11, 95% CI, 1.93–13.06, P = .001) were identified as independent risk factors for 30-day hospital mortality, and ASA≥ Ⅳ (OR, 4.56, 95%CI, 2.56–8.15, P

This study focuses on how the use of digital portfolios in teacher education can support teacher candidates to shift their understanding of assessment as they form their assessment identity. The study was in the context of changing curriculum and assessment practices promoted in British Columbia. We draw on data from a cohort of teacher candidates in the first term of a 16-month post-degree teacher education program, where they created a digital portfolio across multiple courses as part of their final assessment to be used in an exit interview with instructors and teaching professionals from the field. Narratives of teacher candidates’ experiences were collected to shed light on their changing understanding of assessment for learning practices and their emerging teacher identity as assessors promoted by the digital portfolio process. Significance of using digital portfolios to support their process of becoming teachers is focused in the conclusion of the paper. Cette étude se concentre sur la manière dont l’utilisation de portfolios numériques dans la formation des enseignants et des enseignantes peut soutenir les candidats et les candidates à l’enseignement pour changer leur compréhension de l’évaluation alors qu’ils forment leur identité d’évaluation. L’étude s’est déroulée dans le contexte d’un programme d’études et de pratiques d’évaluation en changement favorisé en Colombie-Britannique. Nous nous appuyons sur les données d’une cohorte de candidats et de candidates à l’enseignement récoltées au cours du premier trimestre d’un programme de formation des enseignants post-diplôme de 16 mois, au cours duquel ils ont créé un portfolio numérique couvrant plusieurs cours dans le cadre de leur évaluation finale pour être utilisé en tant qu’entrevue de fin de programme avec des instructeurs et instructrices et des professionnels et professionnelles de la profession. Les narrations des expériences des candidats et des candidates à l’enseignement ont été rassemblées pour éclairer leur compréhension en changement de l’évaluation des pratiques d’apprentissage et leur identité naissante en tant que professeurs et professeures devenus évaluateurs et évaluatrices promus par le processus du portfolio numérique. Dans la conclusion de l’article, l’importance de l’emploi de portfolios numériques pour soutenir le processus qui consiste à devenir enseignant et enseignante est soulignée.

Falls and fall-related injuries are significant public health problems in older adults. While balance-controlling strategies have been extensively researched, there is still a lack of understanding regarding how fast the lower-limb muscles contract and coordinate in response to a sudden loss of standing balance. Therefore, this pilot study aims to investigate the speed and timing patterns of multiple joint/muscles’ activities among the different challenges in standing balance. Twelve healthy young subjects were recruited, and they received unexpected translational balance perturbations with randomized intensities and directions. Electromyographical (EMG) and mechanomyographical (MMG) signals of eight dominant-leg’s muscles, dominant-leg’s three-dimensional (3D) hip/knee/ankle joint angles, and 3D postural sways were concurrently collected. Two-way ANOVAs were used to examine the difference in timing and speed of the collected signals among muscles/joint motions and among perturbation intensities. This study has found that (1) agonist muscles resisting the induced postural sway tended to activate more rapidly than the antagonist muscles, and ankle muscles contributed the most with the fastest rate of response; (2) voluntary corrective lower-limb joint motions and postural sways could occur as early as the perturbation-induced passive ones; (3) muscles reacted more rapidly under a larger perturbation intensity, while the joint motions or postural sways did not. These findings expand the current knowledge on standing-balance-controlling mechanisms and may potentially provide more insights for developing future fall-prevention strategies in daily life.

Abstract Background In plants, histone modification (HM) genes participate in various developmental and defense processes. Gramineae plants (e.g., Triticum aestivum, Hordeum vulgare, Sorghum bicolor, Setaria italica, Setaria viridis, and Zea mays) are important crop species worldwide. However, little information on HM genes is in Gramineae species. Results Here, we identified 245 TaHMs, 72 HvHMs, 84 SbHMs, 93 SvHMs, 90 SiHMs, and 90 ZmHMs in the above six Gramineae species, respectively. Detailed information on their chromosome locations, conserved domains, phylogenetic trees, synteny, promoter elements, and gene structures were determined. Among the HMs, most motifs were conserved, but several unique motifs were also identified. Our results also suggested that gene and genome duplications potentially impacted the evolution and expansion of HMs in wheat. The number of orthologous gene pairs between rice (Oryza sativa) and each Gramineae species was much greater than that between Arabidopsis and each Gramineae species, indicating that the dicotyledons shared common ancestors. Moreover, all identified HM gene pairs likely underwent purifying selection based on to their non-synonymous (Ka)/synonymous (Ks) nucleotide substitutions. Using published transcriptome data, changes in TaHM gene expression in developing wheat grains treated with brassinosteroid, brassinazole, or activated charcoal were investigated. In addition, the transcription models of ZmHMs in developing maize seeds and after gibberellin treatment were also identified. We also examined plant stress responses and found that heat, drought, salt, insect feeding, nitrogen, and cadmium stress influenced many TaHMs, and drought altered the expression of several ZmHMs. Thus, these findings indicate their important functions in plant growth and stress adaptations. Conclusions Based on a comprehensive analysis of Gramineae HMs, we found that TaHMs play potential roles in grain development, brassinosteroid- and brassinazole-mediated root growth, activated charcoal-mediated root and leaf growth, and biotic and abiotic adaptations. Furthermore, ZmHMs likely participate in seed development, gibberellin-mediated leaf growth, and drought adaptation.

BackgroundCellular senescence plays an irreplaceable role in tumorigenesis, progression, and tumor microenvironment (TME) remodeling. However, to date, there is limited research delineating the landscape of cellular senescence in hepatocellular carcinoma (HCC), and an improved understanding on the interaction of tumor-associated cellular senescence with HCC prognosis, TME, and response to immunotherapy is warrant.MethodsTumorigenic and immune infiltration-associated senescence genes were determined by weighted gene co-expression network analysis (WGCNA) and the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm, and subsequently, a prognostic scoring model (named TIS) was constructed using multiple survival analysis algorithms to classify the senescence-related subtypes of HCC. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were conducted to identify the distinct hallmark pathways between high- and low-risk subtypes. Additionally, we carried out correlation analyses for TIS and clinical traits, senescence-associated secretory phenotype (SASP), immune infiltration and evasion, immune checkpoint factors, drug response, and immunotherapeutic efficacy. External experimental validation was conducted to delineate the association of CPEP3 (a TIS gene) with HCC phenotypes through assays of proliferation, colony formation, and invasion.ResultsA five-gene TIS, composed of NET1, ATP6V0B, MMP1, GTDC1, and CPEB3, was constructed and validated using TCGA and ICGC datasets, respectively, and showed a highly robust and plausible signature for overall survival (OS) prediction of HCC in both training and validation cohorts. Patients in the TIS-high group were accompanied by worse OS, activation of carcinogenetic pathways, infiltration of immunosuppressive cells, exclusion of effector killing cells, overexpression of immunomodulatory genes and SASP, and unsatisfied response to immunotherapy. In response to anticancer drugs, patients in the TIS-high group exhibited enhanced susceptibility to several conventional chemotherapeutic agents (5-fluorouracil, docetaxel, doxorubicin, gemcitabine, and etoposide), as well as several inhibitors of pathways involved in cellular senescence (cell-cycle inhibitors, bromodomain and extraterminal domain family (BET) inhibitors, PI3K-AKT pathway inhibitors, and multikinase inhibitors). Additionally, four putative drugs (palbociclib, JAK3 inhibitor VI, floxuridine, and lestaurtinib) were identified as potential compounds for patients in the TIS-high group. Notably, in vitro functional validation showed that CPEB3 knockdown boosted the phenotypes of proliferation, clonogenicity, and invasion in HCC cells, whereas CPEB3 overexpression attenuated these phenotypes.ConclusionsOur study provides comprehensive clues demonstrating the role of novel TIS in predicting HCC prognosis, immunotherapeutic response, and candidate drugs. This work highlights the significance of tumorigenesis- and immune infiltration-related cellular senescence in cancer therapy.

Fluorescent lamp manufacturing workers have been extensively exposed to mercury (Hg). Our aim was to assess their health risks using several approved occupational health risk assessment methods, and to find out which method was more suitable for identification of occupational health risks. Work locations, and air and urine samples were collected from 530 exposed workers in Zhejiang, China. Based on the calculated exposure doses, health risks and risk ratios (RRs) as health risk indices, were evaluated using: Environmental Protection Agency (EPA), Australian, Romanian, Singaporean, International Council on Mining and Metals (ICMM), and Control of Substances Hazardous to Health (COSHH) methods. Among the workers, 86.0% had higher Hg levels than the Chinese occupational exposure limits of 0.02 mg/m3, and 16.7% urine samples were higher than the biological exposure limits of 35.0 μg/g·creatinine. Among workers at the injection, etc. locations, their average RRs, evaluated by the EPA, COSHH and Singaporean methods were 0.97, 0.76, and 0.60, respectively, and were significantly higher than the ICMM (0.39), Australian (0.30) and Romanian (0.29) methods. The RRs from the Singaporean method showed significant correlations with the urinary Hg levels (P < 0.01). In conclusion, the Singaporean method was more appropriate than the others for health risk evaluation because the excessive risks were significantly associated with urinary Hg levels among the workers.

BackgroundNADH: ubiquinone oxidoreductase subunit C1(NDUFC1) encodes a subunit of the Complex I, which may support the structural stability of Complex I and assist in its biogenesis. The expression and functional roles of NDUFC1 in hepatocellular carcinoma (HCC) remain unknown.ResultWe knocked down the expression of NDUFC1 in HCC cell lines to explore the effects of NDUFC1 downregulation on HCC in vitro. MTT assay determined that downregulation of NDUFC1 significantly inhibited cell proliferation. Flow cytometry with (propidium iodide) PI staining indicated silencing of NDUFC1 arrested cell cycle of BEL-7404 cells at G2 phase and SK-HEP-1 cells at S/G2 phase. Annexin V-PI double staining and flow cytometric analysis showed that the downregulation of NDUFC1 significantly increased the population of apoptotic cells. Wound-healing assay and transwell assay indicated that the downregulation of NDUFC1 suppressed the migration and invasion of HCC cells. According to the detection of complex1 activity, we found that the activity of NDUFC1 silenced group decreased, whereas the content of ROS increased. Furthermore, combined with bioinformatics analysis of senescence-related genes, we found that the silence of NDUFC1 in HCC could induce senescence and inhibit autophagy. In addition, NDUFC1 could correlate positively with cancer-related pathways, among which the p53 pathways and the PI3K/Akt/mTOR pathways. Finally, NDUFC1 is high expression in HCC specimens. High NDUFC1 expression was associated with poor prognosis and was an independent risk factor for reduced overall survival (OS).ConclusionsOur study indicated, for the first time, that NDUFC1 is an independent risk factor for the poor prognosis of HCC patients. NDUFC1 may promote tumor progression by inhibiting mitochondrial Complex I and up-regulating ROS through multiple cancer-related and senescence-related pathways of HCC, including p53 pathways and PI3K/Akt/mTOR pathways. We suppose that NDUFC1 might be a potential target for the mitochondrial metabolism therapy of HCC.

When image quality is evaluated, the human visual system (HVS) infers the details in the image through its internal generative mechanism. In this process, the HVS integrates both local and global information about the image, utilizes contextual information to restore the original image information, and compares it with the distorted image information for image quality evaluation. Inspired by this mechanism, a no-reference image quality assessment method is proposed based on a multitask image restoration network. The multitask image restoration network generates a pseudo-reference image as the main task and produces a structural similarity index measure map as an auxiliary task. By mutually promoting the two tasks, a higher-quality pseudo-reference image is generated. In addition, when predicting the image quality score, both the quality restoration features and the difference features between the distorted and reference images are used, thereby fully utilizing the information from the pseudo-reference image. In order to facilitate the model’s ability to extract both global and local features, we introduce a multi-scale feature fusion module. Experimental results demonstrate that the proposed method achieves excellent performance on both synthetically and authentically distorted databases.

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of the human visual system (HVS) can be combined. In this paper, inspired by the ventral pathway and the dorsal pathway of the HVS, a dual-pathway convolutional neural network is proposed for BIQA tasks. The proposed method consists of two pathways: the “what” pathway, which mimics the ventral pathway of the HVS to extract the content features of distorted images, and the “where” pathway, which mimics the dorsal pathway of the HVS to extract the global shape features of distorted images. Then, the features from the two pathways are fused and mapped to an image quality score. Additionally, gradient images weighted by contrast sensitivity are used as the input to the “where” pathway, allowing it to extract global shape features that are more sensitive to human perception. Moreover, a dual-pathway multi-scale feature fusion module is designed to fuse the multi-scale features of the two pathways, enabling the model to capture both global features and local details, thus improving the overall performance of the model. Experiments conducted on six databases show that the proposed method achieves state-of-the-art performance.

Air quality monitoring in polluted environments is of great significance to human health. Traditional methods use various pieces of meteorological equipment, which have limited applications in complex terrains and high costs. In this paper, a novel idea is put forward to solve the problem of air pollution monitoring in urban areas. We investigate whether air quality can be assessed visually by examining the haziness of photos from a far distance. Specifically, the correlation between the air quality indexes, such as the AQI, PM2.5, and PM10, of real outdoor scenarios and the haziness level evaluation scores of the monitoring images is calculated. The results show that the objective indicators can indeed reflect the level of air pollution, and the degree of correlation is invariant to the image size. To apply this new observation to a practical system, a novel method called fastDBCP (fast dark and bright channel prior) is developed. Based on a down-sampling strategy, a ratio is calculated between the dark and bright channel prior information in scaled images and adopted as the visual index of air pollution. Our experimental results show that the proposed metric not only demonstrates advantages in terms of its correlation degree and computational speed, but also shows a high level of classification accuracy compared to that of competing metrics.

Photovoltaic (PV) panels have been widely used as one of the solutions for green energy sources. Performance monitoring, fault diagnosis, and Control of Operation at Maximum Power Point (MPP) of PV panels became one of the popular research topics in the past. Model parameters could reflect the health conditions of a PV panel, and model parameter estimation can be applied to PV panel fault diagnosis. In this paper, we will propose a new algorithm for PV panel model parameters estimation by using a Neural Network (ANN) with a Numerical Current Prediction (NCP) layer. Output voltage and current signals (VI) after load perturbation are observed. An ANN is trained to estimate the PV panel model parameters, which is then fined tuned by the NCP to improve the accuracy to about 6%. During the testing stage, VI signals are input into the proposed ANN-NCP system. PV panel model parameters can then be estimated by the proposed algorithms, and the estimated model parameters can be then used for fault detection, health monitoring, and tracking operating points for MPP conditions.

With the rapid development of artificial intelligence technology, the exploration and application in the field of intelligent education has become a research hotspot of increasing concern. In the actual classroom scenarios, students’ classroom behavior is an important factor that directly affects their learning performance. Specifically, students with poor self-management abilities, particularly specific developmental disorders, may face educational and academic difficulties owing to physical or psychological factors. Therefore, the intelligent perception and identification of school-aged children’s classroom behaviors are extremely valuable and significant. The traditional method for identifying students’ classroom behavior relies on statistical surveys conducted by teachers, which incurs problems such as being time-consuming, labor-intensive, privacy-violating, and an inaccurate manual intervention. To address the above-mentioned issues, we constructed a motion sensor-based intelligent system to realize the perception and identification of classroom behavior in the current study. For the acquired sensor signal, we proposed a Voting-Based Dynamic Time Warping algorithm (VB-DTW) in which a voting mechanism is used to compare the similarities between adjacent clips and extract valid action segments. Subsequent experiments have verified that effective signal segments can help improve the accuracy of behavior identification. Furthermore, upon combining with the classroom motion data acquisition system, through the powerful feature extraction ability of the deep learning algorithms, the effectiveness and feasibility are verified from the perspectives of the dimensional signal characteristics and time series separately so as to realize the accurate, non-invasive and intelligent children’s behavior detection. To verify the feasibility of the proposed method, a self-constructed dataset (SCB-13) was collected. Thirteen participants were invited to perform 14 common class behaviors, wearing motion sensors whose data were recorded by a program. In SCB-13, the proposed method achieved 100% identification accuracy. Based on the proposed algorithms, it is possible to provide immediate feedback on students’ classroom performance and help them improve their learning performance while providing an essential reference basis and data support for constructing an intelligent digital education platform.

Myopia has become one of the most critical health problems in the world with the increasing time spent indoors and increasing close work. Pathological myopia may have multiple complications, such as myopic macular degeneration, retinal detachment, cataracts, open-angle glaucoma, and severe cases that can cause blindness. Mounting evidence suggests that the cause of myopia can be attributed to the complex interaction of environmental exposure and genetic susceptibility. An increasing number of researchers have focused on the genetic pathogenesis of myopia in recent years. Scleral remodeling and excessive axial elongating induced retina thinning and even retinal detachment are myopia's most important pathological manifestations. The related signaling pathways are indispensable in myopia occurrence and development, such as dopamine, nitric oxide, TGF-β, HIF-1α, etc. We review the current major and recent progress of biomedicine on myopia-related signaling pathways and mechanisms.

Dental mesenchymal stem cells (DMSCs) are crucial in tooth development and periodontal health, and their multipotential differentiation and self-renewal ability play a critical role in tissue engineering and regenerative medicine. Methylation modifications could promote the appropriate biological behavior by postsynthetic modification of DNA or protein and make the organism adapt to developmental and environmental prompts by regulating gene expression without changing the DNA sequence. Methylation modifications involved in DMSC fate include DNA methylation, RNA methylation, and histone modifications, which have been proven to exert a significant effect on the regulation of the fate of DMSCs, such as proliferation, self-renewal, and differentiation potential. Understanding the regulation of methylation modifications on the behavior and the immunoinflammatory responses involved in DMSCs contributes to further study of the mechanism of methylation on tissue regeneration and inflammation. In this review, we briefly summarize the key functions of histone methylation, RNA methylation, and DNA methylation in the differentiation potential and self-renewal of DMSCs as well as the opportunities and challenges for their application in tissue regeneration and disease therapy.

Haze level evaluation is highly desired in outdoor scene monitoring applications. However, there are relatively few approaches available in this area. In this paper, a novel haze level evaluation strategy for real-world outdoor scenes is presented. The idea is inspired by the utilization of dark and bright channel prior (DBCP) for haze removal. The change between hazy and haze-free scenes in bright channels could serve as a haze level indicator, and we have named it DBCP-I. The variation of contrast between dark and bright channels in a single hazy image also contains useful information to reflect haze level. By searching for a segmentation threshold, a metric called DBCP-II is proposed. Combining the strengths of the above two indicators, a hybrid metric named DBCP-III is constructed to achieve better performance. The experiment results on public, real-world benchmark datasets show the advantages of the proposed methods in terms of assessment accuracy with subjective human ratings. The study is first-of-its-kind with preliminary exploration in the field of haze level evaluation for real outdoor scenes, and it has a great potential to promote research in autonomous driving and automatic air quality monitoring. The open-source codes of the proposed algorithms are free to download.

In this study, we use the critical slowing down (CSD) theory to identify the precursory anomalies of groundwater radon based on the 1000-day continuous data from 8 monitoring stations in Yunnan Province, China during the seismically active period of 1993–1996. The low-frequency and high-frequency information were extracted from raw groundwater radon data to calculate their one-step lag autocorrelation (AR-1) and variance, respectively, in order to identify the precursory anomalies. The results show that the anomaly characteristics can be divided into three categories: sudden jump anomalies, persistent anomalies, and fluctuation anomalies. The highest average seismic recognition rate is 72.78%, based on the high-frequency information’s autocorrelation, while the lowest is 45.08%, based on the low-frequency information’s variance. The crustal activity and the change in hydrogeological conditions are possibly the main factors influencing groundwater radon anomalies in the selected period in the study area. There is a positive correlation between the anomaly occurrence time and epicentral distance when epicentral distance is less than 300 km, which may be related to the seismogenic modes and hydrogeological conditions. This study provides a reference for identifying groundwater radon anomalies before earthquakes by mathematical methods.