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Purpose: Although doctoral education has experienced substantial development in recent decades, it remains an elite, hence fragile, dimension of university policy and practice. This study aims to articulate perspectives to guide the next phase of strengthening and growth. Design/methodology/approach: Working from theoretical and empirical research conducted in China, including scholarship on workforce ecosystems, education design and the student experience, this study contributes a framework with qualitative insights which clarify the goals and experiences of doctoral education in ways that will render it more relevant, effective and contributing. Findings: The paper identifies areas for doctoral reform to ensure career readiness, including three distinctive outcomes and four indispensable experiences. Originality/value: This study advances a doctoral design framework which can render transparent the substance of programs and prompt program coordinators to develop and ensure career relevance.

Despite the importance of undergraduate research for student learning and development, not enough work has been done to clarify its effects in different disciplinary contexts. Using data from the China College Student Survey, this research adopts Becher and Trowler's theory of discipline classification to understand the relationship between undergraduate research and students' learning outcomes in different disciplines. It indicates that first, contributing to journals/conferences correlates with students' self-reported learning outcomes in Physics, History, and Engineering, but these relationships can be explained by process-centered activities, except in Physics. Second, early-year undergraduates' learning outcomes are relatively weakly related to conducting research with faculty in pure disciplines. By contrast, such relationships are distinct in applied disciplines. Third, in soft disciplines, participating in competitions significantly correlates with more types of students' learning outcomes than conducting research with faculty, while in hard disciplines, they both play quite important roles. It makes recommendations for future research and practice, which enrich insight into how universities can best engage undergraduates in research.

Acute respiratory distress syndrome (ARDS) is a severe critical respiratory disease characterized by refractory hypoxemia, which is caused by intrapulmonary and extrapulmonary factors. It has a rapid onset, and high morbidity and mortality. With the global prevalence and mutation of respiratory viruses, the diagnosis and treatment of ARDS have become more complicated, requiring exploration into the molecular mechanisms and effective therapeutic methods of the occurrence and development of ARDS in clinical practice. Researchers have found that the pathogenesis of ARDS involves the interaction of multiple factors, including imbalances in inflammatory responses and redox reactions, dysregulation of endothelial cells, disruption of alveolar-capillary barrier and abnormalities in coagulation function. Although advancements in molecular biology techniques such as genomics and proteomics have provided new insights into the pathogenesis of ARDS, there is still a lack of early diagnostic biomarker and effective drugs targeted for ARDS. At present, more comprehensive and in-depth basic and clinical research is still needed. Increasing evidence suggests that transient receptor potential vanilloid-1 (TRPV1), also known as the capsaicin receptor, plays a crucial role in respiratory system diseases. TRPV1 is widely distributed in the upper respiratory tract, airway smooth muscle, alveoli and pulmonary blood vessels, participating in mediating airway dilation and constriction, cough reflex, and release of inflammatory mediators related to inflammation and pain, as well as sensing and transmitting various biological signals related to temperature, chemical substances and mechanical stress stimuli in the respiratory system. The widespread distribution and diverse physiological functions of TRPV1 make it a research hotspot in the occurrence and development of respiratory system diseases such as pneumonia, pulmonary edema, cough, asthma and acute lung injury. This article reviews the correlation and molecular mechanisms between ARDS caused by sepsis, traumatic brain injury and respiratory viruses with TRPV1, aiming to summarize the positive effects of regulating TRPV1 expression on the pathogenesis of ARDS and provide reference for strengthening early diagnosis and effective intervention measures for ARDS.

Tobacco (Nicotiana tabacum L.) bacterial wilt, caused by Ralstonia solanacearum, is indeed a highly destructive plant disease, leading to substantial damage in tobacco production. While biological control is considered an effective measure for managing bacterial wilt, related research in this area has been relatively limited compared to other control methods. In order to discover new potential antagonistic bacteria with high biocontrol efficacy against tobacco bacterial wilt, we conducted an analysis of the microbial composition differences between disease-suppressive and disease-conducive soils using Illumina sequencing. As a result, we successfully isolated six strains from the disease-suppressive soil that exhibited antibacterial activity against Ralstonia solanacearum. Among these strains, B4-7 showed the strongest antibacterial activity, even at acidic conditions with a pH of 4.0. Based on genome analysis using Average Nucleotide Identity (ANI), B4-7 was identified as Bacillus velezensis. In greenhouse and field trials, strain B4-7 significantly reduced the disease index of tobacco bacterial wilt, with control efficiencies reaching 74.03% and 46.88% respectively. Additionally, B4-7 exhibited plant-promoting abilities that led to a 35.27% increase in tobacco production in field conditions. Quantitative real-time (qPCR) analysis demonstrated that strain B4-7 effectively reduced the abundance of R. solanacearum in the rhizosphere. Genome sequencing and Liquid Chromatography-Mass Spectrometry (LC-MS) analysis revealed that strain B4-7 potentially produces various lipopeptide metabolites, such as microlactin, bacillaene, difficidin, bacilysin, and surfactin. Furthermore, B4-7 influenced the structure of the rhizosphere soil microbial community, increasing bacterial abundance and fungal diversity, while also promoting the growth of different beneficial microorganisms. In addition, B4-7 enhanced tobacco’s resistance to R. solanacearum by increasing the activities of defense enzymes, including superoxide dismutase (SOD), phenylalanine ammonia-lyase (PAL), peroxidase (POD), catalase (CAT), and polyphenol oxidase (PPO). Collectively, these findings suggest that B. velezensis B4-7 holds significant biocontrol potential and can be considered a promising candidate strain for eco-friendly management of tobacco bacterial wilt.

The relationship between distinct dietary selenium intake and type 2 diabetes (T2D) is still a topic of uncertainty. This study examined the relationship between dietary selenium intake and T2D risk among middle-aged and older Chinese adults. Dietary selenium intake was assessed through three 24 h recalls, using data from the China Health and Nutrition Survey. To investigate the relationship and the potential dose–response pattern between selenium intake and the likelihood of developing T2D, we employed both the restricted cubic spline analysis and the Cox proportional hazards model as our analytical tools. A cohort of 5970 participants aged ≥ 50 years was followed for an average of 5.44 years. The results revealed a V-shaped correlation between selenium intake and T2D risk, with the lowest risk observed at approximately 45 µg/day. Below this level, the risk decreased with an increasing selenium intake, while the risk increased between 45 and 100 µg/day. No significant association was found beyond 100 µg/day. These findings suggest that both low and high selenium consumption may increase T2D risk, highlighting the importance of maintaining a balanced selenium intake for T2D prevention.

In the era of educational intelligence, the development of student-oriented personalized learning has become a new trend in educational research. Based on fuzzy cognitive theory, this paper proposes a cognitive diagnosis model for English vocabulary and a personalized test question recommendation model for English vocabulary based on cognitive diagnosis. The cognitive diagnostic model combines the four-parameter logistics model to accurately analyze the learner’s cognitive state, applies the fuzzy CDF assumption to calculate the learner’s knowledgeability level, and employs the fuzzy logic method for cognitive modeling. Assess students’ mastery levels on subjective and objective questions, improve existing recommendation methods that do not adequately consider students’ cognitive levels, and develop a personalized recommendation model for PMF-FCD. We utilized a high school in Yan’an City, Shaanxi Province, China, as a learning location for English vocabulary training. The student’s overall performance on the English vocabulary posttest improved by 14.22 compared with the pre-test, and the mean value of learning attitudes improved by 1.17 compared with the pre-test, with improvements in learning interests, perceptions, and habits. All the strategy dimensions of learning strategies, except the memory strategy dimension, showed significant positive effects after the experiment (p

Corydalis yanhusuo W. T. Wang, also known as yanhusuo, yuanhu, yanhu and xuanhu, is one of the herb components of many Chinese Traditional Medicine prescriptions such as Jin Ling Zi San and Yuanhu-Zhitong priscription. C. yanhusuo was traditionally used to relieve pain and motivate blood and Qi circulation. Now there has been growing interest in pharmacological effects of alkaloids, the main bioactive components of C. yanhusuo. Eighty-four alkaloids isolated from C. yanhusuo are its important bioactive components and can be characterized into protoberberine alkaloids, aporphine alkaloids, opiate alkaloids and others and proper extraction or co-administration methods modulate their contents and efficacy. Alkaloids from C. yanhusuo have various pharmacological effects on the nervous system, cardiovascular system, cancer and others through multiple molecular mechanisms such as modulating neurotransmitters, ion channels, gut microbiota, HPA axis and signaling pathways and are potential treatments for many diseases. Plenty of novel drug delivery methods such as autologous red blood cells, self-microemulsifying drug delivery systems, nanoparticles and others have also been investigated to better exert the effects of alkaloids from C. yanhusuo. This review summarized the alkaloid components of C. yanhusuo, their pharmacological effects and mechanisms, and methods of drug delivery to lay a foundation for future investigations.

The pulses in X-ray-burst (XRB) light curves from soft gamma-ray repeaters (SGRs) are generally thought to arise from magnetic crustal fractures or magnetic reconnection, reflecting the evolution of the energy release process in magnetars. In this study, we conduct a comprehensive timing analysis of 27 XRBs from SGR J0501+4156 detected by the Gamma-ray Burst Monitor on board Fermi. Utilizing a improved pulse-finding algorithm, we identify a total of 95 pulses and fit them using multiple FRED functions to obtain pulse-shape parameters based on the Markov Chain Monte Carlo method. We calculate the minimum variability timescales (MVTs) of the XRBs based on the shortest pulse; the distribution of MVTs follows a log-Gaussian function with a mean of ${7.22}_{-2.11}^{+2.93}$ ms (1 σ ). The distributions of rise time, decay time, waiting time, width, skewness, and peakedness all follow the log-Gaussian function, and multiple power-law dependencies are observed between them; for example, a power-law positive correlation between decay time and rise time with 4.7 σ , and a power-law negative correlation between pulse width and peakedness with 6.8 σ . Besides, there is a positive correlation with 3.7 σ between the number of pulses and burst duration. Our findings favor a magnetospheric origin, and some similarities with gamma-ray bursts imply that they have similar radiation mechanisms, e.g., magnetic reconnection processes.

The overall temporal and spectral characteristics (e.g., duration, fluence, peak flux, peak count rate, and total counts) of X-ray bursts (XRBs) originating from magnetars have been extensively studied to confirm their self-organized criticality (SOC) behaviors. However, for the pulses in XRBs, which are an important part of unraveling radiation processes such as magnetic reconnection and crustal rupture, their variable statistical characteristics are still unclear. In this work, we investigate the distributions of fluctuations in duration, waiting time, peak count rate, and total counts of pulses within bursts from two active and prolific magnetars, SGR J1935+2154 and SGR J1550-5418, observed by Fermi’s Gamma-ray Burst Monitor, Insight-HXMT, and GECAM. We report that the waiting time for pulses follows SOC, whereas previous studies indicated for bursts do not, possibly due to incomplete observations. Besides, the duration, peak count rate, and total counts for pulses are also SOC behaviors. The α -values for the duration of pulses for both magnetars are ∼2, and the inferred Euclidean dimension S is 3. Our findings provide evidence for the SOC of each radiation process during a burst, for example, multiple pulses produced by multiple magnetic reconnections triggered by a single starquake. Finally, the similar statistical characteristics for pulses from both magnetars lend support to their shared radiation processes.

The milestone discovery of GW170817-GRB 170817A-AT 2017gfo has shown that gravitational waves (GWs) could be produced during the merger of a neutron star–neutron star/black hole and that in electromagnetic (EM) waves, a gamma-ray burst (GRB) and a kilonova (KN) are generated in sequence after the merger. Observationally, however, EM properties before the merger phase are still unclear. Here we report a peculiar precursor in a KN-associated long-duration GRB 211211A, providing evidence of the EM before the merger. This precursor lasts ∼0.2 s, and the waiting time between the precursor and the main burst is ∼1 s, comparable to that between GW170817 and GRB 170817A. The spectrum of the precursor could be well fit with a nonthermal cutoff power-law model instead of a blackbody. In particular, a ∼22 Hz quasiperiodic oscillation candidate (∼3 σ ) is detected in the precursor. These temporal and spectral properties indicate that this precursor is probably produced by a catastrophic flare accompanied with magnetoelastic or crustal oscillations of a magnetar in a binary compact merger. The strong magnetic field of the magnetar can also account for the prolonged duration of GRB 211211A. However, it poses a challenge to reconcile the rather short lifetime of a magnetar with the rather long spiraling time of a binary neutron star system only by the GW radiation before the merger.

The major observation of the X-ray burst (XRB) in association with the fast radio burst (FRB) FRB 200428 originating from SGR J1935+2154 on 2020 April 28 substantiates magnetars as one of the origins of FRBs. However, it is still unclear why only a few XRBs in association with FRBs have been observed solely in this magnetar. In this study, we investigate the minimum variation timescales (MVTs) of XRBs from SGR J1550-5418, an active magnetar similar to SGR J1935+2154, and conduct a comprehensive comparison of their MVT properties. Our analysis reveals that the distribution of the MVT for SGR J1550-5418 follows a lognormal Gaussian function with the mean 6.4 ± 0.4 ms. Interestingly, we detect an evolution in the MVTs, i.e., the fitted mean of the MVT distribution in 2008 October is about 3 times larger than that in 2009, indicating potential variations in radiation regions possibly attributed to changes in magnetic field topology. Besides, we do not find a significant correlation between the MVT and either duration or energy. Finally, there is no significant difference between the MVT distributions across different energy ranges for SGR J1550-5418 and SGR J1935+2154, which supports a common physical origin.

BackgroundDiabetes is a major contributor to global burden of disease. The role of magnesium in the prevention of diabetes has aroused concern. However, the research results on the impact of dietary magnesium on the risk of diabetes are hitherto inconsistent. ObjectiveTo evaluate the association between dietary magnesium intake and the risk of diabetes through a systematic review. MethodsPubMed, Web of Science, China National Knowledge Infrastructure, Wanfang databases were searched for prospective studies that contained risk estimates for magnesium intake-associated diabetes and were published from January 1, 2000 to December 31, 2021. Two researchers independently screened the literature according to a set of pre-prepared inclusion and exclusion criteria, extracted the data according to an unified data extraction table, and evaluated the quality of included articles with Newcastle-Ottawa Scale (NOS). R 4.0.3 software and Stata SE16.0 software were used for meta-analysis and subgroup meta-analysis, and Higgins I2 statistics were used to test the heterogeneity of the included studies. The sources of heterogeneity were analyzed by univariate meta regression. ResultsA total of 14 articles involving 17 prospective cohort studies (1065267 participants and 40506 patients with diabetes) were included in the study. The NOS scores ranged from 8 to 9, with an average of 8.6, indicating that the included studies were classified as being high quality. The highest quintile of magnesium intake group reduced the risk of diabetes by 22% (RR=0.78, 95%CI: 0.73-0.82) compared with the lowest quintile group. This association was not substantially modified by geographic region, sex, or follow-up length. The highest quintile of dietary magnesium intake in the Americas and Asia were associated with 22% and 26% reductions in the risk of type 2 diabetes respectively compared with the lowest quintile group (the Americas, RR=0.78, 95%CI: 0.73-0.84; Asia, RR=0.74, 95%CI: 0.63-0.88); The highest quintile of dietary magnesium intake in female, male and without gender stratified were associated with 22%, 19% and 46% reductions in the risk of type 2 diabetes respectively compared with the lowest quintile group (Female RR=0.78, 95%CI: 0.73-0.84; Male RR=0.81, 95%CI: 0.74-0.89; Both RR=0.54, 95%CI: 0.42-0.68); Compared with the lowest quintile groups, the groups with the highest quintile of dietary magnesium intake with a follow-up time of less than 10 years and more than 10 years reduced the risk of type 2 diabetes by 26% and 20% respectively (≤10 years, RR=0.74, 95%CI: 0.65-0.83; ＞10 years, RR=0.80, 95%CI: 0.75-0.85). After adjusting for hypertension, the highest quintile of dietary magnesium intake group reduced the risk of type 2 diabetes by 20% compared with the lowest quintile group (RR=0.80, 95%CI: 0.74-0.85). The year of publication (P

Abstract Excessive proliferation and migration of airway smooth muscle cell (ASMC) contribute to asthma pathogenesis. Long noncoding RNAs (lncRNAs) are reported to take part in asthma pathogenesis. This study is targeted at deciphering the role of the lncRNA antisense noncoding RNA in the INK4 locus (ANRIL) in ASMC proliferation, migration and extracellular matrix (ECM) deposition. qRT‐PCR was performed to determine ANRIL, miR‐98‐5p, and cyclin D1 (CCND1) mRNA expression levels in transforming growth factor‐β1 (TGF‐β1)‐treated ASMCs. CCK‐8 and Transwell assays were employed to examine ASMC proliferation and migration, respectively. Dual‐luciferase reporter gene assay and RNA immunoprecipitation assay were carried out for analyzing the targeted relationship of miR‐98‐5p with ANRIL or CCND1 mRNA 3′‐UTR. The levels of CCND1 and ECM proteins (such as fibronectin, COL3A1, and COL1A2) in ASMCs were detected through Western blot. In this work, we found that ANRIL and CCND1 were up‐regulated in TGF‐β1‐treated ASMCs, whereas miR‐98‐5p was down‐regulated. ANRIL overexpression facilitated the proliferation, ECM deposition and migration of TGF‐β1‐induced ASMCs, while knocking down ANRIL had the opposite effect. Furthermore, ANRIL targeted miR‐98‐5p directly, and CCND1 was miR‐98‐5p's downstream target. ANRIL indirectly increased CCND1 expression in ASMCs via competitively binding to miR‐98‐5p. MiR‐98‐5p inhibition or CCND1 overexpression counteracted the inhibiting effect that ANRIL knockdown had on TGF‐β1‐stimulated ASMC proliferation, migration and ECM deposition. In conclusion, ANRIL indirectly up‐regulates CCND1 expression by targeting miR‐98‐5p to promote ASMC proliferation, migration and ECM deposition, thus facilitating the pathogenesis of asthma.

Abstract In China, tuberculosis (TB) is endemic and the Bacillus Callmette–Güerin (BCG) vaccine is administered to all the newborns, which may lead to BCG infection in patients with chronic granulomatous disease (CGD). Infection of BCG/TB in CGD patients can be fatal and pulmonary is the most affected organ. Our objective was to assess the imaging of pulmonary BCG/TB infection in CGD. We screened 169 CGD patients and identified the patients with pulmonary BCG/TB infection. BCG infection was diagnosis according to the vaccination history, local infection manifestation, acid-fast bacilli staining, specific polymerase chain reaction, and/or spoligotyping. PPD, T-SPOT and acid-fast bacilli staining were used for diagnosis of TB. Totally 58 patients were identified, including TB (n = 7), solely BCG (n = 18), BCG + bacterial (n = 20), and BCG + fungi (n = 13). The onset of BCG disease was much earlier than TB. For those patients only with BCG, lymphadenopathy was the first and most prevalent feature. The most found location was the left axilla, followed by the ipsilateral cervical areas and mediastinal or hilar area. On chest CT, ground-glass opacities, multiple nodules and pulmonary scarring were the most common findings. For TB patients, the pulmonary infections were more serious, including large masses, severe lymphadenopathy, and extensive pulmonary fibrosis. Pulmonary infection of BCG were more common than TB in CGD patients, but much less severe.

Abstract Precise customer requirements acquisition is the primary stage of product conceptual design, which plays a decisive role in product quality and innovation. However, existing customer requirements mining approaches pay attention to the offline or online customer comment feedback and there has been little quantitative analysis of customer requirements in the analogical reasoning environment. Latent and innovative customer requirements can be expressed by analogical inspiration distinctly. In response, this paper proposes a semantic analysis-driven customer requirements mining method for product conceptual design based on deep transfer learning and improved latent Dirichlet allocation (ILDA). Initially, an analogy-inspired verbal protocol analysis experiment is implemented to obtain detailed customer requirements descriptions of elevator. Then, full connection layers and a softmax layer are added to the output-end of Chinese bidirectional encoder representations from Transformers (BERT) pre-training language model. The above deep transfer model is utilized to realize the customer requirements classification among functional domain, behavioral domain and structural domain in the customer requirement descriptions of elevator by fine-tuning training. Moreover, the ILDA is adopted to mine the functional customer requirements that can represent customer intention maximally. Finally, an effective accuracy of customer requirements classification is acquired by using the BERT deep transfer model. Meanwhile, five kinds of customer requirements of elevator and corresponding keywords as well as their weight coefficients in the topic-word distribution are extracted. This work can provide a novel research perspective on customer requirements mining for product conceptual design through natural language processing.