Recent studies utilizing AI-driven speech-based Alzheimer’s disease (AD) detection have achieved remarkable success in detecting AD dementia through the analysis of audio and text data. However, detecting AD at an early stage of mild cognitive impairment (MCI), remains a challenging task, due to the lack of sufficient training data and imbalanced diagnostic labels. Motivated by recent advanced developments in Generative AI (GAI) and Large Language Models (LLMs), we propose an LLM-based data generation framework, leveraging prior knowledge encoded in LLMs to generate new data samples. Our novel LLM generation framework introduces two novel data generation strategies, namely, the cross-lingual and the counterfactual data generation, facilitating out-of-distribution learning over new data samples to reduce biases in MCI label prediction due to the systematic underrepresentation of MCI subjects in the AD speech dataset. The results have demonstrated that our proposed framework significantly improves MCI Detection Sensitivity and F1-score on average by a maximum of 38% and 31%, respectively. Furthermore, key speech markers in predicting MCI before and after LLM-based data generation have been identified to enhance our understanding of how the novel data generation approach contributes to the reduction of MCI label prediction biases, shedding new light on speech-based MCI detection under low data resource constraint. Our proposed methodology offers a generalized data generation framework for improving downstream prediction tasks in cases where limited and/or imbalanced data have presented significant challenges to AI-driven health decision-making. Future study can focus on incorporating more datasets and exploiting more acoustic features for speech-based MCI detection.

The previous study indicated that ubiquitination is involved in the freezing tolerance of hydrated seeds. Parthenolide (PN), inducing the ubiquitination of MDM2, an E3 ring-finger ubiquitin ligase, adversely affects the freezing tolerance of hydrated lettuce seeds. Therefore, a proteomics analysis was conducted to identify PN's targets in hydrated seeds exposed to cooling conditions. Several pathways, including oxidative phosphorylation (KEGG00190), amino sugar and nucleotide sugar metabolism (KEGG00520), and biosynthesis of nucleotide sugars (KEGG01250), were enriched in the PN treatment under slow-cooling conditions (3°C h−1, P < 0.05). Among the proteins in oxidative phosphorylation, the expression of NADH dehydrogenases and ATP synthases (ATPsyn) decreased in PN treatment. In contrast, uncoupling proteins increased after PN treatment, which led to the dissociation of the electron transport chain from ATP synthesis. Treatments with rotenone, dicoumarol, and oligomycin (i.e., oxidative phosphorylation inhibitors) decreased the survival rate of hydrated seeds under freezing conditions, which indicated that energy metabolism was related to the freezing tolerance of hydrated seeds. The predicted interactions between PN and MDM2-like proteins of Lactuca indicated that LsMDM2-5 forms two potential hydrogen bonds with PN. Furthermore, based on AlphaFold predictions and yeast 2-hybrid results, MDM2-5 might interact directly with NADH2. The knockdown of MDM2-5 by RNAi caused a higher level of NADH2 and ATPsyn and a higher freezing tolerance of hydrated seeds. This indicated that MDM2 played negative roles in regulating ATP synthesis and freezing tolerance of hydrated seeds.

In this paper, on–off switching digitization of a W-band variable gain power amplifier (VGPA) with above 60 dB dynamic range is introduced for large-scale phased array. Digitization techniques of on–off switching modified stacking transistors with partition are proposed to optimize configuration of control sub-cells. By the proposed techniques, gain control of a radio frequency variable gain amplifier (VGA) could be highly customized for both coarse and fine switching requirements instead of using additional digital-to-analog converters to tune the overall amplifier bias. The designed VGA in 130 nm SiGe has achieved switchable gain range from −46.4 to 20.6 dB and power range from −25.0 to 15.7 dBm at W band. The chip size of the fabricated VGPA is about 0.31 mm × 0.1 mm.

Cross-language internet memes have emerged as a unique and popular mode of online communication, combining bilingual elements with visually textual components. These memes exhibit distinctive characteristics at semantic, syntactic, and pragmatic levels, rendering them a noteworthy semiotic phenomenon in contemporary digital culture. To deepen our understanding of cross-language internet memes, this study investigates user perceptions through a questionnaire, employing SPSS Statistics software for analysis. Applying a social semiotic approach, we decipher the semiotic mechanisms of cross-language memes, shedding light on their potential implications for identity construction. Additionally, we reflect on two prominent trends in internet meme development: the shift from monomodal to multimodal communication and from monolingual to multilingual expressions. This research hopes to provide insights for meme research and online discourse investigations.

We present a theory that quantifies the interplay between intrapore and interpore flow variabilities and their impact on hydrodynamic dispersion. The theory reveals that porous media with varying levels of structural disorder exhibit notable differences in interpore flow variability, characterised by the flux-weighted probability density function (PDF), $\hat {\psi }_\tau (\tau ) \sim \tau ^{-\theta -2}$, for advection times $\tau$ through conduits. These differences result in varying relative strengths of interpore and intrapore flow variabilities, leading to distinct scaling behaviours of the hydrodynamic dispersion coefficient $D_L$, normalised by the molecular diffusion coefficient $D_m$, with respect to the Péclet number $Pe$. Specifically, when $\hat {\psi }_\tau (\tau )$ exhibits a broad distribution of $\tau$ with $\theta$ in the range of $(0, 1)$, the dispersion undergoes a transition from power-law scaling, $D_L/D_m \sim Pe^{2-\theta }$, to linear scaling, $D_L/D_m \sim Pe$, and eventually to logarithmic scaling, $D_L/D_m \sim Pe\ln (Pe)$, as $Pe$ increases. Conversely, when $\tau$ is narrowly distributed or when $\theta$ exceeds 1, dispersion consistently follows a logarithmic scaling, $D_L/D_m \sim Pe\ln (Pe)$. The power-law and linear scaling occur when interpore variability predominates over intrapore variability, while logarithmic scaling arises under the opposite condition. These theoretical predictions are supported by experimental data and network simulations across a broad spectrum of porous media.

This study aimed to demonstrate the utilization value of 1PN embryos. The 1PN zygotes collected from December 2021 to September 2022 were included in this study. The embryo development, the pronuclear characteristics, and the genetic constitutions were investigated. The overall blastocyst formation and good-quality blastocyst rates in 1PN zygotes were 22.94 and 16.24%, significantly lower than those of 2PN zygotes (63.25 and 50.23%, respectively, P = 0.000). The pronuclear characteristics were found to be correlated with the developmental potential. When comparing 1PN zygotes that developed into blastocysts to those that arrested, the former exhibited a significantly larger area (749.49 ± 142.77 vs. 634.00 ± 119.05, P = 0.000), a longer diameter of pronuclear (29.81 ± 3.08 vs. 27.30 ± 3.00, P = 0.000), and a greater number of nucleolar precursor body (NPB) (11.56 ± 3.84 vs. 7.19 ± 2.73, P = 0.000). Among the tested embryos, the diploidy euploidy rate was significantly higher in blastocysts in comparison with the arrested embryos (66.67 vs. 11.76%, P = 0.000), which was also significantly higher in IVF-1PN blastocysts than in ICSI-1PN blastocysts (75.44 vs. 25.00%, P = 0.001). However, the pronuclear characteristics were not found to be linked to the chromosomal ploidy once they formed blastocysts.

In summary, while the developmental potential of 1PN zygotes is reduced, our study shows that, in addition to the reported pronuclear area and diameter, the number of NPB is also associated with their developmental potential. The 1PN blastocysts exhibit a high diploidy euploidy rate, are recommend to be clinically used post genetic testing, especially for patients who do not have other 2PN embryos available.

Glycosylation modifications of proteins and glycan hydrolysis are critical for protein function in biological processes. Aberrations in glycosylation enzymes are linked to lysosomal storage disorders (LSDs), immune interactions, congenital disorders and tumour progression. Mannosidase alpha class 2B member 1 (MAN2B1) is a lysosomal hydrolase from the α-mannosidase family. Dysfunction of MAN2B1 has been implicated as causative factors in mannosidosis, a lysosomal storage disorder characterised by cognitive impairment, hearing loss and immune system and skeletal anomalies. Despite decades of research, its role in pathogenic infections, autoimmune conditions, cancers and neurodegenerative pathologies is highly ambiguous. Future studies are required to shed more light on the intricate functioning of MAN2B1. To this end, we review the biological functions, expression patterns, enzymatic roles and potential implications of MAN2B1 across various cell types and disease contexts. Additionally, the novel insights presented in this review may aid in understanding the role of MAN2B1 in immune cells, thereby paving the way for targeted therapeutic interventions in immune-related disorders.

Predicting epidemic trends of coronavirus disease 2019 (COVID-19) remains a key public health concern globally today. However, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection rate in previous studies of the transmission dynamics model was mostly a fixed value. Therefore, we proposed a meta-Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model by adding a time-varying SARS-CoV-2 reinfection rate to the transmission dynamics model to more accurately characterize the changes in the number of infected persons. The time-varying reinfection rate was estimated using random-effect multivariate meta-regression based on published literature reports of SARS-CoV-2 reinfection rates. The meta-SEIRS model was constructed to predict the epidemic trend of COVID-19 from February to December 2023 in Sichuan province. Finally, according to the online questionnaire survey, the SARS-CoV-2 infection rate at the end of December 2022 in Sichuan province was 82.45%. The time-varying effective reproduction number in Sichuan province had two peaks from July to December 2022, with a maximum peak value of about 15. The prediction results based on the meta-SEIRS model showed that the highest peak of the second wave of COVID-19 in Sichuan province would be in late May 2023. The number of new infections per day at the peak would be up to 2.6 million. We constructed a meta-SEIRS model to predict the epidemic trend of COVID-19 in Sichuan province, which was consistent with the trend of SARS-CoV-2 positivity in China. Therefore, a meta-SEIRS model parameterized based on evidence-based data can be more relevant to the actual situation and thus more accurately predict future trends in the number of infections.

The liver has multiple functions such as detoxification, metabolism, synthesis and storage. Folate is a water-soluble vitamin B9, which participates in one-carbon transfer reactions, maintains methylation capacity and improves oxidative stress. Folic acid is a synthetic form commonly used as a dietary supplement. The liver is the main organ for storing and metabolising folate/folic acid, and the role of folate/folic acid in liver diseases has been widely studied. Deficiency of folate results in methylation capacity dysfunction and can induce liver disorders. However, adverse effects of excessive use of folic acid on the liver have also been reported. This review aims to explore the mechanism of folate/folic acid in different liver diseases, promote further research on folate/folic acid and contribute to its rational clinical application.

To investigate the associations between dietary patterns and biological ageing, identify the most recommended dietary pattern for ageing and explore the potential mediating role of gut microbiota in less-developed ethnic minority regions (LEMRs). This prospective cohort study included 8288 participants aged 30–79 years from the China Multi-Ethnic Cohort study. Anthropometric measurements and clinical biomarkers were utilised to construct biological age based on Klemera and Doubal’s method (KDM-BA) and KDM-BA acceleration (KDM-AA). Dietary information was obtained through the baseline FFQ. Six dietary patterns were constructed: plant-based diet index, healthful plant-based diet index, unhealthful plant-based diet index, healthy diet score, Dietary Approaches to Stop Hypertension (DASH), and alternative Mediterranean diets. Follow-up adjusted for baseline analysis assessed the associations between dietary patterns and KDM-AA. Additionally, quantile G-computation identified significant beneficial and harmful food groups. In the subsample of 764 participants, we used causal mediation model to explore the mediating role of gut microbiota in these associations. The results showed that all dietary patterns were associated with KDM-AA, with DASH exhibiting the strongest negative association (β = −0·91, 95 % CI (–1·19, −0·63)). The component analyses revealed that beneficial food groups primarily included tea and soy products, whereas harmful groups mainly comprised salt and processed vegetables. In mediation analysis, the Synergistetes and Pyramidobacter possibly mediated the negative associations between plant-based diets and KDM-AA (5·61–9·19 %). Overall, healthy dietary patterns, especially DASH, are negatively associated with biological ageing in LEMRs, indicating that Synergistetes and Pyramidobacter may be potential mediators. Developing appropriate strategies may promote healthy ageing in LEMRs.

Over the last decade, we have gained a better understanding of impulse control disorder in Parkinson’s disease (PD-ICD), a medication complication in PD. Researchers were aware of its complexity and took efforts to learn more about its diagnostic and treatment possibilities. Nevertheless, clinical management for it is currently neglected. We conducted a narrative overview of literature published from 2012 to October 2023 on various aspects of clinical management for PD-ICD. A potential “susceptibility-catalytic-stress” model in the development of PD-ICD was proposed and a profile encoding predictors for PD-ICD was created. Based on these predictors, some methods for prediction were recently developed for better prediction, such as the polymorphic dopamine genetic risk score and the clinic-genetic ICD-risk score. A variety of treatment options, including dose reduction of dopamine receptor agonists (DAs), DAs removal, DAs switch, and add-on therapy, are investigated with inconsistent reports. Based on current findings, we developed a clinical management model prototype centered on prevention, consisting of prediction, prevention, follow-up and monitoring, therapy, and recurrence prevention, for clinical reference, and further proposed 4 key clinical management principles, including standardization, prediction centered, persistence, and whole course.