LncRNA PVT1 promotes gemcitabine resistance of pancreatic cancer via activating Wnt/β-catenin and autophagy pathway through modulating the miR-619-5p/Pygo2 and miR-619-5p/ATG14 axes

BACKGROUND

Pancreatic cancer is one of the most lethal malignancies and has an extremely poor diagnosis and prognosis. The development of resistance to gemcitabine is still a major challenge. The long noncoding RNA PVT1 was reported to be involved in carcinogenesis and chemoresistance; however, the mechanism by which PVT1 regulates the sensitivity of pancreatic cancer to gemcitabine remains poorly understood.

METHODS

The viability of pancreatic cancer cells was assessed by MTT assay in vitro and xenograft tumor formation assay in vivo. The expression levels of PVT1 and miR-619-5p were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Western blotting analysis and qRT-PCR were performed to assess the protein and mRNA levels of Pygo2 and ATG14, respectively. Autophagy was explored via autophagic flux detection under confocal microscopy and autophagic vacuole investigation under transmission electron microscopy (TEM). The functional role and mechanism of PVT1 were further investigated by gain- and loss-of-function assays in vitro.

RESULTS

In the present study, we demonstrated that PVT1 was up-regulated in gemcitabine-resistant pancreatic cancer cell lines. Gain- and loss-of-function assays revealed that PVT1 impaired sensitivity to gemcitabine in vitro and in vivo. We further found that PVT1 up-regulated the expression of both Pygo2 and ATG14 and thus regulated Wnt/β-catenin signaling and autophagic activity to overcome gemcitabine resistance through sponging miR-619-5p. Moreover, we discovered three TCF/LEF binding elements (TBEs) in the promoter region of PVT1, and activation of Wnt/β-catenin signaling mediated by the up-regulation of Pygo2 increased PVT1 expression by direct binding to the TBE region. Furthermore, PVT1 was discovered to interact with ATG14, thus promoting assembly of the autophagy specific complex I (PtdIns3K-C1) and ATG14-dependent class III PtdIns3K activity.

CONCLUSIONS

These data indicate that PVT1 plays a critical role in the sensitivity of pancreatic cancer to gemcitabine and highlight its potential as a valuable target for pancreatic cancer therapy.

Endophytic Fungal Community of Huperzia serrata: Diversity and Relevance to the Production of Huperzine A by the Plant Host

As the population ages globally, there seem to be more people with Alzheimer's disease. Unfortunately, there is currently no specific treatment for the disease. At present, Huperzine A (HupA) is one of the best drugs used for the treatment of Alzheimer's disease and has been used in clinical trials for several years in China. HupA was first separated from Huperzia serrata, a traditional medicinal herb that is used to cure fever, contusions, strains, hematuria, schizophrenia, and snakebite for several hundreds of years in China, and has been confirmed to have acetylcholinesterase inhibitory activity. With the very slow growth of H. serrata, resources are becoming too scarce to meet the need for clinical treatment. Some endophytic fungal strains that produce HupA were isolated from H. serrate in previous studies. In this article, the diversity of the endophytic fungal community within H. serrata was observed and the relevance to the production of HupA by the host plant was further analyzed. A total of 1167 strains were obtained from the leaves of H. serrata followed by the stems (1045) and roots (824). The richness as well as diversity of endophytic fungi within the leaf and stem were higher than in the root. The endophytic fungal community was similar within stems as well as in leaves at all taxonomic levels. The 11 genera (Derxomyces, Lophiostoma, Cyphellophora, Devriesia, Serendipita, Kurtzmanomyces, Mycosphaerella, Conoideocrella, Brevicellicium, Piskurozyma, and Trichomerium) were positively correlated with HupA content. The correlation index of Derxomyces with HupA contents displayed the highest value (CI = 0.92), whereas Trichomerium showed the lowest value (CI = 0.02). Through electrospray ionization mass spectrometry (ESI-MS), it was confirmed that the HS7-1 strain could produce HupA and the total alkaloid concentration was 3.7 ug/g. This study will enable us to screen and isolate the strain that can produce HupA and to figure out the correlation between endophytic fungal diversity with HupA content in different plant organs. This can provide new insights into the screening of strains that can produce HupA more effectively.

Hemoperfusion Adsorbents for Removal of Common Toxins in Liver and Kidney Failure: Recent Progress, Challenges, and Prospects

Liver and kidney failure can lead to extensive accumulation of toxic metabolites in the blood and tissues, such as bilirubin, blood ammonia, endotoxins, cytokines, creatinine, uric acid, and urea, which aggravate the progression of the disease. Hemoperfusion can effectively adsorb and remove toxins from the blood and treat liver and kidney failure. However, the adsorption efficiency and safety of traditional hemoperfusion adsorbents are not ideal. Thus, it is urgent to develop adsorbents with good blood compatibility, as well as high adsorption and strong selective capacities, to fulfill the clinical needs. In recent years, new hemoperfusion adsorbents with improved adsorption performance and good blood compatibility have been developed. This review classifies and summarizes the recent research progress in hemoperfusion adsorbents for common blood toxins (bilirubin, blood ammonia, endotoxins, cytokines, creatinine, uric acid, and urea) produced by liver and kidney failure. The composition and structure of various toxin adsorbents, toxin adsorption performance, biocompatibility, blood safety, and the adsorption mechanisms of toxins are discussed. Based on a summary of recent studies, feasible strategies have been explored for designing and preparing hemoperfusion adsorbents to fulfill future development requirements. The trends and clinical application prospects of various toxin adsorbents are also discussed.

The effect of dipeptidyl peptidase IV on disease-associated microglia phenotypic transformation in epilepsy

BACKGROUND

Accumulating evidence suggests that disease-associated microglia (DAM), a recently discovered subset of microglia, plays a protective role in neurological diseases. Targeting DAM phenotypic transformation may provide new therapeutic options. However, the relationship between DAM and epilepsy remains unknown.

METHODS

Analysis of public RNA-sequencing data revealed predisposing factors (such as dipeptidyl peptidase IV; DPP4) for epilepsy related to DAM conversion. Anti-epileptic effect was assessed by electroencephalogram recordings and immunohistochemistry in a kainic acid (KA)-induced mouse model of epilepsy. The phenotype, morphology and function of microglia were assessed by qPCR, western blotting and microscopic imaging.

RESULTS

Our results demonstrated that DPP4 participated in DAM conversion and epilepsy. The treatment of sitagliptin (a DPP4 inhibitor) attenuated KA-induced epilepsy and promoted the expression of DAM markers (Itgax and Axl) in both mouse epilepsy model in vivo and microglial inflammatory model in vitro. With sitagliptin treatment, microglial cells did not display an inflammatory activation state (enlarged cell bodies). Furthermore, these microglia exhibited complicated intersections, longer processes and wider coverage of parenchyma. In addition, sitagliptin reduced the activation of NF-κB signaling pathway and inhibited the expression of iNOS, IL-1β, IL-6 and the proinflammatory DAM subset gene CD44.

CONCLUSION

The present results highlight that the DPP4 inhibitor sitagliptin can attenuate epilepsy and promote DAM phenotypic transformation. These DAM exhibit unique morphological features, greater migration ability and better surveillance capability. The possible underlying mechanism is that sitagliptin can reduce the activation of NF-κB signaling pathway and suppress the inflammatory response mediated by microglia. Thus, we propose DPP4 may act as an attractive direction for DAM research and a potential therapeutic target for epilepsy.

Deep brain stimulation of fornix in Alzheimer's disease: From basic research to clinical practice

Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases associated with the degradation of memory and cognitive ability. Current pharmacotherapies show little therapeutic effect in AD treatment and still cannot prevent the pathological progression of AD. Deep brain stimulation (DBS) has shown to enhance memory in morbid obese, epilepsy and traumatic brain injury patients, and cognition in Parkinson's disease (PD) patients deteriorates during DBS off. Some relevant animal studies and clinical trials have been carried out to discuss the DBS treatment for AD. Reviewing the fornix trials, no unified conclusion has been reached about the clinical benefits of DBS in AD, and the dementia ratings scale has not been effectively improved in the long term. However, some patients have presented promising results, such as improved glucose metabolism, increased connectivity in cognition-related brain regions and even elevated cognitive function rating scale scores. The fornix plays an important regulatory role in memory, attention, and emotion through its complex fibre projection to cognition-related structures, making it a promising target for DBS for AD treatment. Moreover, the current stereotaxic technique and various evaluation methods have provided references for the operator to select accurate stimulation points. Related adverse events and relatively higher costs in DBS have been emphasized. In this article, we summarize and update the research progression on fornix DBS in AD and seek to provide a reliable reference for subsequent experimental studies on DBS treatment of AD.

Identification of Wnt/β-Catenin- and Autophagy-Related lncRNA Signature for Predicting Immune Efficacy in Pancreatic Adenocarcinoma

Pancreatic cancer is one of the tumors with a poor prognosis. Therefore, it is significant and urgent to explore effective biomarkers for risk stratification and prognosis prediction to promote individualized treatment and prolong the survival of patients with PAAD. In this study, we identified Wnt/β-catenin- and autophagy-related long non-coding RNAs (lncRNAs) and demonstrated their role in predicting immune efficacy for PAAD patients. The univariate and multivariate Cox proportional hazards analyses were used to construct a prognostic risk model based on six autophagy- and Wnt/β-catenin-related lncRNAs (warlncRNAs): LINC01347, CASC8, C8orf31, LINC00612, UCA1, and GUSBP11. The high-risk patients were significantly associated with poor overall survival (OS). The receiver operating characteristic (ROC) curve analysis was used to assess the predictive accuracy of the prognostic risk model. The prediction efficiency was supported by the results of an independent validation cohort. Subsequently, a prognostic nomogram combining warlncRNAs with clinical indicators was constructed and showed a good predictive efficiency for survival risk stratification. Furthermore, functional enrichment analysis demonstrated that the signature according to warlncRNAs is closely linked to malignancy-associated immunoregulatory pathways. Correlation analysis uncovered that warlncRNAs' signature was considerably associated with immunocyte infiltration, immune efficacy, tumor microenvironment score, and drug resistance.

Aromatic amino acids in the cellulose binding domain of Penicillium crustosum endoglucanase EGL1 differentially contribute to the cellulose affinity of the enzyme

The cellulose binding domain (CBD) of cellulase binding to cellulosic materials is the initiation of a synergistic action on the enzymatic hydrolysis of the most abundant renewable biomass resources in nature. The binding of the CBD domain to cellulosic substrates generally relies on the interaction between the aromatic amino acids structurally located on the flat face of the CBD domain and the glucose rings of cellulose. In this study, we found the CBD domain of a newly cloned Penicillium crustosum endoglucanase EGL1, which was phylogenetically related to Aspergillus, Fusarium and Rhizopus, and divergent from the well-characterized Trichoderma reeseis cellulase CBD domain, contain two conserved aromatic amino acid-rich regions, Y₄₅₁-Y₄₅₂ and Y₄₇₇-Y₄₇₈-Y₄₇₉, among which three amino acids Y₄₅₁, Y₄₇₇, and Y₄₇₈ structurally sited on a flat face of this domain. Cellulose binding assays with green fluorescence protein as the marker, adsorption isotherm assays and an isothermal titration calorimetry assays revealed that although these three amino acids participated in this process, the Y₄₅₁-Y₄₅₂ appears to contribute more to the cellulose binding than Y₄₇₇-Y₄₇₈-Y₄₇₉. Further glycine scanning mutagenesis and structural modelling revealed that the binding between CBD domain and cellulosic materials might be multi-amino-acids that participated in this process. The flexible poly-glucose molecule could contact Y₄₅₁, Y₄₇₇, and Y₄₇₈ which form the contacting flat face of CBD domain as the typical model, some other amino acids in or outside the flat face might also participate in the interaction. Thus, it is possible that the conserved Y₄₅₁-Y₄₅₂ of CBD might have a higher chance of contacting the cellulosic substrates, contributing more to the affinity of CBD than the other amino acids.

A Novel Demodulation Analysis Technique for Bearing Fault Diagnosis via Energy Separation and Local Low-Rank Matrix Approximation

Bearing fault diagnosis is of utmost importance in the maintenance of mechanical equipment. The collected fault vibration signal generally presents a modulated nature due to the special structure and dynamic characteristics of the bearings. This paper introduces a novel demodulation analysis technique via energy separation and local low-rank matrix approximation (LLORMA) to address this type of signal. The amplitude envelope and instantaneous frequency of the signal can be calculated via an energy separation algorithm based on the Teager energy operator. We can confirm the bearing faults by comparing the peak frequencies of the Fourier spectrum of the amplitude envelope and instantaneous frequency with the theoretical bearing fault-related frequencies. However, this algorithm is only suitable for handling single-component signals. In addition, the powerful background noise has a serious effect on the demodulation results. To tackle these problems, a new signal decomposition method based on LLORMA is proposed to decompose the signal into several single-components and eliminate the noise simultaneously. After that, the single-component signal representing the fault characteristics can be identified via the high frequency feature of the modulated signal. The analysis of the simulated signal and the bearing outer race fault signal collected from a bearing-gear fault test rig indicate that the proposed technique has an excellent diagnostic performance for bearing fault signals.

Unveiling the impact of digital industrialization on synergistic governance of pollution and carbon reduction in China: a geospatial perspective

The impact of digital industrialization on regional pollution control and carbon reduction in China is an area that remains largely unexplored despite being a new driving force in promoting high-quality economic development. This study constructs a combined system synergy model to measure the synergistic governance effect of regional pollution and carbon reduction in China from 2011 to 2020 and then estimates the direct impact and spatial spillover effect using a spatial dual-weight model. Our findings indicate that digital industrialization has a greater impact on regional pollution reduction and carbon reduction as geographical distance decreases, with the spillover effect with close geographical relationships being higher than that of adjacent. Furthermore, the heterogeneity analysis reveals that the added value of digital technology and services has a significantly positive effect, while the spatial spillover effect of the added value of digital infrastructure is significantly negative. Finally, our mechanism judgements prove digital industrialization can impact the level of regional co-governance of pollution and carbon reduction through source prevention, process control, and end-treatment. Our study provides a factual basis for further promoting China's environmental pollution control and carbon reduction behavior and offers a method to use different spatial weights in depth.

Fungal Strains with Identical Genomes Were Found at a Distance of 2000 Kilometers after 40 Years

Heredity and variation are inherent characteristics of species and are mainly reflected in the stability and variation of the genome; the former is relative, while the latter is continuous. However, whether life has both stable genomes and extremely diverse genomes at the same time is unknown. In this study, we isolated Sclerotinia sclerotiorum strains from sclerotium samples in Quincy, Washington State, USA, and found that four single-sclerotium-isolation strains (PB4, PB273, PB615, and PB623) had almost identical genomes to the reference strain 1980 isolated in the west of Nebraska 40 years ago. The genome of strain PB4 sequenced by the next-generation sequencing (NGS) and Pacific Biosciences (PacBio) sequencing carried only 135 single nucleotide polymorphisms (SNPs) and 18 structural variations (SVs) compared with the genome of strain 1980 and 48 SNPs were distributed on Contig_20. Based on data generated by NGS, three other strains, PB273, PB615, and PB623, had 256, 275, and 262 SNPs, respectively, against strain 1980, which were much less than in strain PB4 (532 SNPs) and none of them occurred on Contig_20, suggesting much closer genomes to strain 1980 than to strain PB4. All other strains from America and China are rich in SNPs with a range of 34,391-77,618 when compared with strain 1980. We also found that there were 39-79 SNPs between strain PB4 and its sexual offspring, 53.1% of which also occurred on Contig_20. Our discoveries show that there are two types of genomes in S. sclerotiorum, one is very stable and the other tends to change constantly. Investigating the mechanism of such genome stability will enhance our understanding of heredity and variation.

Leukemia inhibitory factor protects against experimental periodontitis through immuno-modulations of both macrophages and periodontal ligament fibroblasts

BACKGROUND

To explore the role of leukemia inhibitory factor (LIF) in periodontitis via in vivo and in vitro experiments.

METHODS

The second upper molar of LIF knockout mice and their wild-type littermates were ligated for 8 days. Micro-computed tomography (micro-CT), histological analysis, and quantitative real-time polymerase chain reaction (qRT-PCR) were performed. The expression levels of proinflammatory cytokines were examined in mouse bone marrow derived macrophages and human periodontal ligament fibroblasts (HPDLFs) after lipopolysaccharide (LPS) treatment.

RESULTS

LIF deficiency promoted alveolar bone loss, inflammatory cells infiltration, osteoclasts formation and collagen fiber degradation in ligature-induced mouse, along with higher expressions of proinflammatory cytokines, including interleukin-6 (IL6), IL-1β (IL1B), tumor necrosis factor-α (TNFA), matrix metalloproteinase 13 (MMP13), and RANKL/OPG ratio. Additionally, LIF deletion led to higher expression levels of these proinflammatory cytokines in mouse bone marrow-derived macrophages from both femur and alveolar bone and HPDLFs when treated with LPS. Administration of recombined LIF attenuated TNFA, IL1B, and RANKL/OPG ratio in HPDLFs.

CONCLUSIONS

These findings indicate that LIF deficiency promotes the progress of periodontitis via modulating immuno-inflammatory responses of macrophages and periodontal ligament fibroblasts, and the application of LIF may be an adjunctive treatment for periodontitis to resolute inflammation.

Alterations and resilience of intestinal microbiota to increased water temperature are accompanied by the recovery of immune function in Nile tilapia

In the context of ongoing global warming, fish, as aquatic ectotherms, are highly vulnerable to increased water temperature caused by climate change and extreme heatwaves because of their inability to maintain their body temperature. After prolonged coevolution, the intestinal microbiota has become an integral part of fish and plays a pivotal role in immunity and metabolism. To date, however, little is known about the effects of increased water temperature on the intestinal microbiota of fish, particularly the intestinal mucosa-associated microbiota. Here, we investigated the variation patterns of the intestinal microbiota and immune status in Nile tilapia (Oreochromis niloticus; 125.02 ± 4.55 g) under increased water temperature. The results showed that the microbial diversity, structure, dominant microbes, and predicted function of fish intestinal microbiota were resilient to low-level warming (increasing by 2 °C) but not to high-level warming (increasing by 8 °C) and that fish immune parameters (serum lysozyme content and bactericidal activity) recovered simultaneously. Notably, along with compromised immune function, short-term warming (7 days) drove a significant increase in the microbial richness and diversity of fish intestinal mucosae, in which the overgrowth of opportunistic pathogens such as Romboutsia ilealis, Escherichia-Shigella, Fusobacterium, Streptococcus, Acinetobacter, and Enterobacter inhibited the colonization of potential probiotics such as Cetobacterium, ultimately resulting in a significant reduction in metabolic pathways and a significant increase in the potentially pathogenic phenotype. After long-term warming (37 days), the above alterations disappeared in low-level warming but remained in high-level warming. Critically, long-term warming disrupted the network complexity and stability of the intestinal mucosa- and digesta-associated microbiota to different extents. Collectively, this study revealed that the alterations and resilience of intestinal microbiota to increased water temperature coincided with the recovery of immune function in fish. Our findings extend the understanding of how the intestinal microbiota in aquatic ectotherms respond to increased water temperature, providing important implications for harnessing the potential benefits of host-associated microorganisms to enhance their resilience to climate change.

ZMIZ2 facilitates hepatocellular carcinoma progression via LEF1 mediated activation of Wnt/β-catenin pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies with a high lethality rate. ZMIZ2 is a transcriptional co-activator implicated in various human diseases. However, the role and molecular mechanism of ZMIZ2 in HCC remains to be elucidated.

METHODS

The expression and prognostic value of ZMIZ2 in HCC was excavated from public databases and explored by bioinformatic analysis. Then the expression of ZMIZ2 and related genes was further validated by quantitative RT-PCR, western blotting, and immunohistochemistry. Loss and gain-of-function experiments were performed in vitro and in vivo to investigate the function of ZMIZ2 in HCC. In addition, transcriptome sequencing and immunoprecipitation was conducted to explore the potential molecular mechanisms of ZMIZ2.

RESULTS

ZMIZ2 was highly expressed in HCC and associated with poor prognosis. Silencing ZMIZ2 significantly inhibited HCC cell proliferation, cell cycle process, migration, and invasion in vitro, and also inhibited the progression of HCC in vivo. Additionally, ZMIZ2 expression was correlated with immune cell infiltration in HCC samples. Somatic mutation analysis showed that ZMIZ2 and TP53 mutations jointly affected the progression of HCC. Mechanistically, ZMIZ2 interacted with LEF1 to regulate malignant progression of HCC by activating the Wnt/β-catenin pathway.

CONCLUSION

ZMIZ2 was overexpressed in HCC and associated with poor prognosis. The overexpression of ZMIZ2 was corelated with malignant phenotype, and it facilitated HCC progression via LEF1-mediated activation of the Wnt/β-catenin pathway. Furthermore, ZMIZ2 could be served as a prognostic biomarker and a new therapeutic target for HCC.

Research of multi-label text classification based on label attention and correlation networks

Multi-Label Text Classification (MLTC) is a crucial task in natural language processing. Compared to single-label text classification, MLTC is more challenging due to its vast collection of labels which include extracting local semantic information, learning label correlations, and solving label data imbalance problems. This paper proposes a model of Label Attention and Correlation Networks (LACN) to address the challenges of classifying multi-label text and enhance classification performance. The proposed model employs the label attention mechanism for a more discriminative text representation and uses the correlation network based on label distribution to enhance the classification results. Also, a weight factor based on the number of samples and a modulation function based on prediction probability are combined to alleviate the label data imbalance effectively. Extensive experiments are conducted on the widely-used conventional datasets AAPD and RCV1-v2, and extreme datasets EUR-LEX and AmazonCat-13K. The results indicate that the proposed model can be used to deal with extreme multi-label data and achieve optimal or suboptimal results versus state-of-the-art methods. For the AAPD dataset, compared with the suboptimal method, it outperforms the second-best method by 2.05% ∼ 5.07% in precision@k and by 2.10% ∼ 3.24% in NDCG@k for k = 1, 3, 5. The superior outcomes demonstrate the effectiveness of LACN and its competitiveness in dealing with MLTC tasks.

Differences of bacterioplankton communities between the source and upstream regions of the Yangtze River: microbial structure, co-occurrence pattern, and environmental influencing factors

The source area of the Yangtze River is located in the hinterland of the Qinghai-Tibet Plateau, which is known as the "Earth's third pole." It is the water conservation area and the natural barrier of the ecosystem of the Yangtze River basin. It is also the most sensitive area of the natural ecosystem, and the ecological environment is very fragile. Microorganisms play key roles in the biogeochemical processes of water. In this paper, the bacterioplankton communities in the source and upstream regions of the Yangtze River were studied based on 16S rRNA high-throughput sequencing, and their environmental influencing factors were further analyzed. Results showed that the upstream region had higher richness and diversity than the source region. The predominant bacterial phyla in the source and upstream regions were Proteobacteria, Firmicutes, and Actinobacteriota. The bacterial phyla associated with municipal pollution and opportunistic pathogen, such as Firmicutes and Actinobacteriota, were more abundant in the upstream. By contrast, distinct planktonic bacterial genera associated with mining pollution, such as Acidiphilium and Acidithiobacillus, were more abundant in the source region. The co-occurrence network showed that the interaction of bacterioplankton community is more frequent in the upstream. The bacterioplankton community compositions, richness, and functional profiles were affected by the spatial heterogeneity. Moreover, variation partitioning analysis further confirmed that the amount of variation in the source region independently explained by variables of altitude was the largest, followed by water nutrient. This paper revealed the spatial distribution of planktonic bacterial communities in the source and upstream regions of the Yangtze River and its correlation with environmental factors, providing information support for ensuring the health and safety of aquatic ecosystems in the Yangtze River Basin.

Highly Linear Stretching Sensors with Braiding Structure Constraining Cracks

Stretchable fiber-based electronics can be triggered by joint activities of human beings to produce varied resistance signals, provoking extensive attention from sports fitness, health care, wearables, and other related fields. The linearity of the response signal, as a quintessential parameter, is paramount for the performance evaluation of stretching sensors. In this study, three-strand braid (TSB) is fabricated via braiding three filaments of polypyrrole/polyurethane (PPy/PU). Equivalent circuit indicates that every three adjacent segments in TSB connect in parallel, thus TSB outperforms single PPy/PU filament in electric conduction. In contrast to the single PPy/PU filament, the TSB due to its interlocked structure suffers less stress and thus constrains cracks, performing great linearity (R2 = 0.995 in 0-75% strain), fast response time (40 ms), and satisfactory reciprocating stability (10 000 cycles). The working suitability tests of TSB in manifold elongations, stretching rates, and initial functional spacing suggest that the spacing of 1, 2, and 4 cm is suitable for the elongation range of 0.8-1.6, 0.8-2.4, and 1.2-4.8 cm, respectively, with stretching rates of 4-10 mm s-1. TSB is of great service for monitoring joint activities (e.g., bending of finger, wrist, elbow), and even potential in the applications like virtual reality (VR) and augmented reality (AR).

A dual-decoder banded convolutional attention network for bone segmentation in ultrasound images

BACKGROUND

Ultrasound (US) has great potential for application in computer-assisted orthopedic surgery (CAOS) due to its non-radiative, cost-effective, and portable traits. However, bone segmentation from low-quality US images has been challenging. Traditional segmentation methods cannot achieve satisfactory results due to their high customization and dependence on bone morphology. Existing deep learning-based methods make it difficult to ensure efficient and accurate segmentation due to the ignorance of prior knowledge of bone features during feature learning.

PURPOSE

This paper aims to systematically investigate feature extraction and segmentation methodologies of bone US images and then proposes an innovative convolutional neural network to address the need for precise and efficient bone structure extraction in CAOS.

METHODS

This paper has proposed a dual-decoder banded convolutional attention network (BCA-Net), which takes the raw US image as input and simplified U-Net as the baseline network. Multiscale banded convolution kernels are employed internally in the BCA-Net model, leveraging the prior knowledge that bone surfaces in US images are exhibited as bright bands of a few millimeters in width. Additionally, a shared encoder to extract input features and two independent decoders to generate outputs for the bone surface and bone shadow mask are integrated into the BCA-Net model, leveraging the prior knowledge that US bone surfaces manifest low-intensity hollow shadows below. Then, a new task consistency loss is introduced that can utilize inter-task dependency fully and enhance the performance of our model. In the network construction process, a dataset containing 1623 sets of US images was adopted, and a five-fold cross-validation strategy was divided into the training and validation sets for the model's training and validation. Many vital metrics were introduced to comprehensively evaluate the model performance, including overlap, edge distance, area under curve, and model efficiency. Finally, the model performance was subjected to a confidence interval, Tukey's honest significant difference, and Cohen's d statistics at a significance level (5%) to ensure the accuracy and reliability of the obtained findings.

RESULTS

The experimental results show that the BCA-Net model performs well in the bone surface segmentation task. Its average Dice coefficient reaches 87.51%, 4.04% higher than U-Net's, proving its superior bone surface segmentation accuracy. Meanwhile, the average distance error is 0.2 mm, 0.33 mm lower than U-Net's, highlighting its accuracy in detail capture and boundary recognition. Using a confidence distance threshold of 1.02 mm, the Dice coefficient of the BCA-Net model exceeds 98%, an improvement of 1.87% over U-Net's, which is highly consistent with manual labeling. The BCA-Net model achieves a statistical significance of p-values < 0.05 in the above accuracy comparisons. In addition, the BCA-Net model has a small parameter count (5.58 M) and high computational efficiency (35.85 frames per second), further validating its excellent potential in bone surface segmentation tasks.

CONCLUSIONS

The proposed method achieves excellent performance with high accuracy and efficiency, aligning well with clinical requirements and holding excellent potential for advancing the utilization of US images in CAOS.

Replenishment of vitamin A for 7 days partially restored hepatic gene expressions altered by its deficiency in rats

We investigated the effects of vitamin A (VA) status on metabolism of Zucker rats with different genders and genotypes, and of short-term refeeding of a VA sufficient (VAS) diet on VA deficient (VAD) animals. First, male and female Zucker lean (ZL) and fatty (ZF) rats at weaning were fed a VAD or VAS diet for 8 weeks. Second, male VAD ZL rats were fed a VAS diet for 3 (VAD-VAS3d) or 7 (VAD-VAS7d) days. The body weight (BW), blood parameters, and hepatic expressions of genes for metabolism were determined. VA deficiency reduced BW gain in ZL and ZF rats of either gender. VAD ZL rats had lower plasma glucose, insulin, and leptin levels than VAS ZL rats. VAD-VAS3d and VAD-VAS7d rats had higher plasma glucose, insulin, and leptin levels than that in the VAD rats. The hepatic mRNA levels of Gck, Cyp26a1, Srebp-1c, Igf1, Rarb, Rxra, Rxrg, Pparg, and Ppard were lowered by VA deficiency. Refeeding of the VAS diet for 3 days restored the Gck and Cyp26a1 expressions, and for 7 days restored the Gck, Cyp26a1, Igf1, and Rxrb expressions significantly. The 7-day VA replenishment partially restored the hepatic gene expressions and metabolic changes in VAD ZL rats.

Effect of an extension speech training program based on Chinese idioms in patients with post-stroke non-fluent aphasia: A randomized controlled trial

BACKGROUND

Chinese idioms have potential to act as preliminary training material in studies on post-stroke aphasia.

OBJECTIVE

To explore an extension speech training program that takes Chinese idioms as context and expands them into characters, words, sentences and paragraphs and evaluate the effects of this program in patients with post-stroke non-fluent aphasia.

METHODS

This was a randomized controlled trial. We recruited patients with post-stroke non-fluent aphasia from the Renmin Hospital of Wuhan University from January 2021 to January 2022. Participants were randomly assigned to group I and group II. Patients in group I had treatment with extension speech training based on Chinese idioms, and those in group II had treatment with conventional speech rehabilitation training. The training period in both groups was 40 min daily for 2 weeks.

RESULTS

A total of 70 patients (group I, n = 34; and group II, n = 36) completed the trial and were analyzed according to protocol. There were no significant differences in baseline values between both groups. After intervention, the scores of oral expression, comprehension, and reading in the Aphasia Battery Of Chinese scale and the scores of the Comprehensive Activities of Daily Living questionnaire significantly improved in both groups (P <0.05), with group I benefiting more (P <0.05).

CONCLUSION

This extension speech training program based on Chinese idioms can improve the language function and daily communication ability of the patients with post-stroke non-fluent aphasia.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2000031825.

Development and Validation of an AI-Driven System for Automatic Literature Analysis and Molecular Regulatory Network Construction

Decoding gene regulatory networks is essential for understanding the mechanisms underlying many complex diseases. GENET is developed, an automated system designed to extract and visualize extensive molecular relationships from published biomedical literature. Using natural language processing, entities and relations are identified from a randomly selected set of 1788 scientific articles, and visualized in a filterable knowledge graph. The performance of GENET is evaluated and compared with existing methods. The named entity recognition model has achieved an overall precision of 94.23% (4835/5131; 93.56-94.84%), recall of 97.72% (4835/4948; 97.27-98.10%), and an F1 score of 95.94%. The relation extraction model has demonstrated an overall precision of 91.63% (2593/2830; 90.55-92.59%), recall of 89.17% (2593/2908; 87.99-90.25%), and an F1 score of 90.38%. GENET significantly outperforms existing methods in extracting molecular relationships (P < 0.001). Additionally, GENET has successfully predicted WNT family member 4 regulates insulin-like growth factor 2 via signal transducer and activator of transcription 3 in colon cancer. With RNA sequencing data and multiple immunofluorescence, the authenticity of this prediction is validated, supporting the promising feasibility of GENET.

Transcription factor OsMYB2 triggers amino acid transporter OsANT1 expression to regulate rice growth and salt tolerance

Amino acid transporters (AATs) play important roles in plant growth and stress tolerance; however, whether the abscisic acid signaling pathway regulates their transcription in rice (Oryza sativa) under salt stress remains unclear. In this study, we report that the transcription factor OsMYB2 (MYB transcription factor 2) of the abscisic acid signaling pathway mediates the expression of the gene encoding the AAT aromatic and neutral AAT 1 (OsANT1), which positively regulates growth and salt tolerance in rice. OsANT1 was mainly expressed in the leaf blade and panicle under normal conditions and transports leucine, phenylalanine, tyrosine, and proline (Pro), positively regulating tillering and yield in rice. Nevertheless, salt stress induced the accumulation of abscisic acid and strongly increased the expression level of OsANT1 in the root, resulting in enhanced salt tolerance of rice seedlings, as evidenced by higher Pro concentration and antioxidant-like enzyme activities and lower malondialdehyde and hydrogen peroxide concentrations. Moreover, we showed that OsMYB2 interacts with the promoter of OsANT1 and promotes its expression. Overexpression of OsMYB2 also improved tillering, yield, and salt tolerance in rice. In conclusion, our results suggest that the transcription factor OsMYB2 triggers OsANT1 expression and regulates growth and salt tolerance in rice, providing insights into the role of the abscisic acid signaling pathway in the regulatory mechanism of AATs in response to salt stress.

Unveiling the Pathogenic Role of Novel CPLANE1 Compound Heterozygous Variants in Joubert Syndrome: Insights Into mRNA Stability and NMD Pathway

Joubert syndrome (JS) is a rare neurodevelopmental disorder associated with mutations in genes involved in ciliary function. Germline variants in CPLANE1 have been implicated in JS. In this study, we investigated a family with three adverse pregnancies characterised by fetal malformations consistent with JS. Whole-exome sequencing (WES) identified compound heterozygous variants in CPLANE1: c.8893C>T (p.Gln2965*) and c.203C>T (p.Thr68Ile). Sanger sequencing confirmed the variants in the family. Bioinformatics analysis predicted that the c.203C>T variant affects mRNA splicing and protein function. Functional studies using PBMCs demonstrated that the c.203C>T variant causes exon 3 skipping, resulting in a frameshift and premature termination codon, leading to potential nonsense-mediated mRNA degradation (NMD). The mRNA transcription and translation inhibition experiment, by treatment with actinomycin D and puromycin, indicated that the c.203C>T variant leads to accelerated mRNA degradation. Notably, the inhibition of SMG1, a key marker of the NMD pathway, partially rescued mRNA expression in mutated cells, providing further evidence of NMD activation. Based on these findings and ACMG guidelines, the c.203C>T variant was reclassified from a variant of uncertain significance (VUS) to likely pathogenic. This is the first report of novel CPLANE1 compound heterozygous variants contributing to JS in this family. Our study expands the known pathogenic variant spectrum of CPLANE1 in JS and provides new insights into the molecular mechanisms of this ciliopathy.

Causality between Celiac disease and kidney disease: A Mendelian Randomization Study

Celiac disease, characterized as an autoimmune disorder, possesses the capacity to affect multiple organs and systems. Earlier research has indicated an increased risk of kidney diseases associated with celiac disease. However, the potential causal relationship between genetic susceptibility to celiac disease and the risk of kidney diseases remains uncertain. We conducted Mendelian randomization analysis using nonoverlapping European population data, examining the link between celiac disease and 10 kidney traits in whole-genome association studies. We employed the inverse variance-weighted method to enhance statistical robustness, and results' reliability was reinforced through rigorous sensitivity analysis. Mendelian randomization analysis revealed a genetic susceptibility of celiac disease to an increased risk of immunoglobulin A nephropathy (OR = 1.44; 95% confidence interval [CI] = 1.17-1.78; P = 5.7 × 10-4), chronic glomerulonephritis (OR = 1.15; 95% CI = 1.08-1.22; P = 2.58 × 10-5), and a decline in estimated glomerular filtration rate (beta = -0.001; P = 2.99 × 10-4). Additionally, a potential positive trend in the causal relationship between celiac disease and membranous nephropathy (OR = 1.37; 95% CI = 1.08-1.74; P = 0.01) was observed. Sensitivity analysis indicated the absence of pleiotropy. This study contributes novel evidence establishing a causal link between celiac disease and kidney traits, indicating a potential association between celiac disease and an elevated risk of kidney diseases. The findings provide fresh perspectives for advancing mechanistic and clinical research into kidney diseases associated with celiac disease.

The Emerging Scenario of Ferroptosis in Pancreatic Cancer Tumorigenesis and Treatment

Pancreatic cancer remains one of the most lethal forms of cancer. Currently, there is a lack of effective drug treatments for pancreatic cancer. However, as a newly discovered form of non-apoptotic cell death, ferroptosis has garnered increasing attention in relation to pancreatic cancer. Understanding the role of ferroptosis in the tumorigenesis and treatment of pancreatic cancer may enable more effective clinical trials and treatments for pancreatic cancer and may minimize side effects or restrict the emergence of drug resistance. In this review, we summarize the current knowledge regarding the process and underlying mechanisms of ferroptosis, as well as its dual role in both promoting tumorigenesis and facilitating treatment strategies for pancreatic cancer. Additionally, how ferroptosis is implicated in the development of pancreatitis and insulin resistance, indicating that ferroptosis may play an important role in the risk of pancreatitis- and insulin-resistance-related pancreatic cancers, is also addressed.

Current Strategies for Modulating Tumor-Associated Macrophages with Biomaterials in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related deaths in the world. However, there are currently few clinical diagnosis and treatment options available, and there is an urgent need for novel effective approaches. More research is being undertaken on immune-associated cells in the microenvironment because they play a critical role in the initiation and development of HCC. Macrophages are specialized phagocytes and antigen-presenting cells (APCs) that not only directly phagocytose and eliminate tumor cells, but also present tumor-specific antigens to T cells and initiate anticancer adaptive immunity. However, the more abundant M2-phenotype tumor-associated macrophages (TAMs) at tumor sites promote tumor evasion of immune surveillance, accelerate tumor progression, and suppress tumor-specific T-cell immune responses. Despite the great success in modulating macrophages, there are still many challenges and obstacles. Biomaterials not only target macrophages, but also modulate macrophages to enhance tumor treatment. This review systematically summarizes the regulation of tumor-associated macrophages by biomaterials, which has implications for the immunotherapy of HCC.