Prediction model for developing neuropsychiatric systemic lupus erythematosus in lupus patients

OBJECTIVE

This study aimed to construct a predictive model for assessing the risk of development of neuropsychiatric systemic lupus erythematosus (NPSLE) among patients with SLE based on clinical, laboratory, and meteorological data.

METHODS

A total of 2232 SLE patients were included and were randomly assigned into training and validation sets. Variables such as clinical and laboratory data and local meteorological data were screened by univariate and least absolute shrinkage and selection operator (LASSO) logistic regression modelling. After 10-fold cross-validation, the predictive model was built by multivariate logistic regression, and a nomogram was constructed to visualize the risk of NPSLE. The efficacy and accuracy of the model were assessed by receiver operating characteristic (ROC) curve and calibration curve analysis. Net clinical benefit was assessed by decision curve analysis.

RESULTS

Variables that were included in the predictive model were anti-dsDNA, anti-SSA, lymphocyte count, hematocrit, erythrocyte sedimentation rate, pre-albumin, retinol binding protein, creatine kinase isoenzyme MB, Nterminal brain natriuretic peptide precursor, creatinine, indirect bilirubin, fibrinogen, hypersensitive C-reactive protein, CO, and mild contamination. The nomogram showed a broad prediction spectrum; the area under the curve (AUC) was 0.895 (0.858-0.931) for the training set and 0.849 (0.783-0.916) for the validation set.

CONCLUSION

The model exhibits good predictive performance and will confer clinical benefit in NPSLE risk calculation. Key Points • Clinical, laboratory, and meteorological data were incorporated into a predictive model for neuropsychiatric systemic lupus erythematosus (NPSLE) in SLE patients. • Anti-dsDNA, anti-SSA, LYM, HCT, ESR, hsCRP, IBIL, PA, RBP, CO, Fib, NT-proBNP, Crea, CO, and mild contamination are predictors of the development of NPSLE and may have potential for research. • The nomogram has good predictive performance and clinical value and can be used to guide clinical diagnosis and treatment.

An Acid-Responsive Iron-Based Nanocomposite for OSCC Treatment

Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, characterized by invasiveness, local lymph node metastasis, and poor prognosis. Traditional treatment and medications have limitations, making the specific inhibition of OSCC growth, invasion, and metastasis a challenge. The tumor microenvironment exhibits mildly acidity and high concentrations of H2O2, and its exploitation for cancer treatment has been widely researched across various cancers, but research in the oral cancer field is relatively limited. In this study, by loading ultra-small Prussian blue nanoparticles (USPBNPs) into mesoporous calcium-silicate nanoparticles (MCSNs), we developed an acid-responsive iron-based nanocomposite, USPBNPs@MCSNs (UPM), for the OSCC treatment. UPM demonstrated excellent dual enzyme activities, generating toxic ·OH in a mildly acidic environment, effectively killing OSCC cells and producing O2 in a neutral environment to alleviate tissue hypoxia. The results showed that UPM could effectively inhibit the proliferation, migration, and invasion of OSCC cells, as well as the growth of mice solid tumors, without obvious systemic toxicity. The mechanisms may involve UPM inducing ferroptosis of OSCC cells by downregulating the xCT/GPX4/glutathione (GSH) axis, characterized by intracellular iron accumulation, reactive oxygen species accumulation, GSH depletion, lipid peroxidation, and abnormal changes in mitochondrial morphology. Therefore, this study provides empirical support for ferroptosis as an emerging therapeutic target for OSCC and offers a valuable insight for future OSCC treatment.

Inhibition of Lck/Fyn kinase activity promotes the differentiation of induced Treg cells through AKT/mTOR pathway

Regulatory T (Treg) cells are indispensable in maintaining the immune homeostasis and preventing autoimmune diseases. Regulatory T (Treg) cells include thymus derived Treg cells (tTregs) and peripherally induced Treg cells (iTreg), which are differentiated from antigen stimulated CD4+ naïve T cells in presence of TGFβ. tTregs are quite stable, and more immune suppressive, while iTreg cells are less stable, and are prone to differentiate into inflammatory T cells. Therefore, identification of small molecules that could promote the differentiation of iTreg cells is an attractive strategy for autoimmune diseases. Inhibition of AKT/mTOR pathway promotes their differentiation. Whether inhibition of Lck/Fyn kinase activity (upstream of AKT/mTOR pathway) can be used to promote the differentiation of iTreg cells has not been determined. Here, we showed that Srci1, a small molecular inhibitor of Lck/Fyn, promoted the differentiation of FOXP3+ iTreg cells. Srci1 treatment resulted in inhibition of phosphorylation of key components of AKT/mTOR pathway, including mTOR, p70 S6K, 4EBP1, and promoted the expression of Foxp3 and its target genes, thereby promoted differentiation of in vitro iTreg cells. Srci1 treated iTreg cells showed more similar gene expression profile to that of tTreg cells. Our results thus suggest that inhibition of Lck/Fyn kinase activity can promote the differentiation of iTreg cells, and may have implication in autoimmune diseases.

Bromuconazole exposure induces cardiac dysfunction by upregulating the expression LEF1

With the wide application of bromuconazole (BRO), a kind of triazole fungicide, the environmental problems caused by BRO have been paid more and more attention. In this study, adult male zebrafish were exposed to environmental related concentration and the maximum non-lethal concentration for zebrafish larvae (0,50 ng/L and 7.5 mg/L) for 7 days, respectively. Zebrafish exposed to BRO exhibited a significant reduction in body length and an increase in fatness index, indicating adverse physiological changes. Notably, the exposed zebrafish showed enlarged heart ventricular volumes and thinner heart walls. Transcriptome analysis of heart samples showed that BRO exposure mainly affected pathways related to cardiac energy metabolism. In addition, the amount of ATP in the heart tissue was correspondingly reduced, and the expression levels of genes related to controlling ion balance and myosin synthesis in the heart were also altered. The study extended its findings to the rat cardiomyocytes (H9C2), where similar cardiotoxic effects including changes in transcription of genes related to energy metabolism and heart function were also observed, suggesting a potential universal mechanism of BRO-induced cardiotoxicity. In a doxorubicin (DOX) induced larval zebrafish heart failure model, the expression of lymphoid enhancer-binding factor 1(LEF1), a key gene in the Wnt/β-catenin signaling pathway, was significantly increased in larval zebrafish and adult fish heart tissues and cardiomyocytes, suggesting that LEF1 might play an important role in BRO-induced cardiotoxicity. Taken together, BRO exposure could interfere with cardiac function and metabolic capacity by abnormal activation the expression of LEF1. The study emphasized the urgent need for monitoring and regulating BRO due to its harmful effects on the hearts of aquatic organisms.

Development of inducible promoters for regulating gene expression in Clostridium tyrobutyricum for biobutanol production

Clostridium tyrobutyricum is an anaerobe known for its ability to produce short-chain fatty acids, alcohols, and esters. We aimed to develop inducible promoters for fine-tuning gene expression in C. tyrobutyricum. Synthetic inducible promoters were created by employing an Escherichia coli lac operator to regulate the thiolase promoter (PCathl) from Clostridium acetobutylicum, with the best one (LacI-Pto4s) showing a 5.86-fold dynamic range with isopropyl β- d-thiogalactoside (IPTG) induction. A LT-Pt7 system with a dynamic range of 11.6-fold was then created by combining LacI-Pto4s with a T7 expression system composing of RNA polymerase (T7RNAP) and Pt7lac promoter. Furthermore, two inducible expression systems BgaR-PbgaLA and BgaR-PbgaLB with a dynamic range of ~40-fold were developed by optimizing a lactose-inducible expression system from Clostridium perfringens with modified 5' untranslated region (5' UTR) and ribosome-binding site (RBS). BgaR-PbgaLB was then used to regulate the expressions of a bifunctional aldehyde/alcohol dehydrogenase encoded by adhE2 and butyryl-CoA/acetate Co-A transferase encoded by cat1 in C. tyrobutyricum wild type and Δcat1::adhE2, respectively, demonstrating its efficient inducible gene regulation. The regulated cat1 expression also confirmed that the Cat1-catalyzed reaction was responsible for acetate assimilation in C. tyrobutyricum. The inducible promoters offer new tools for tuning gene expression in C. tyrobutyricum for industrial applications.

TYG Index as a Novel Predictor of Clinical Outcomes in Advanced Chronic Heart Failure with Renal Dysfunction Patients

Background

The triglyceride-glucose (TYG) index is a novel and reliable marker reflecting insulin resistance. Its predictive ability for cardiovascular disease onset and prognosis has been confirmed. However, for advanced chronic heart failure (acHF) patients, the prognostic value of TYG is challenged due to the often accompanying renal dysfunction (RD). Therefore, this study focuses on patients with aHF accompanied by RD to investigate the predictive value of the TYG index for their prognosis.

Methods and Results

717 acHF with RD patients were included. The acHF diagnosis was based on the 2021 ESC criteria for acHF. RD was defined as the eGFR < 90 mL/(min/1.73 m2). Patients were divided into two groups based on their TYG index values. The primary endpoint was major adverse cardiovascular events (MACEs), and the secondary endpoints is all-cause mortality (ACM). The follow-up duration was 21.58 (17.98-25.39) months. The optimal cutoff values for predicting MACEs and ACM were determined using ROC curves. Hazard factors for MACEs and ACM were revealed through univariate and multivariate COX regression analyses. According to the univariate COX regression analysis, high TyG index was identified as a risk factor for MACEs (hazard ratio = 5.198; 95% confidence interval [CI], 3.702-7.298; P < 0.001) and ACM (hazard ratio = 4.461; 95% CI, 2.962-6.718; P < 0.001). The multivariate COX regression analysis showed that patients in the high TyG group experienced 440.2% MACEs risk increase (95% CI, 3.771-7.739; P < 0.001) and 406.2% ACM risk increase (95% CI, 3.268-7.839; P < 0.001). Kaplan-Meier survival analysis revealed that patients with high TyG index levels had an elevated risk of experiencing MACEs and ACM within 30 months.

Conclusion

This study found that patients with high TYG index had an increased risk of MACEs and ACM, and the TYG index can serve as an independent predictor for prognosis.

Enhanced Cardiovascular Disease Prediction Modelling using Machine Learning Techniques: A Focus on CardioVitalnet

Aiming at early detection and accurate prediction of cardiovascular disease (CVD) to reduce mortality rates, this study focuses on the development of an intelligent predictive system to identify individuals at risk of CVD. The primary objective of the proposed system is to combine deep learning models with advanced data mining techniques to facilitate informed decision-making and precise CVD prediction. This approach involves several essential steps, including the preprocessing of acquired data, optimized feature selection, and disease classification, all aimed at enhancing the effectiveness of the system. The chosen optimal features are fed as input to the disease classification models and into some Machine Learning (ML) algorithms for improved performance in CVD classification. The experiment was simulated in the Python platform and the evaluation metrics such as accuracy, sensitivity, and F1_score were employed to assess the models' performances. The ML models (Extra Trees (ET), Random Forest (RF), AdaBoost, and XG-Boost) classifiers achieved high accuracies of 94.35%, 97.87%, 96.44%, and 99.00%, respectively, on the test set, while the proposed CardioVitalNet (CVN) achieved 87.45% accuracy. These results offer valuable insights into the process of selecting models for medical data analysis, ultimately enhancing the ability to make more accurate diagnoses and predictions.

The effects of different landscape strategies on outdoor thermal comfort in village squares: a case study in Dayuwan village in Wuhan City

Appropriate landscape configurations significantly mitigate rural thermal degradation. However, limited research exists on seasonal thermal comfort and the interconnections among landscape elements. Using ENVI-met software and field measurements, this study analyzed the microclimate of Dayuwan Village Square in Wuhan City. Fifteen design scenarios, including tree planting, building greening, albedo adjustment, and expanded tree coverage, were quantitatively evaluated to assess their impact on outdoor thermal comfort. Additionally, synergistic interactions between mitigation strategies were explored. The study found that increasing evergreen tree coverage by 50% has minimal impact on comfort during winter and spring. However, it significantly reduces temperatures in summer and autumn, resulting in average predicted mean vote (PMV) decreases of 0.315 and 0.643, respectively. Additionally, this strategy optimizes PMV values at 18:00 on extreme days, with a 0.102 decrease in summer and a 0.002 increase in winter. This research offers practical and sustainable guidance to designers for enhancing mitigation effects through optimal landscape configuration, providing a technical framework for rural environmental improvements.

Comparative performance analysis of Boruta, SHAP, and Borutashap for disease diagnosis: A study with multiple machine learning algorithms

Interpretable machine learning models are instrumental in disease diagnosis and clinical decision-making, shedding light on relevant features. Notably, Boruta, SHAP (SHapley Additive exPlanations), and BorutaShap were employed for feature selection, each contributing to the identification of crucial features. These selected features were then utilized to train six machine learning algorithms, including LR, SVM, ETC, AdaBoost, RF, and LR, using diverse medical datasets obtained from public sources after rigorous preprocessing. The performance of each feature selection technique was evaluated across multiple ML models, assessing accuracy, precision, recall, and F1-score metrics. Among these, SHAP showcased superior performance, achieving average accuracies of 80.17%, 85.13%, 90.00%, and 99.55% across diabetes, cardiovascular, statlog, and thyroid disease datasets, respectively. Notably, the LGBM emerged as the most effective algorithm, boasting an average accuracy of 91.00% for most disease states. Moreover, SHAP enhanced the interpretability of the models, providing valuable insights into the underlying mechanisms driving disease diagnosis. This comprehensive study contributes significant insights into feature selection techniques and machine learning algorithms for disease diagnosis, benefiting researchers and practitioners in the medical field. Further exploration of feature selection methods and algorithms holds promise for advancing disease diagnosis methodologies, paving the way for more accurate and interpretable diagnostic models.

Structure-Guided Discovery of Potent and Selective CLK2 Inhibitors for the Treatment of Knee Osteoarthritis

Osteoarthritis is the most common joint disorder. However, there are no disease-modifying drugs approved for OA treatment. CDC2-like kinase 2 (CLK2) could modulate Wnt signaling via alternative splicing of Wnt target genes and further affect bone differentiation, chondrocyte function, and inflammation, making CLK2 an attractive target for OA therapy. In this study, we designed and synthesized a series of highly potent CLK2 inhibitors based on Indazole 1. Among them, compound LQ23 showed more elevated inhibitory activity against CLK2 than the lead compound (IC50, 1.4 nM) with high CLK2/CLK3 selectivity (>70-fold). Furthermore, LQ23 showed outstanding antiosteoarthritis effects in vitro and in vivo, with the roles specific in decreased inflammatory cytokines, downregulated cartilage degradative enzymes, and increased joint cartilage via suppressing CLK2/Wnt signaling pathway. Overall, these data support LQ23 as a potential candidate for intra-articular knee OA therapy, leveraging its unique mechanism of action for targeted treatment.

Dendritic cells overcome Cre/Lox induced gene deficiency by siphoning cytosolic material from surrounding cells

In a previous report, keratinocytes were shown to share their gene expression profile with surrounding Langerhans cells (LCs), influencing LC biology. Here, we investigated whether transferred material could substitute for lost gene products in cells subjected to Cre/Lox conditional gene deletion. We found that in human Langerin-Cre mice, epidermal LCs and CD11b+CD103+ mesenteric DCs overcome gene deletion if the deleted gene was expressed by neighboring cells. The mechanism of material transfer differed from traditional antigen uptake routes, relying on calcium and PI3K, being susceptible to polyguanylic acid inhibition, and remaining unaffected by inflammation. Termed intracellular monitoring, this process was specific to DCs, occurring in all murine DC subsets tested and human monocyte-derived DCs. The transferred material was presented on MHC-I and MHC-II, suggesting a role in regulating immune responses.

Natural variation of STKc_GSK3 kinase TaSG-D1 contributes to heat stress tolerance in Indian dwarf wheat

Heat stress threatens global wheat (Triticum aestivum) production, causing dramatic yield losses worldwide. Identifying heat tolerance genes and comprehending molecular mechanisms are essential. Here, we identify a heat tolerance gene, TaSG-D1E286K, in Indian dwarf wheat (Triticum sphaerococcum), which encodes an STKc_GSK3 kinase. TaSG-D1E286K improves heat tolerance compared to TaSG-D1 by enhancing phosphorylation and stability of downstream target TaPIF4 under heat stress condition. Additionally, we reveal evolutionary footprints of TaPIF4 during wheat selective breeding in China, that is, InDels predominantly occur in the TaPIF4 promoter of Chinese modern wheat cultivars and result in decreased expression level of TaPIF4 in response to heat stress. These sequence variations with negative effect on heat tolerance are mainly introduced from European germplasm. Our study provides insight into heat stress response mechanisms and proposes a potential strategy to improve wheat heat tolerance in future.

EML4-ALK fusions drive lung adeno-to-squamous transition through JAK-STAT activation

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, exhibits strong cancer plasticity. We find that ALK rearrangement is detectable in 5.1-7.5% of human LUAS, and transgenic expression of EML4-ALK drives lung adenocarcinoma (LUAD) formation initially and squamous transition at late stage. We identify club cells as the main cell-of-origin for squamous transition. Through recapitulating lineage transition in organoid system, we identify JAK-STAT signaling, activated by EML4-ALK phase separation, significantly promotes squamous transition. Integrative study with scRNA-seq and immunostaining identify a plastic cell subpopulation in ALK-rearranged human LUAD showing squamous biomarker expression. Moreover, those relapsed ALK-rearranged LUAD show notable upregulation of squamous biomarkers. Consistently, mouse squamous tumors or LUAD with squamous signature display certain resistance to ALK inhibitor, which can be overcome by combined JAK1/2 inhibitor treatment. This study uncovers strong plasticity of ALK-rearranged tumors in orchestrating phenotypic transition and drug resistance and proposes a potentially effective therapeutic strategy.

TCR signaling induces STAT3 phosphorylation to promote TH17 cell differentiation

TH17 differentiation is critically controlled by "signal 3" of cytokines (IL-6/IL-23) through STAT3. However, cytokines alone induced only a moderate level of STAT3 phosphorylation. Surprisingly, TCR stimulation alone induced STAT3 phosphorylation through Lck/Fyn, and synergistically with IL-6/IL-23 induced robust and optimal STAT3 phosphorylation at Y705. Inhibition of Lck/Fyn kinase activity by Srci1 or disrupting the interaction between Lck/Fyn and STAT3 by disease-causing STAT3 mutations selectively impaired TCR stimulation, but not cytokine-induced STAT3 phosphorylation, which consequently abolished TH17 differentiation and converted them to FOXP3+ Treg cells. Srci1 administration or disrupting the interaction between Lck/Fyn and STAT3 significantly ameliorated TH17 cell-mediated EAE disease. These findings uncover an unexpected deterministic role of TCR signaling in fate determination between TH17 and Treg cells through Lck/Fyn-dependent phosphorylation of STAT3, which can be exploited to develop therapeutics selectively against TH17-related autoimmune diseases. Our study thus provides insight into how TCR signaling could integrate with cytokine signal to direct T cell differentiation.

Petrogenesis and geodynamic implications of the Late Devonian dioritic and granitic intrusive rocks in the Dananhu Belt, Eastern Tianshan Orogenic Belt

The Late Devonian magmatism of the Dananhu arc belt in the Central Asian Orogenic Belt provides a critical geological record. This study provides new comprehensive geochronological, geochemical, and Sr-Nd isotopic data of granodioritic and dioritic intrusions in the Dananhu belt. These findings contribute to unraveling the regional tectonic history and constraining the geodynamic processes involved. Zircon U-Pb dating indicates that the granodiorites and diorites were formed at 382.7 ± 3.8Ma and 363.1 ± 4.3Ma, respectively. The granodiorites show characteristics similar to I-type granites with high SiO2, low MgO and Mg# and aluminium saturation index (<1.1), negligible Eu anomalies, low (K2O + Na2O)/CaO ratios and zircon saturation temperatures (average = 696 °C). Granodiorites also show depleted isotope signatures (εNd(t) = +5.85 to +6.27 and low (87Sr/86Sr)i = 0.704082-0.704583) and juvenile TDM ages (741-793Ma), indicating their origin from a juvenile crust. The diorites are characterized by enrichments in large ion lithophile elements, U and Pb, but depleted in Nb and Ta displaying typical geochemical features of a subduction-related origin, together with high εNd(t) (+6.10 to +6.84) and low initial Sr isotopes (0.703745-0.704601), suggesting that they originated from a subduction fluid modified depleted mantle. The petrogenesis of both granodiorites and diorites in the Dananhu arc provides evidence that they formed through magmatic processes in a subduction tectonic setting. Considering the adakites associated with slab melting from previous studies in the Dananhu arc, it is plausible that the north-dipping subduction of the North Tianshan oceanic lithosphere have contributed to the Dananhu arc magmatism during the Late Devonian.

The mRNA-LNP vaccines - the good, the bad and the ugly?

The mRNA-LNP vaccine has received much attention during the COVID-19 pandemic since it served as the basis of the most widely used SARS-CoV-2 vaccines in Western countries. Based on early clinical trial data, these vaccines were deemed safe and effective for all demographics. However, the latest data raise serious concerns about the safety and effectiveness of these vaccines. Here, we review some of the safety and efficacy concerns identified to date. We also discuss the potential mechanism of observed adverse events related to the use of these vaccines and whether they can be mitigated by alterations of this vaccine mechanism approach.

Engineering the reductive tricarboxylic acid pathway in Aureobasidium pullulans for enhanced biosynthesis of poly-L-malic acid

Aureobasidium pullulans produced poly-L-malic acid (PMA) as the main metabolite in fermentation but with relatively low productivity and yield limiting its industrial application. In this study, A. pullulans ZX-10 was engineered to overexpress cytosolic malate dehydrogenase (MDH) and pyruvate carboxylase (PYC) and PMA synthetase (PMS) using a high-copy yeast episomal plasmid with the gpdA promoter from Aspergillus nidulans. Overexpressing endogenous PMS and heterologous MDH and PYC from Aspergillus oryzae respectively increased PMA production by 19 % - 37 % (0.64 - 0.74 g/g vs. 0.54 g/g for wild type) in shake-flask fermentations, demonstrating the importance of the reductive tricarboxylic acid (rTCA) pathway in PMA biosynthesis. A. pullulans co-expressing MDH and PYC produced 96.7 g/L PMA at 0.90 g/L∙h and 0.68 g/g glucose in fed-batch fermentation, which were among the highest yield and productivity reported. The engineered A. pullulans with enhanced rTCA pathway is advantageous and promising for PMA production.

Upregulation of vesicle-associated membrane protein 7 in breast cancer tissues

BACKGROUND

Vesicle-associated membrane protein 7 (VAMP7) plays oncogenic roles in cancers. However, its clinical significance in breast cancer (BC) tissues remains unknown.

OBJECTIVE

To elucidate the clinical implications of VAMP7, as well as its involvement in the tumor microenvironment and molecular pathways of breast cancer.

METHODS

BC (n=100) and non-cancerous breast tissues (n= 100) were collected for an immunohistochemical experiment (1:200). The protein expression level of VAMP7 was determined by using a semi-quantitative scoring method. High-throughput RNA-sequencing data of BC tissues were analyzed to confirm the mRNA expression trend of VAMP7. Additionally, the largest BC prognosis cohort data were collected to mine the potential impact VAMP7 has on BC progression. The association between VAMP7 and the microenvironment of BC was evaluated by using a CIBERSORT algorithm. Moreover, we explored the co-expressed molecular mechanisms of VAMP7 in BC by calculating Pearson correlation coefficients and overexpressed genes. Finally, the biological mechanism underlying the relationship between VAMP7 and the key pathways was also explored using gene set enrichment analysis (GSEA). Potential therapeutic strategies were predicted targeting VAMP7.

RESULTS

VAMP7 protein was significantly over-expressed in BC tissue than that in controls (p< 0.001). Compared with 459 normal breast tissues and 113 non-cancerous breast tissues, the expression level of VAMP7 mRNA was significantly increased in 1111 BC tissues. CD4+T cells, macrophages, and naïve B cells had a higher infiltration rate in BC tissues with high VAMP7 expression, while regulatory T cells and CD8+T cells had a lower infiltration rate. Over-expressed VAMP7 was associated with macrophages activation and transition from M1 to M2 polarization. Upregulated VAMP7 could predicted poorer OS, DMFS, PPS, and RFS outcomes. Upregulated VAMP7 co-expressed genes were significantly enriched in the cell cycle checkpoints. GSEA confirmed that over-expressed VAMP7 are markedly associated with functional enrichment in cell cycle related categories, including mitotic spindle, G2M checkpoint, and E2F targets. KU-55933 was predicted as a putative therapeutic drug for BC targeting VAMP7.

CONCLUSIONS

VAMP7 was upregulated in BC tissue and correlated with poor prognosis of BC patients. VAMP7 may promote BC progression by targeting the cell cycle pathway.

Cotton Cloth@ Polydimethylsiloxane -Graphene Flakes- Titanium Dioxide Composite Membrane for Wastewater Purification

Interfacial solar steam generation (ISSG) has been regarded as a simple and highly-efficient method for wastewater purification. Herein, we prepared a superhydrophobic composite membrane, in which polydimethylsiloxane employed as binders to pack graphite flakes and titanium dioxide tightly onto cotton cloth (defined as cotton cloth@PDMS-C-P25). Benefiting from its powerful photothermal effects, cotton cloth@PDMS-C-P25 exhibited high evaporation flux of 1.86 kg m-2 h-1 and 1.73 kg m-2 h-1 for pure water and seawater, respectively. Meanwhile, the prepared composite membrane fulfilled the targets of sewage purification set by its photocatalytic properties, which demonstrated a degradation rate of 66.1 % for Rhodamine B (RhB), and antibacterial efficiency of over 99.99 % for Escherichia coli (E. coli). Furthermore, cotton cloth@PDMS-C-P25 surface was endowed with superhydrophobic and low-adhesion characteristics mainly owing to the synergy of multiscale structure and low surface energy matter, which contribute to the anti-adhesion effect of 97.9 % for E. coli at a high concentration of 107 colony forming units (CFUs). In this work, the cost-effective, environmentally friendly, long-term stable, and superhydrophobic solar-absorber holds a potential prospect for wastewater treatment and desalination in a typical pollution-induced water shortage area.

TRPV1 modulated NLRP3 inflammasome activation via calcium in experimental subarachnoid hemorrhage

Neuroinflammation plays a key role in early brain injury (EBI) of subarachnoid hemorrhage (SAH), and NLRP3 inflammasome plays an important role in the development of neuroinflammation after SAH, but the mechanism of NLRP3 inflammasome activation after SAH is still unclear. TRPV1 is a non-selective calcium channel that is involved in the pathology of neuroinflammation, but its role in SAH has not been revealed. Our study showed that TRPV1 was significantly upregulated after SAH and was predominantly expressed in microglia/macrophages. Antagonism of TRPV1 was effective in ameliorating neurological impairment, brain edema, neuronal damage, and reducing the inflammatory response (evidenced by reducing the number of CD16/32 positive microglia/macrophages, inhibiting the expression of CD16, CD32, CD86, IL-1b, TNF-a and blocking NLRP3 inflammasome activation). However, this effect can be abolished by NLRP3 inflammasome antagonist MCC950. In vitro experiment confirmed that TRPV1 activated NLRP3 inflammasome by increasing intracellular calcium levels. In conclusion, TRPV1 mediates EBI after SAH via calcium/NLRP3, and TRPV1 is a potential therapeutic target after SAH.

Carbon dioxide production index (VCO2i) predicts hyperlactatemia during cardiopulmonary bypass in ediatric carDiac surGery (pGDP- VCO2i): Study protocol for a nested case-control trial

BACKGROUND

Hyperlactatemia (HL) during cardiopulmonary bypass (CPB) is relatively frequent in infants and associates with increased morbidity and mortality. Studies on adults have shown that carbon dioxide production index (VCO2i) during CPB is linked to the occurrence of HL, with 'critical thresholds' for VCO2i reported to be 60 mL/min/m2. However, considering infants have a higher metabolic rate and lower tolerance to hypoxia, the critical threshold of VCO2i in infants cannot be replied to the existing adults' standards. The objective of this study is to investigate the association of VCO2i during CPB and HL, and explore the critical VCO2i threshold during CPB in infants.

METHODS

VCO2i predicts hyperlactatemia during cardiopulmonary bypass in pediatric cardiac surgery (pGDP-VCO2i) is a nested case-control study. A cohort of consecutive pediatric patients of less than 3 years of age, undergoing congenital cardiac surgeries between May 2021 and December 2023 in West China Hospital will be enrolled. The VCO2i levels of each patient will be recorded every 5 min during CPB. The primary outcome is the rate of HL. The infants will be divided into two groups based on the presence or not of HL. Pre- and intraoperative factors will be tested for independent association with HL. Then, we will make an analysis, and the critical value of VCO2i will be obtained. The postoperative outcome of patients with or without HL will be compared.

DISCUSSION

This will be the first trial to investigate the association of VCO2i during CPB and HL, and explore the critical VCO2i threshold during CPB in pediatrics. The results of this study are expected to lay a foundation for clinical application of goal-directed perfusion (GDP) management strategy, and optimize the perfusion strategy and improve the prognosis of pediatric patients undergoing cardiac surgery.

TRIAL REGISTRATION

Chictr.org.cn, ChiCTR2100044296 on 16 March 2021.

Relationship between CD274 gene polymorphism and systemic lupus erythematosus risk in a Chinese Han population

OBJECTIVE

Relationship between surface antigen differentiation cluster 274 (CD274) gene polymorphism and systemic lupus erythematosus (SLE) risk is limited. This study aims to discuss whether in a Chinese Han population, CD274 gene polymorphisms may relate to SLE susceptibility.

METHODS

Three hundred and ten SLE patients and 390 healthy controls were included in this case-control study. Using the Kompetitive Allele-Specific PCR (KASP) approach, five single nucleotide polymorphisms (SNPs), including rs2890658, rs4143815, rs822339, rs2282055, and rs2297137, were genotyped for CD274 gene polymorphisms. Correlation between the polymorphisms and clinical, laboratory features in SLE patients were discussed.

RESULTS

Frequency of C allele was substantially lower in SLE patients than in healthy controls (p = .015), and CC genotype was significantly negatively related to developing SLE at locus rs4143815 (p = .013). At locus rs822339, frequency of GA genotype was higher than that of the healthy controls (p = .006). At locus rs2282055, frequency of GG genotype was lower than that of healthy controls (p = .024). According to subgroup analysis, the CD274 gene polymorphisms rs2890658, rs4143815, rs822339, rs2282055, and rs2297137 were partly linked to some clinical symptoms of SLE patients, such as Complement 4 (C4), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR).

CONCLUSION

CD274 gene polymorphisms may be susceptible to SLE in the Chinese Han people.

Breast cancer diagnosis and management guided by data augmentation, utilizing an integrated framework of SHAP and random augmentation

Recent research indicates that early detection of breast cancer (BC) is critical in achieving favorable treatment outcomes and reducing the mortality rate associated with it. With the difficulty in obtaining a balanced dataset that is primarily sourced for the diagnosis of the disease, many researchers have relied on data augmentation techniques, thereby having varying datasets with varying quality and results. The dataset we focused on in this study is crafted from SHapley Additive exPlanations (SHAP)-augmentation and random augmentation (RA) approaches to dealing with imbalanced data. This was carried out on the Wisconsin BC dataset and the effectiveness of this approach to the diagnosis of BC was checked using six machine-learning algorithms. RA synthetically generated some parts of the dataset while SHAP helped in assessing the quality of the attributes, which were selected and used for the training of the models. The result from our analysis shows that the performance of the models used generally increased to more than 3% for most of the models using the dataset obtained by the integration of SHAP and RA. Additionally, after diagnosis, it is important to focus on providing quality care to ensure the best possible outcomes for patients. The need for proper management of the disease state is crucial so as to reduce the recurrence of the disease and other associated complications. Thus the interpretability provided by SHAP enlightens the management strategies in this study focusing on the quality of care given to the patient and how timely the care is.

Pharmacological inhibition of MYC to mitigate chemoresistance in preclinical models of squamous cell carcinoma

Rationale: Cisplatin-based chemotherapy is the first-line treatment for late-stage head and neck squamous cell carcinoma (HNSCC). However, resistance to cisplatin has become a major obstacle for effective therapy. Cancer stem cells (CSCs) are critical for tumor initiation, growth, metastasis, and chemoresistance. How to effectively eliminate CSCs and overcome chemoresistance remains a key challenge. Herein, we confirmed that MYC plays critical roles in chemoresistance, and explored targeting MYC to overcome cisplatin resistance in preclinical models. Methods: The roles of MYC in HNSCC cisplatin resistance and cancer stemness were tested in vitro and in vivo. The combined therapeutic efficiency of MYC targeting using the small molecule MYC inhibitor MYCi975 and cisplatin was assessed in a 4‑nitroquinoline 1-oxide-induced model and in a patient-derived xenograft model. Results: MYC was highly-expressed in cisplatin-resistant HNSCC. Targeting MYC using MYCi975 eliminated CSCs, prevented metastasis, and overcame cisplatin resistance. MYCi975 also induced tumor cell-intrinsic immune responses, and promoted CD8+ T cell infiltration. Mechanistically, MYCi975 induced the DNA damage response and activated the cGAS-STING-IRF3 signaling pathway to increase CD8+ T cell-recruiting chemokines. Conclusions: Our findings suggested that targeting MYC might eliminate CSCs, prevent metastasis, and activate antitumor immunity to overcome cisplatin resistance in HNSCC.

Genome-wide identification of the C2H2 zinc finger gene family and expression analysis under salt stress in sweetpotato

Introduction

The higher plant transcription factor C2H2 zinc finger protein (C2H2-ZFP) is essential for plant growth, development, and stress response. There are limited studies on C2H2-ZFP genes in sweetpotato, despite a substantial number of C2H2-ZFP genes having been systematically found in plants.

Methods

In this work, 178 C2H2-ZFP genes were found in sweetpotato, distributed randomly on 15 chromosomes, and given new names according to where they were located. These members of the zinc finger gene family are separated into six branches, as shown by the phylogenetic tree. 24 tandem repeats of IbZFP genes and 46 fragment repeats were identified, and a homology study revealed that IbZFP genes linked more regions with wild relative species of sweetpotato as well as rhizome plants like potato and cassava. And we analyzed the expression patterns of IbZFP genes during the early development of sweetpotato storage roots (SRs) and salt stress using transcriptome data, and identified 44 IbZFP genes that exhibited differences in expression levels during the early expansion of sweetpotato SRs in different varieties, and 92 IbZFP genes that exhibited differences in expression levels under salt stress in salt tolerant and salt sensitive sweetpotato varieties. Additionally, we cloned six IbZFP genes in sweetpotato and analyzed their expression patterns in different tissues, their expression patterns under abiotic stress and hormone treatment, and subcellular localization.

Results and discussion

The results showed that the IbZFP genes had tissue specificity in sweetpotato and were induced to varying degrees by drought and salt stress. ABA and GA3 treatments also affected the expression of the IbZFP genes. We selected IbZFP105, which showed significant differences in expression levels under salt stress and ABA treatment, to be heterologously expressed in Arabidopsis thaliana. We found that IbZFP105 OE lines exhibited higher tolerance to salt stress and ABA stress. This indicates that IbZFP105 can enhance the salt tolerance of plants. These results systematically identified the evolution and expression patterns of members of the C2H2-ZFP gene family in sweetpotato, providing a theoretical basis for studying the role of IbZFP genes in the development of sweetpotato SRs and in resistance to stress.

A Novel LncRNA MASCC1 Regulates the Progression and Metastasis of Head and Neck Squamous Cell Carcinoma by Sponging miR-195

The altered expression of long noncoding RNAs (lncRNAs) is associated with human carcinogenesis. We performed a high-throughput analysis of lncRNA expression in strictly selected pairs of metastatic head and neck squamous cell carcinoma (HNSCC) and non-metastatic HNSCC samples. We identified a novel lncRNA, which was highly expressed in metastatic HNSCC, named Metastasis Associated Squamous Cell Carcinoma 1 (MASCC1), for further study. Using qRT-PCR, we further compared MASCC1 expression in 60 HNSCC samples. The results show that high expression of MASCC1 in patients with HNSCC was related to poor prognosis. In vitro, MASCC1 knockdown (KD) inhibited HNSCC proliferation, migration, invasion, and tumor sphere formation, while promoting apoptosis. In vivo, MASCC1 KD inhibited HNSCC growth and lymph node metastasis. Mechanistically, MASCC1 acted as a competing endogenous RNA (ceRNA) by binding to miR-195, subsequently regulating the expression of Cyclin D1, BCL-2, and YAP1. Moreover, miR-195 overexpression rescued the effects of MASCC1 on the biological behaviors of HNSCC. Taken together, our results suggest that MASCC1 is a novel oncogene that can predict the prognosis of patients with HNSCC and is a potential therapeutic target for HNSCC intervention.

Metabolomic responses based on transcriptome of the hepatopancreas in Exopalaemon carinicauda under carbonate alkalinity stress

High carbonate alkalinity is one of the major stress factors for survival of aquatic animals in saline-alkaline water. Exopalaemon carinicauda is a good model for studying the saline-alkaline adaption mechanism in crustacean because of its great adaptive capacity to alkalinity stress. In this study, non-targeted liquid chromatography-mass spectrometry (LC-MS) metabolomics analyses based on high-throughput RNA sequencing (RNA-Seq) were used to study the metabolomic responses of hepatopancreas in E. carinicauda at 12 h and 36 h after acute carbonate alkalinity stress. The results revealed that most of the significantly differential metabolites were related to the lipid metabolism. In particular, the sphingolipid metabolism was observed at 12 h, the glycerophospholipid metabolism was detected at 36 h, and the linoleic acid metabolic pathway was significantly enriched at both 12 h and 36 h. The combined transcriptome and metabolome analysis showed that energy consumption increased at 12 h, resulting in significant enrichment of AMPK signaling pathways, which contributed to maintain energy homeostasis. Subsequently, the hepatopancreas provided sufficient energy supply through cAMP signaling pathway and glycerophosphate metabolism to maintain normal metabolic function at 36 h. These findings might help to understand the molecular mechanisms of the E. carinicauda under carbonate alkalinity stress, thereby promote the research and development of saline-alkaline resistant shrimp.

Decreased syntaxin17 expression contributes to the pathogenesis of acute pancreatitis in murine models by impairing autophagic degradation

Acute pancreatitis (AP) is an inflammatory disease of the exocrine pancreas. Disruptions in organelle homeostasis, including macroautophagy/autophagy dysfunction and endoplasmic reticulum (ER) stress, have been implicated in human and rodent pancreatitis. Syntaxin 17 (STX17) belongs to the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) subfamily. The Qa-SNARE STX17 is an autophagosomal SNARE protein that interacts with SNAP29 (Qbc-SNARE) and the lysosomal SNARE VAMP8 (R-SNARE) to drive autophagosome-lysosome fusion. In this study, we investigated the role of STX17 in the pathogenesis of AP in male mice or rats induced by repeated intraperitoneal injections of cerulein. We showed that cerulein hyperstimulation induced AP in mouse and rat models, which was characterized by increased serum amylase and lipase activities, pancreatic edema, necrotic cell death and the infiltration of inflammatory cells, as well as markedly decreased pancreatic STX17 expression. A similar reduction in STX17 levels was observed in primary and AR42J pancreatic acinar cells treated with CCK (100 nM) in vitro. By analyzing autophagic flux, we found that the decrease in STX17 blocked autophagosome-lysosome fusion and autophagic degradation, as well as the activation of ER stress. Pancreas-specific STX17 knockdown using adenovirus-shSTX17 further exacerbated pancreatic edema, inflammatory cell infiltration and necrotic cell death after cerulein injection. These data demonstrate a critical role of STX17 in maintaining pancreatic homeostasis and provide new evidence that autophagy serves as a protective mechanism against AP.

Correction: A spiral microfluidic device for rapid sorting, trapping, and long-term live imaging of Caenorhabditis elegans embryos

[This corrects the article DOI: 10.1038/s41378-023-00485-4.].

Hyperon Polarization along the Beam Direction Relative to the Second and Third Harmonic Event Planes in Isobar Collisions at sqrt[s_{NN}]=200 GeV

The polarization of Λ and Λ[over ¯] hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sqrt[s_{NN}]=200  GeV. This is the first experimental evidence of the hyperon polarization by the triangular flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild p_{T} dependence. The azimuthal angle dependence of the polarization follows the vorticity pattern expected due to elliptic and triangular anisotropic flow, and qualitatively disagrees with most hydrodynamic model calculations based on thermal vorticity and shear induced contributions. The model results based on one of existing implementations of the shear contribution lead to a correct azimuthal angle dependence, but predict centrality and p_{T} dependence that still disagree with experimental measurements. Thus, our results provide stringent constraints on the thermal vorticity and shear-induced contributions to hyperon polarization. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.

Guided Wave Characteristic Research and Probabilistic Crack Evaluation in Complex Multi-Layer Stringer Splice Joint Structure

Multi-layer and multi-rivet connection structures are critical components in the structural integrity of a commercial aircraft, in which elements like skin, splice plate, strengthen patch, and stringer are fastened together layer by layer with multiple rows of rivets for assembling the fuselage and wings. Their non-detachability and inaccessibility pose significant challenges for assessing their health states. Guided wave-based structural health monitoring (SHM) has shown great potential for on-line damage monitoring in hidden structural elements. However, the multi-layer and multi-rivet features introduce complex boundary conditions for guided wave propagation and sensor layouts. Few studies have discussed the guided wave characteristic and damage diagnosis in multi-layer and multi-rivet connection structures. This paper comprehensively researches guided wave propagation characteristics in the multi-layer stringer splice joint (MLSSJ) structure through experiments and numerical simulations for the first time, consequently developing sensor layout rules for such complex structures. Moreover, a Gaussian process (GP)-based probabilistic mining diagnosis method with path-wave band features is proposed. Experiments on a batch of MLSSJ specimens are performed for validation, in which increasing crack lengths are set in each specimen. The results indicate the effectiveness of the proposed probabilistic evaluation method. The maximum root mean squared error of the GP quantitative diagnosis is 1.5 mm.

Research on the intelligent internet nursing model based on the child respiratory and asthma control test scale for asthma management of preschool children

BACKGROUND

Childhood asthma is a common respiratory ailment that significantly affects preschool children. Effective asthma management in this population is particularly challenging due to limited communication skills in children and the necessity for consistent involvement of a caregiver. With the rise of digital healthcare and the need for innovative interventions, Internet-based models can potentially offer relatively more efficient and patient-tailored care, especially in children.

AIM

To explore the impact of an intelligent Internet care model based on the child respiratory and asthma control test (TRACK) on asthma management in preschool children.

METHODS

The study group comprised preschoolers, aged 5 years or younger, that visited the hospital's pediatric outpatient and emergency departments between January 2021 and January 2022. Total of 200 children were evenly and randomly divided into the observation and control groups. The control group received standard treatment in accordance with the 2016 Guidelines for Pediatric Bronchial Asthma and the Global Initiative on Asthma. In addition to above treatment, the observation group was introduced to an intelligent internet nursing model, emphasizing the TRACK scale. Key measures monitored over a six-month period included the frequency of asthma attack, emergency visits, pulmonary function parameters (FEV1, FEV1/FVC, and PEF), monthly TRACK scores, and the SF-12 quality of life assessment. Post-intervention asthma control rates were assessed at six-month follow-up.

RESULTS

The observation group had fewer asthma attacks and emergency room visits than the control group (P < 0.05). After six months of treatment, the children in both groups had higher FEV1, FEV1/FVC, and PEF (P < 0.05). Statistically significant differences were observed between the two groups (P < 0.05). For six months, children in the observation group had a higher monthly TRACK score than those in the control group (P < 0.05). The PCS and MCSSF-12 quality of life scores were relatively higher than those before the nursing period (P < 0.05). Furthermore, the groups showed statistically significant differences (P < 0.05). The asthma control rate was higher in the observation group than in the control group (P < 0.05).

CONCLUSION

TRACK based Intelligent Internet nursing model may reduce asthma attacks and emergency visits in asthmatic children, improve lung function, quality of life, and the TRACK score and asthma control rate. The effect of nursing was significant, allowing for development of an asthma management model.

Vicinity Vision Transformer

Vision transformers have shown great success on numerous computer vision tasks. However, their central component, softmax attention, prohibits vision transformers from scaling up to high-resolution images, due to both the computational complexity and memory footprint being quadratic. Linear attention was introduced in natural language processing (NLP) which reorders the self-attention mechanism to mitigate a similar issue, but directly applying existing linear attention to vision may not lead to satisfactory results. We investigate this problem and point out that existing linear attention methods ignore an inductive bias in vision tasks, i.e., 2D locality. In this article, we propose Vicinity Attention, which is a type of linear attention that integrates 2D locality. Specifically, for each image patch, we adjust its attention weight based on its 2D Manhattan distance from its neighbouring patches. In this case, we achieve 2D locality in a linear complexity where the neighbouring image patches receive stronger attention than far away patches. In addition, we propose a novel Vicinity Attention Block that is comprised of Feature Reduction Attention (FRA) and Feature Preserving Connection (FPC) in order to address the computational bottleneck of linear attention approaches, including our Vicinity Attention, whose complexity grows quadratically with respect to the feature dimension. The Vicinity Attention Block computes attention in a compressed feature space with an extra skip connection to retrieve the original feature distribution. We experimentally validate that the block further reduces computation without degenerating the accuracy. Finally, to validate the proposed methods, we build a linear vision transformer backbone named Vicinity Vision Transformer (VVT). Targeting general vision tasks, we build VVT in a pyramid structure with progressively reduced sequence length. We perform extensive experiments on CIFAR-100, ImageNet-1 k, and ADE20 K datasets to validate the effectiveness of our method. Our method has a slower growth rate in terms of computational overhead than previous transformer-based and convolution-based networks when the input resolution increases. In particular, our approach achieves state-of-the-art image classification accuracy with 50% fewer parameters than previous approaches.

Paper-Based All-in-One Origami Nanobiosensor for Point-of-Care Detection of Cardiac Protein Markers in Whole Blood

Rapid and accurate diagnosis of cardiovascular diseases (CVDs) at the earliest stage is of paramount importance to improve the treatment outcomes and avoid irreversible damage to a patient's cardiovascular system. Microfluidic paper-based devices (μPADs) represent a promising platform for rapid CVD diagnosis at the point of care (POC). This paper presents an electrochemical μPAD (E-μPAD) with an all-in-one origami design for rapid and POC testing of cardiac protein markers in whole blood. Based on the label-free, electrochemical impedance spectroscopy (EIS) immunoassay, the E-μPAD integrates all essential components on a single chip, including three electrochemical cells, a plasma separation membrane, and a buffer absorption pad, enabling easy and streamlined operations for multiplexed detection of three cardiac protein markers [cardiac troponin I (cTnI), brain natriuretic peptide (BNP)-32, and D-Dimer] on a finger-prick whole blood sample within 46 min. Superior analytical performance is achieved through sensitive EIS measurement on carbon electrodes decorated with semiconductor zinc oxide nanowires (ZnO NWs). Using spiked human plasma samples, ultralow limits of detection (LODs) of E-μPAD are achieved at 4.6 pg/mL (190 fM) for cTnI, 1.2 pg/mL (40 fM) for BNP-32, and 146 pg/mL (730 fM) for D-Dimer. Real human blood samples spiked with purified proteins are also tested, and the device's analytical performance was proven to be comparable to commercial ELISA kits. The all-in-one E-μPAD will allow rapid and sensitive testing of cardiac protein markers through easy operations, which holds great potential for on-site screening of acute CVDs in nonlaboratory settings such as emergency rooms, doctor's offices, or patient homes.

Atherosclerotic plaque vulnerability quantification system for clinical and biological interpretability

Acute myocardial infarction dominates coronary artery disease mortality. Identifying bio-signatures for plaque destabilization and rupture is important for preventing the transition from coronary stability to instability and the occurrence of thrombosis events. This computational systems biology study enrolled 2,235 samples from 22 independent bulks cohorts and 14 samples from two single-cell cohorts. A machine-learning integrative program containing nine learners was developed to generate a warning classifier linked to atherosclerotic plaque vulnerability signature (APVS). The classifier displays the reliable performance and robustness for distinguishing ST-elevation myocardial infarction from chronic coronary syndrome at presentation, and revealed higher accuracy to 33 pathogenic biomarkers. We also developed an APVS-based quantification system (APVSLevel) for comprehensively quantifying atherosclerotic plaque vulnerability, empowering early-warning capabilities, and accurate assessment of atherosclerosis severity. It unraveled the multidimensional dysregulated mechanisms at high resolution. This study provides a potential tool for macro-level differential diagnosis and evaluation of subtle genetic pathological changes in atherosclerosis.

Electroencephalogram-Based Subject Matching Learning (ESML): A Deep Learning Framework on Electroencephalogram-Based Biometrics and Task Identification

An EEG signal (Electroencephalogram) is a bioelectric phenomenon reflecting human brain activities. In this paper, we propose a novel deep learning framework ESML (EEG-based Subject Matching Learning) using raw EEG signals to learn latent representations for EEG-based user identification and tack classification. ESML consists of two parts: one is the ESML1 model via an LSTM-based method for EEG-user linking, and one is the ESML2 model via a CNN-based method for EEG-task linking. The new model ESML is simple, but effective and efficient. It does not require any restrictions for EEG data collection on motions and thinking for users, and it does not need any EEG preprocessing operations, such as EEG denoising and feature extraction. The experiments were conducted on three public datasets and the results show that ESML performs the best and achieves significant performance improvement when compared to baseline methods (i.e., SVM, LDA, NN, DTS, Bayesian, AdaBoost and MLP). The ESML1 model provided the best precision at 96% with 109 users and the ESML2 model achieved 99% precision at 3-Class task classification. These experimental results provide direct evidence that EEG signals can be used for user identification and task classification.

N-acetyl-d-glucosamine-based oligosaccharides from chitin: Enzymatic production, characterization and biological activities

Chitin, the second most abundant biopolymer, possesses diverse applications in the food, agricultural, and pharmaceutical industries due to its functional properties. However, the potential applications of chitin are limited owing to its high crystallinity and low solubility. N-acetyl chitooligosaccharides and lacto-N-triose II, the two types of GlcNAc-based oligosaccharides, can be obtained from chitin by enzymatic methods. With their lower molecular weights and improved solubility, these two types of GlcNAc-based oligosaccharides display more various beneficial health effects when compared to chitin. Among their abilities, they have exhibited antioxidant, anti-inflammatory, anti-tumor, antimicrobial, and plant elicitor activities as well as immunomodulatory and prebiotic effects, which suggests they have the potential to be utilized as food additives, functional daily supplements, drug precursors, elicitors for plants, and prebiotics. This review comprehensively covers the enzymatic methods used for the two types of GlcNAc-based oligosaccharides production from chitin by chitinolytic enzymes. Moreover, current advances in the structural characterization and biological activities of these two types of GlcNAc-based oligosaccharides are summarized in the review. We also highlight current problems in the production of these oligosaccharides and trends in their development, aiming to offer some directions for producing functional oligosaccharides from chitin.

Systemic lupus erythematosus with high disease activity identification based on machine learning

OBJECTIVE

Clinical evaluation of systemic lupus erythematosus (SLE) disease activity is limited and inconsistent, and high disease activity significantly, seriously impacts on SLE patients. This study aims to generate a machine learning model to identify SLE patients with high disease activity.

METHOD

A total of 1014 SLE patients with low disease activity and 453 SLE patients with high disease activity were included. A total of 94 clinical, laboratory data and 17 meteorological indicators were collected. After data preprocessing, we use mutual information and multisurf to evaluate and select the importance of features. The selected features are used for machine learning modeling. Performance of the model is evaluated and verified by a series of binary classification indicators.

RESULTS

We screened out hematuria, proteinuria, pyuria, low complement, precipitation, sunlight and other features for model construction by integrated feature selection. After hyperparameter optimization, the LGB has the best performance (ROC: AUC = 0.930; PRC: AUC = 0.911, APS = 0.913; balance accuracy: 0.856), and the worst is the naive bayes (ROC: AUC = 0.849; PRC: AUC = 0.719, APS = 0.714; balance accuracy: 0.705). Finally, the selection of features has good consistency in the composite feature importance bar plot.

CONCLUSION

We identify SLE patients with high disease activity by a simple machine learning pipeline, especially the LGB model based on the characteristics of proteinuria, hematuria, pyuria and other feathers screened out by collective feature selection.

Alternative splicing of TaHSFA6e modulates heat shock protein-mediated translational regulation in response to heat stress in wheat

Heat stress greatly threatens crop production. Plants have evolved multiple adaptive mechanisms, including alternative splicing, that allow them to withstand this stress. However, how alternative splicing contributes to heat stress responses in wheat (Triticum aestivum) is unclear. We reveal that the heat shock transcription factor gene TaHSFA6e is alternatively spliced in response to heat stress. TaHSFA6e generates two major functional transcripts: TaHSFA6e-II and TaHSFA6e-III. TaHSFA6e-III enhances the transcriptional activity of three downstream heat shock protein 70 (TaHSP70) genes to a greater extent than does TaHSFA6e-II. Further investigation reveals that the enhanced transcriptional activity of TaHSFA6e-III is due to a 14-amino acid peptide at its C-terminus, which arises from alternative splicing and is predicted to form an amphipathic helix. Results show that knockout of TaHSFA6e or TaHSP70s increases heat sensitivity in wheat. Moreover, TaHSP70s are localized in stress granule following exposure to heat stress and are involved in regulating stress granule disassembly and translation re-initiation upon stress relief. Polysome profiling analysis confirms that the translational efficiency of stress granule stored mRNAs is lower at the recovery stage in Tahsp70s mutants than in the wild types. Our finding provides insight into the molecular mechanisms by which alternative splicing improves the thermotolerance in wheat.

LightNet: a novel lightweight convolutional network for brain tumor segmentation in healthcare

Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model. This work proposes a simple and effective feed-forward CNN, LightNet (Light Network). Based on multi-path and multi-level, it replaces traditional convolutional methods with light operations, which reduces network parameters and redundant feature maps. In the up-sampling stage, a light channel attention module is added to achieve richer multi-scale and spatial semantic feature information extraction of brain tumor. The performance of the network is evaluated in the Multimodal Brain Tumor Segmentation Challenge (BraTS 2015) dataset, and results are presented here alongside other high-performing CNNs. Results show comparable accuracy with other methods but with increased efficiency, segmentation performance, and reduced redundancy and computational complexity. The result is a high-performing network with a balance between efficiency and accuracy, allowing, for example, better energy performance on mobile devices.

Dendritic Cells Overcome Cre/Lox Induced Gene Deficiency by Siphoning Material From Neighboring Cells Using Intracellular Monitoring-a Novel Mechanism of Antigen Acquisition

Macrophages and dendritic cells (DCs) in peripheral tissue interact closely with their local microenvironment by scavenging protein and nucleic acids released by neighboring cells. Material transfer between cell types is necessary for pathogen detection and antigen presentation, but thought to be relatively limited in scale. Recent reports, however, demonstrate that the quantity of transferred material can be quite large when DCs are in direct contact with live cells. This observation may be problematic for conditional gene deletion models that assume gene products will remain in the cell they are produced in. Here, we investigate whether conditional gene deletions induced by the widely used Cre/Lox system can be overcome at the protein level in DCs. Of concern, using the human Langerin Cre mouse model, we find that epidermal Langerhans cells and CD11b+CD103+ mesenteric DCs can overcome gene deletion if the deleted gene is expressed by neighboring cells. Surprisingly, we also find that the mechanism of material transfer does not resemble known mechanisms of antigen uptake, is dependent on extra- and intracellular calcium, PI3K, and scavenger receptors, and mediates a majority of material transfer to DCs. We term this novel process intracellular monitoring, and find that it is specific to DCs, but occurs in all murine DC subsets tested, as well as in human DCs. Transferred material is successfully presented and cross presented on MHC-II and MHC-I, and occurs between allogeneic donor and acceptors cells-implicating this widespread and unique process in immunosurveillance and organ transplantation.

Characterization of a Glycoside Hydrolase Family 157 Endo-β-1,3-Glucanase That Displays Antifungal Activity against Phytopathogens

β-1,3-Glucan-degrading enzymes are widely used in fields such as food processing, plant protection, and breweries. In this work, we identified a glycoside hydrolase (GH) family 157 endo-β-1,3-glucanase (BsGlc157A) from Bacteroides sp. M27 and characterized its biochemical properties, structural model, and antifungal activity. Enzymological characterization indicated that BsGlc157A performs its optimal catalytic activity at pH 6.0 and 40 °C. BsGlc157A adopted the classic (β/α)₈ TIM-barrel structure. Two catalytic residues, the nucleophile (Glu215) and the proton donor (Glu123), were confirmed via structural modeling and site-directed mutagenesis. Moreover, BsGlc157A hydrolyzed curdlan into a series of oligosaccharides with polymerization degrees 2-5 and exhibited inhibitory effects on the hyphal growth of typical fruit pathogenic fungi (Monilinia fructicola, Alternaria alternata, and Colletotrichum gloeosporioides), thereby illustrating effective biocontrol activity. These results revealed the catalytic properties and the application potential of GH family 157 β-1,3-glucanase, thus providing valuable biochemistry information about the group of carbohydrate-active enzymes.

Adopting environment friendly technology model for green consumer adoption: is financial access important?

The objective of study is to test the role of access to finance between environment friendly technological adoption model for reshaping green consumer adoption pattern. For this, fuzzy-analytic approach is applied on Chinese model. The study findings highlighted that the environment friendly business initiatives must be maintained for longer durations to maintain environmental stability while time-honored techniques of controlling the environment evolve. In China, the technology acceptance model (TAM) in eco-friendly e-commerce increases consumer adoption goals for ecologically responsible items and creates new avenues for securing funding. The theoretical underpinnings of this study come from the fields of rational choice and planned behavior. Fifteen Chinese e-commerce professionals provided information for the research. Pythagorean fuzzy (PAHP) and FTOPSIS techniques are used to predict the results. The research results provide light on how TAM shapes the mindset, values, and goals of eco-conscious online shoppers in China, allowing them to get financial access while also helping to preserve the country's natural resources. Both theoretical and practical suggestions suggested directions to the key stakeholders to obtain financial access so that green consumer adoption may enhance for towards the adoption of environment friendly technology models.

Overexpression of 9-cis-Epoxycarotenoid Dioxygenase Gene, IbNCED1, Negatively Regulates Plant Height in Transgenic Sweet Potato

Plant height is one of the key agronomic traits for improving the yield of sweet potato. Phytohormones, especially gibberellins (GAs), are crucial to regulate plant height. The enzyme 9-cis-epoxycarotenoid dioxygenase (NCED) is the key enzyme for abscisic acid (ABA) biosynthesis signalling in higher plants. However, its role in regulating plant height has not been reported to date. Here, we cloned a new NCED gene, IbNCED1, from the sweet potato cultivar Jishu26. This gene encoded the 587-amino acid polypeptide containing an NCED superfamily domain. The expression level of IbNCED1 was highest in the stem and the old tissues in the in vitro-grown and field-grown Jishu26, respectively. The expression of IbNCED1 was induced by ABA and GA3. Overexpression of IbNCED1 promoted the accumulation of ABA and inhibited the content of active GA3 and plant height and affected the expression levels of genes involved in the GA metabolic pathway. Exogenous application of GA3 could rescue the dwarf phenotype. In conclusion, we suggest that IbNCED1 regulates plant height and development by controlling the ABA and GA signalling pathways in transgenic sweet potato.

Measurements of the Elliptic and Triangular Azimuthal Anisotropies in Central ^{3}He+Au, d+Au and p+Au Collisions at sqrt[s_{NN}]=200 GeV

The elliptic (v_{2}) and triangular (v_{3}) azimuthal anisotropy coefficients in central ^{3}He+Au, d+Au, and p+Au collisions at sqrt[s_{NN}]=200  GeV are measured as a function of transverse momentum (p_{T}) at midrapidity (|η|<0.9), via the azimuthal angular correlation between two particles both at |η|<0.9. While the v_{2}(p_{T}) values depend on the colliding systems, the v_{3}(p_{T}) values are system independent within the uncertainties, suggesting an influence on eccentricity from subnucleonic fluctuations in these small-sized systems. These results also provide stringent constraints for the hydrodynamic modeling of these systems.

Comparative Transcriptome Analysis Reveals the Effect of Lignin on Storage Roots Formation in Two Sweetpotato (Ipomoea batatas (L.) Lam.) Cultivars

Sweet potato (Ipomoea batatas (L.) Lam.) is one of the most important crops with high storage roots yield. The formation and expansion rate of storage root (SR) plays a crucial role in the production of sweet potato. Lignin affects the SR formation; however, the molecular mechanisms of lignin in SR development have been lacking. To reveal the problem, we performed transcriptome sequencing of SR harvested at 32, 46, and 67 days after planting (DAP) to analyze two sweet potato lines, Jishu25 and Jishu29, in which SR expansion of Jishu29 was early and had a higher yield. A total of 52,137 transcripts and 21,148 unigenes were obtained after corrected with Hiseq2500 sequencing. Through the comparative analysis, 9577 unigenes were found to be differently expressed in the different stages in two cultivars. In addition, phenotypic analysis of two cultivars, combined with analysis of GO, KEGG, and WGCNA showed the regulation of lignin synthesis and related transcription factors play a crucial role in the early expansion of SR. The four key genes swbp1, swpa7, IbERF061, and IbERF109 were proved as potential candidates for regulating lignin synthesis and SR expansion in sweet potato. The data from this study provides new insights into the molecular mechanisms underlying the impact of lignin synthesis on the formation and expansion of SR in sweet potatoes and proposes several candidate genes that may affect sweet potato yield.

Lupus nephritis or not? A simple and clinically friendly machine learning pipeline to help diagnosis of lupus nephritis

OBJECTIVE

Diagnosis of lupus nephritis (LN) is a complex process, which usually requires renal biopsy. We aim to establish a machine learning pipeline to help diagnosis of LN.

METHODS

A cohort of 681 systemic lupus erythematosus (SLE) patients without LN and 786 SLE patients with LN was established, and a total of 95 clinical, laboratory data and 17 meteorological indicators were collected. After tenfold cross-validation, the patients were divided into training set and test set. The features selected by collective feature selection method of mutual information (MI) and multisurf were used to construct the models of logistic regression, decision tree, random forest, naive Bayes, support vector machine (SVM), light gradient boosting (LGB), extreme gradient boosting (XGB), and artificial neural network (ANN), the models were compared and verified in post-analysis.

RESULTS

Collective feature selection method screens out antistreptolysin (ASO), retinol binding protein (RBP), lupus anticoagulant 1 (LA1), LA2, proteinuria and other features, and the hyperparameter optimized XGB (ROC: AUC = 0.995; PRC: AUC = 1.000, APS = 1.000; balance accuracy: 0.990) has the best performance, followed by LGB (ROC: AUC = 0.992; PRC: AUC = 0.997, APS = 0.977; balance accuracy: 0.957). The worst performance is naive Bayes model (ROC: AUC = 0.799; PRC: AUC = 0.822, APS = 0.823; balance accuracy: 0.693). In the composite feature importance bar plots, ASO, RF, Up/Ucr, and other features play important roles in LN.

CONCLUSION

We developed and validated a new and simple machine learning pathway for diagnosis of LN, especially the XGB model based on ASO, LA1, LA2, proteinuria, and other features screened out by collective feature selection.

A rare early-onset neonatal case of Birk-Barel syndrome presenting severe obstructive sleep apnea: a case report

Background

Birk-Barel syndrome, also known as KCNK9 imprinting syndrome, is a rare fertility disorder. And the main clinical manifestations include congenital hypotonic, craniofacial malformation, developmental delay, and intellectual disability. Generally, such patients could be diagnosed beyond the infant period. Moreover, the delayed diagnosis might lead to a poor prognosis of rehabilitation therapy. However, neonatal obstructive sleep apnea (OSA) was seldom reported in Birk-Barel syndrome. Here, we reported a severe neonatal OSA case induced by Birk-Barel syndrome, resulting in an early diagnosis with improved outcomes by integrative management.

Case presentation

The proband was a neonate presenting with recurrent severe OSA, with craniofacial deformity and congenital muscle hypotonia. Bronchoscopy examinations indicated a negative finding of pharyngeal and bronchus stenosis, while laryngomalacia had been observed. Whole exon sequencing demonstrated a c. 710C>A heterozygous variant resulting in a change of amino acid (p.A237D). This variant resulted in a change of amino acid sequence, affected protein features and changed splice site leading to a structural deformation in KCNK9 protein. This p.A237D variant also affected the crystal structure on the p.G129 site. Additionally, we used the mSCM tool to measure the free energy changes between wild-type and mutant protein, which indicated highly destabilizing (-2.622 kcal/mol).

Conclusion

This case report expands the understanding of Birk-Barel syndrome and indicates that OSA could serve as the on-set manifestation of Birk-Barel syndrome. This case emphasized genetic variants which were associated with severe neonatal OSA. Adequate WES assessment promotes early intervention and improves the prognosis of neurological disorders in young children.