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 TGFß. 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.

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.

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/ß-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.

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.

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.

Large-range two-dimensional sub-nano-misalignment sensing for lithography with a piecewise frequency regression network.

Circular gratings have been traditionally used as coarse alignment markers rather than fine ones for carrying out two-dimensional (2D) large-range misalignment measurements. This is primarily due to its complex phase distribution, which renders the extraction of information from high-precision alignment challenging using conventional frequency filtering methods. Along these lines, in this work, a novel, to the best of our knowledge, convolutional regression filter capable of achieving a 2D misalignment measurement with an impressive accuracy of 0.82 nm across a 3 mm range was introduced. Importantly, the proposed approach exhibited robustness against system errors and noise. It is anticipated that this strategy will provide an effective solution for similar misalignment sensing applications and hold promise for addressing future challenges in these fields.

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Mixing native broadleaved tree species is a widely used method for renovating Pinus massoniana plantations. Soil microbial necromass carbon and organic carbon fractions are important parameters for evaluating the impacts of tree species mixing and soil organic carbon (SOC) stability. However, their responses to the mixing and renovation of P. massoniana plantation has not been understood yet. Here, we selected a pure P. massoniana plantation (PP) and a mixed P. massoniana and Castanopsis hystrix plantation, with ages of 16 (MP16) and 38 years (MP38), respectively, as the research objects. We quantified soil physical and chemical properties, microbial necromass carbon content, and organic carbon components at different soil layers to reveal whether and how the introduction of C. hystrix into P. massoniana plantation affected soil microbial necromass carbon and organic carbon components. The results showed that the mixed P. massoniana and C. hystrix plantation significantly reduced fungal necromass carbon content and the ratio of fungal/bacterial necromass carbon in the 0-20 cm and 20-40 cm soil layers. There were no significant differences in microbial necromass carbon contents, bacterial necromass carbon contents, and their contributions to SOC among the different plantations. The contribution of fungal necromass carbon to SOC was higher than that of bacterial necromass carbon in all plantation types. The contribution of soil mineral-associated organic carbon (MAOC) to SOC was higher than that of occluded particulate organic carbon (oPOC) and light-free particulate organic carbon (fPOC) for all plantation types. Mixing the precious broadleaved tree species (i.e., C. hystrix) with coniferous species (P. massoniana) significantly increased MAOC content and the contribution of MAOC, oPOC, and fPOC to SOC in the 0-20 cm and 20-40 cm soil layers. The MAOC of MP38 was significantly higher than that of PP in all soil layers and the MAOC of MP38 stands were significantly higher than MP16 stands in the 20-40 cm, 40-60 cm, and 60-100 cm soil layers, indicating that hybridization enhanced SOC stability and that the SOC of MP38 stands were more stable than MP16 stands. SOC and total nitrogen contents were the main environmental factors driving the changes in soil microbial necromass carbon, while soil total nitrogen and organically complexed Fe-Al oxides were the primary factors affecting organic carbon fraction. Therefore, SOC stability can be enhanced by introducing native broadleaved species, such as C. hystrix, during the management of the P. massoniana plantation.

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.

Diabetic kidney disease as an independent predictor of long-term adverse outcomes in patients with coronary artery disease and diabetic mellitus.

Background: Diabetic kidney disease (DKD) had been proposed as a contributor in the pathogenesis of coronary artery disease (CAD). However, the relationship of DKD and the long-term adverse outcomes in patients with CAD after percutaneous coronary intervention (PCI) was still undiscovered. Methods: Approximately 892 patients with CAD enrolled from January 2012 to December 2016. The patients were divided into two groups, the DKD group (n = 341) and the None DKD group (n = 551). The primary outcome was major adverse cardiac events (MACE) after PCI. The average follow-up time was 1,897 ± 1,276 days. Results: Baseline data showed that some factors were significantly different between the two groups, including age, body mass index, gender (female), hypertension, smoking, stroke history, heart failure, duration of diabetic mellitus (DM), low-density lipoprotein cholesterol, urinary protein/creatinine ratio, serum creatinine, hemoglobin, platelet, antiplatelet, beta blocker, statin, antihypertensive drugs, and insulin (all p < 0.005). There were significant differences between the two groups in MACE, 40.3% vs. 52.2% (p = 0.001), and in cardiovascular death events and all-cause death events (5.6% vs. 20.5%, p < 0.001 and 4.4% vs. 13.5%, p < 0.001, respectively). In the DKD group, the risk of MACE was elevated to 141.9% [hazard ratio (HR) = 1.419, 95% confidence interval (CI): 1.164-1.730, p = 0.001] in the Cox univariable regression analyses; after adjusting co-variables, the Cox multivariable regression analyses demonstrated that DKD was an independent predictor for MACE (HR = 1.291, 95% CI: 1.027-1.624, p = 0.029) in patients with CAD after PCI, as well as in cardiovascular death events (HR = 2.148, 95% CI: 1.292-3.572, p = 0.003) and all-cause death events (HR = 2.229, 95% CI: 1.325-3.749, p = 0.003). Conclusion: This study suggests that DKD is an independent and novel predictor of long-term adverse outcomes in patients with CAD and DM who underwent PCI.

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.

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 ß- 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.

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.

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.

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.

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.

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.

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.

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 4­nitroquinoline 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.