Comparative effectiveness of chemotherapy in different histological types of pancreatic cancer: a PSM-based study using the SEER database.

This study aimed to compare the effectiveness of chemotherapy in different histological types of pancreatic cancer using data collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients who were diagnosed with pancreatic cancer between 2004 and 2015 were selected from the SEER database. Propensity score matching (PSM) was employed to minimize the selection bias. The Kaplan-Meier survival curves and the log-rank test were utilized to compare the overall survival (OS) and cancer-specific survival (CSS) among different groups. Of the 7,653 pancreatic cancer patients, both OS and CSS were higher in the chemotherapy group than those in the non-chemotherapy group (p < 0.001). After PSM, 2381 pairs were generated. The Kaplan-Meier survival curved indicated that both OS and CSS for pancreatic ductal adenocarcinoma (PDAC), pancreatic adenosquamous carcinoma (PASC), and pancreatic mucin-producing adenocarcinoma (PMPAC) (p < 0.001) in the chemotherapy group were superior to those in the non-chemotherapy group, while there was no significant difference in pancreatic mucinous adenocarcinoma (PMAC) (p = 0.2586). Compared with PASC and PMPAC, PDAC exhibited longer OS and CSS. The results of statistical analysis showed that PASC tumors were mainly poorly differentiated, and the majority of patients with PMPAC had distant metastasis. Chemotherapy could prolong pancreatic cancer patients' survival, especially for patients with advanced disease. PMPAC patients had a higher rate of metastasis, accompanying with the worse survival.

TIMP1 protects against blood-brain barrier disruption after subarachnoid haemorrhage by inhibiting ubiquitination of astrocytic ß1-integrin.

BACKGROUND: Astrocytes regulate blood-brain barrier (BBB) integrity, whereas subarachnoid haemorrhage (SAH) results in astrocyte dysregulation and BBB disruption. Here, we explored the involvement of tissue inhibitor of matrix metalloprotease-1 (TIMP1) in astrocyte-mediated BBB protection during SAH, along with its underlying mechanisms. METHODS: C57BL/6J mice were used to establish a model of SAH. The effects of TIMP1 on SAH outcomes were analysed by intraperitoneal injection of recombinant mouse TIMP1 protein (rm-TIMP1; 250 µg/kg). The roles of TIMP1 and its effector ß1-integrin on astrocytes were observed by in vivo transduction with astrocyte-targeted adeno-associated virus carrying TIMP1 overexpression plasmid or ß1-integrin RNAi. The molecular mechanisms underlying TIMP1 and ß1-integrin interactions were explored in primary cultured astrocytes stimulated with red blood cells (RBCs). RESULTS: TIMP1 was upregulated after SAH. Administration of rm-TIMP1 mitigated SAH-induced early brain injury (EBI) in male and female mice. TIMP1 was primarily expressed in astrocytes; its overexpression in astrocytes led to increased ß1-integrin expression in astrocytes, along with the preservation of astrocytic endfoot attachment to the endothelium and subsequent recovery of endothelial tight junctions. All of these effects were reversed by the knockdown of ß1-integrin in astrocytes. Molecular analysis showed that TIMP1 overexpression decreased the RBC-induced ubiquitination of ß1-integrin; this effect was partially achieved by inhibiting the interaction between ß1-integrin and the E3 ubiquitin ligase Trim21. CONCLUSION: TIMP1 inhibits the interaction between ß1-integrin and Trim21 in astrocytes, thereby rescuing the ubiquitination of astrocytic ß1-integrin. It subsequently restores interactions between astrocytic endfeet and the endothelium, as well as BBB integrity, eventually mitigating SAH-induced EBI.

Neutrophil-like pH-responsive pro-efferocytic nanoparticles improve neurological recovery by promoting erythrophagocytosis after intracerebral hemorrhage.

Rationale: Intracerebral hemorrhage (ICH) is a devastating cerebrovascular disease resulting from blood extravasating into the brain parenchyma. Escalation of erythrophagocytosis (a form of efferocytosis), avoiding the consequent release of the detrimental erythrocyte lysates, may be a promising target of ICH management. The ADAM17 inhibitor and liver X receptor (LXR) agonist could promote efficient efferocytosis and injury repair. Nevertheless, the poor bioavailability and restriction of the blood-brain barrier (BBB) hinder their application. Therefore, it is needed that biocompatible and smart nanoplatforms were designed and synthesized to realize effective therapy targeting erythrophagocytosis. Methods: We first assessed the synergistic effect of therapeutic GW280264X (an ADAM17 inhibitor) and desmosterol (an LXR agonist) on erythrophagocytosis in vitro. Then a pH-responsive neutrophil membrane-based nanoplatform (NPEOz) served as a carrier to accurately deliver therapeutic GW280264X and desmosterol to the damaged brain was prepared via co-extrusion. Afterwards, their pH-responsive performance was valued in vitro and targeting ability was assessed through fluorescence image in vivo. Finally, the pro-erythrophagocytic and anti-neuroinflammatory ability of the nanomedicine and related mechanisms were investigated. Results: After the synergistical effect of the above two drugs on erythrophagocytosis was confirmed, we successfully developed neutrophil-disguised pH-responsive nanoparticles to efficiently co-deliver them. The nanoparticles could responsively release therapeutic agents under acidic environments, and elicit favorable biocompatibility and ability of targeting injury sites. D&G@NPEOz nanoparticles enhanced erythrophagocytosis through inhibiting shedding of the efferocytotic receptors MERTK/AXL mediated by ADAM17 and accelerating ABCA-1/ABCG-1-mediated cholesterol efflux regulated by LXR respectively. In addition, the nano-formulation was able to modulate the inflammatory microenvironment by transforming efferocytes towards a therapeutic phenotype with reducing the release of proinflammatory cytokines while increasing the secretion of anti-inflammatory factors, and improve neurological function. Conclusions: This biomimetic nanomedicine is envisaged to offer an encouraging strategy to effectively promote hematoma and inflammation resolution, consequently alleviate ICH progression.

Paraneoplastic anti-GAD65 extralimbic encephalitis presented with epilepsy: A case report.

RATIONALE: Autoimmunity targeting glutamic acid decarboxylase 65 (GAD65) is associated with type 1 diabetes mellitus as well as various neurological diseases. In the central nervous system, GAD65 autoimmunity usually presents with limbic encephalitis, whereas extralimbic encephalitis (ELE) has only been reported in a few cases. Moreover, anti-GAD65 ELE in the paraneoplastic context has not yet been reported. PATIENT CONCERNS: A 60-year-old man presented with intermittent cough and sputum for 10 years, with no other diseases. The patient presented with recurrent seizures that were resistant to antiepileptic drugs (AEDs). Chest computed tomography and pathological results confirmed the diagnosis of small cell lung cancer. Paraneoplastic testing found a high level of GAD65 antibodies in his serum, and cerebrospinal fluid analysis revealed lymphocytic pleocytosis, indicating autoimmune encephalitis. Brain magnetic resonance imaging showed multifocal T2 fluid-attenuated inversion recovery hyperintensities in the extralimbic areas including the subcortex and deep white matter of the bilateral frontal lobe, parietal lobe, and insula lobes. DIAGNOSES: Finally, a diagnosis of anti-GAD65 autoimmune ELE with a paraneoplastic etiology from the small cell lung cancer was suspected. INTERVENTIONS: The patient refused any tumor-suppressive treatment or immunotherapy for potential side effects and only received AEDs levetiracetam, sodium valproate, and diazepam. OUTCOMES: The epilepsy of the patient was resistant to AEDs, and the patient died a week after discharge due to disease progression. LESSONS: Anti-GAD65 autoimmune encephalitis can be extralimbic, can present with isolated epilepsy, and extralimbic anti-GAD65 encephalitis can occur with an underlying malignancy.

Current knowledge of thrombocytopenia in sepsis and COVID-19.

Thrombocytopenia, characterized by a decrease in platelet count, is commonly observed in sepsis and COVID-19. In sepsis, thrombocytopenia can result from various mechanisms, including impaired platelet production in the bone marrow, accelerated platelet destruction due to increased inflammation, sequestration of platelets in the spleen, immune-mediated platelet destruction, or dysregulated host responses. Similarly, thrombocytopenia has been reported in COVID-19 patients, but the immune-related mechanisms underlying this association remain unclear. Notably, interventions targeting thrombocytopenia have shown potential for improving outcomes in both sepsis and COVID-19 patients. Understanding these mechanisms is crucial for developing effective treatments.

Src inhibition rescues FUNDC1-mediated neuronal mitophagy in ischaemic stroke.

BACKGROUND: Ischaemic stroke triggers neuronal mitophagy, while the involvement of mitophagy receptors in ischaemia/reperfusion (I/R) injury-induced neuronal mitophagy remain not fully elucidated. Here, we aimed to investigate the involvement of mitophagy receptor FUN14 domain-containing 1 (FUNDC1) and its modulation in neuronal mitophagy induced by I/R injury. METHODS: Wild-type and FUNDC1 knockout mice were generated to establish models of neuronal I/R injury, including transient middle cerebral artery occlusion (tMCAO) in vivo and oxygen glucose deprivation/reperfusion in vitro. Stroke outcomes of mice with two genotypes were assessed. Neuronal mitophagy was analysed both in vivo and in vitro. Activities of FUNDC1 and its regulator Src were evaluated. The impact of Src on FUNDC1-mediated mitophagy was assessed through administration of Src antagonist PP1. RESULTS: To our surprise, FUNDC1 knockout mice subjected to tMCAO showed stroke outcomes comparable to those of their wild-type littermates. Although neuronal mitophagy could be activated by I/R injury, FUNDC1 deletion did not disrupt neuronal mitophagy. Transient activation of FUNDC1, represented by dephosphorylation of Tyr18, was detected in the early stages (within 3 hours) of neuronal I/R injury; however, phosphorylated Tyr18 reappeared and even surpassed baseline levels in later stages (after 6 hours), accompanied by a decrease in FUNDC1-light chain 3 interactions. Spontaneous inactivation of FUNDC1 was associated with Src activation, represented by phosphorylation of Tyr416, which changed in parallel with the level of phosphorylated FUNDC1 (Tyr18) during neuronal I/R injury. Finally, FUNDC1-mediated mitophagy in neurons under I/R conditions can be rescued by pharmacological inhibition of Src. CONCLUSIONS: FUNDC1 is inactivated by Src during the later stage (after 6 hours) of neuronal I/R injury, and rescue of FUNDC1-mediated mitophagy may serve as a potential therapeutic strategy for treating ischaemic stroke.

Using machine learning to determine age over 16 based on development of third molar and periodontal ligament of second molar.

BACKGROUND: Having a reliable and feasible method to estimate whether an individual has reached 16 years of age would greatly benefit forensic analysis. The study of age using dental information has matured recently. In addition, machine learning (ML) is gradually being applied for dental age estimation. AIM: The purpose of this study was to evaluate the development of the third molar using the Demirjian method (Demirjian3M), measure the development index of the third molar (I3M) using the method by Cameriere, and assess the periodontal ligament development of the second molar (PL2M). This study aimed to predict whether Chinese adolescents have reached the age of criminal responsibility (16 years) by combining the above measurements with ML techniques. SUBJECTS & METHODS: A total of 665 Chinese adolescents aged between 12 and 20 years were recruited for this study. The development of the second and third molars was evaluated by taking orthopantomographs. ML algorithms, including random forests (RF), decision trees (DT), support vector machines (SVM), K-nearest neighbours (KNN), Bernoulli Naive Bayes (BNB), and logistic regression (LR), were used for training and testing to determine the dental age. This is the first study to combine ML with an evaluation of periodontal ligament and tooth development to predict whether individuals are over 16 years of age. RESULTS AND CONCLUSIONS: The study showed that SVM had the highest Bayesian posterior probability at 0.917 and a Youden index of 0.752. This finding provides an important reference for forensic identification, and the combination of traditional methods and ML is expected to improve the accuracy of age determination for this population, which is of substantial significance for criminal litigation.

M2 macrophage-derived extracellular vesicles augment immune evasion and development of colorectal cancer via a circRNA_CCDC66/microRNA-342-3p/metadherin axis.

The M2 macrophages are major components in the tumor microenvironment and are closely linked to immune suppression and tumor metastasis. This work focuses on how M2 macrophage-derived extracellular vesicles (EVs) affect colorectal cancer (CRC) progression. THP-1 monocytes were induced to differentiate to M0 or M2 macrophages, and the macrophage-derived EVs (M0-EVs and M2-EVs, respectively) were collected and identified. The M2-EVs stimulation augmented proliferation, mobility, and the in vivo tumorigenic activity of CRC cells. Circular RNA_CCDC66 (circ_CCDC66) was highly enriched in M2-EVs and could be delivered into CRC cells. The RNA pull-down and luciferase assays showed that circ_CCDC66 could competitively bind to microRNA (miR)-342-3p, therefore restoring the expression of metadherin (MTDH) mRNA, a target transcript of miR-342-3p. Suppression of circ_CCDC66 in the M2-EVs or specific knockdown of MTDH in CRC significantly blocked the growth and mobility of CRC cells. However, miR-342-3p inhibition restored the malignant phenotype of cancer cells. Moreover, the MTDH knockdown was found to increase the cytotoxicity of CD8+ T and reduce the protein level of the immune checkpoint PDL1 in CRC cells. In summary, this study reveals that the M2-EVs augment immune evasion and development of CRC by delivering circ_CCDC66 and restoring the MTDH level.

A Novel Chaotic Image Encryption Scheme Armed with Global Dynamic Selection.

Due to the equivalent keys revealed by a chosen-plaintext attack or a chosen-ciphertext attack, most of the existing chaotic image encryption schemes are demonstrated to be insecure. In order to improve security performance, some scholars have recently proposed the plaintext-related chaotic image encryption scheme. Although the equivalent effect of a one-time pad is achieved, an additional secure channel is required to transmit the hash values or other parameters related to the plaintext before the ciphertext can be decrypted at the receiving end. Its main drawback is that an absolutely secure channel is needed to transmit the information related to the plaintext, which is not feasible in practical applications. To further solve this problem, this paper proposes a chaotic image encryption scheme based on global dynamic selection of a multi-parallel structure. First, a chaotic sequence is employed to dynamically select DNA encoding rules. Secondly, the permutation with a multi-parallel structure is performed on the DNA-encoded matrix, and the DNA decoding rules are dynamically selected according to another chaotic sequence. Finally, the diffusion rules obtained by the ciphertext feedback mechanism are introduced to determine the dynamic diffusion. Compared with the existing local dynamic encryption schemes, the main advantage of this scheme is that it can realize global dynamic selection, so as to ensure that there is no equivalent key, and it can resist the chosen-ciphertext attack or chosen-plaintext attack and does not need an additional secure channel to transmit parameters related to plaintext, which is practical. A theoretical analysis and numerical experiments demonstrate the feasibility of the method.

Deep learning based dental implant failure prediction from periapical and panoramic films.

Background: Dental implant failure is a critical condition that can seriously compromise therapeutic efficacy. Insufficient bone volume, unfavorable bone quality, periodontal bone loss, and systemic conditions, including osteopenia/osteoporosis and diabetes mellitus, have been associated with implant failure. Early indicators of potential implant failure could help mitigate the risk of severe complications. This study aimed to develop an effective implant outcome prediction model using dental periapical and panoramic films. Methods: A total of 248 patients (89 with failed implants and 159 with successful implants) were examined. A total of 529 periapical images and 551 panoramic images were collected from the patients for a deep learning-based model. Based on radiographic peri-implant alveolar bone pattern, implant outcome was divided into three categories: implant failure with marginal bone loss, implant failure without marginal bone loss, and implant success. We extracted features using a deep convolutional neural network (CNN) and built a hybrid model to combine periapical and panoramic images. A comparison among three categories of receiver operating characteristic (ROC) curves was performed. The diagnostic accuracy, precision, recall and F1-score of the dataset were assessed. Results: Our model achieved an AUC (area under the ROC curve) of 0.972 for failure with marginal bone loss, 0.947 for failure without marginal bone loss and 0.975 for success. In all conditions, for periapical images alone, the diagnostic accuracy was 78.6%; the precision was 0.84, recall was 0.73, and F1-score was 0.75. For panoramic images alone, the diagnostic accuracy was 78.7%; the precision was 0.87, recall was 0.63, and F1-score was 0.66. Both periapical and panoramic images were used in our novel method, and the prediction accuracy was 87%. The precision was 0.85, recall was 0.88, and F1-score was 0.85. Conclusions: The deep learning model used features from periapical and panoramic images to effectively predict the occurrence of implant failure and might facilitate early clinical intervention for potential dental implant failures.

Metformin Regulates Gut Microbiota Abundance to Suppress M2 Skewing of Macrophages and Colorectal Tumorigenesis in Mice.

The correlation of imbalanced gut microbiota with the onset and progression of colorectal cancer (CRC) has become clear. This work investigates the effect of metformin on gut microbiota and genesis of CRC in mice. Human fecal samples were collected from healthy control (HC) donors and CRC patients. Compared to HC donors, CRC patients had reduced abundance of gut microbiota; however, they had increased abundance of detrimental Bacteroidetes. Mice were injected with azomethane (AOM) to induce colorectal tumorigenesis models. Treatment of CRC patients-sourced fecal microbiota promoted tumorigenesis, and it increased the expression of Ki67, ß-catenin, COX-2, and Cyclin D1 in mouse colon tissues. Further treatment of metformin blocked the colorectal tumorigenesis in mice. Fecal microbiota from the metformin-treated mice was collected, which showed decreased Bacteroidetes abundance and suppressed AOM-induced colorectal tumorigenesis in mice as well. Moreover, the metformin- modified microbiota promoted the M1 macrophage-related markers IL-6 and iNOS but suppressed the M2 macrophage-related markers IL-4R and Arg1 in mouse colon tissues. In conclusion, this study suggests that metformin-mediated gut microbiota alteration suppresses macrophage M2 polarization to block colorectal tumorigenesis.

Applicability of the London Atlas method in the East China population.

BACKGROUND: Dental age estimation is important for developmental assessment and individual identification. The London Atlas, a recently proposed method for dental age estimation, has been reported to perform satisfactorily in various populations. OBJECTIVE: In this study, we assessed the reproducibility, repeatability and applicability of the London Atlas method in the East China population and compared it with the Demirjian method. MATERIALS AND METHODS: We assessed panoramic radiographs of 835 pediatric patients ages 6.0-19.9 years using the London Atlas and the Demirjian method. We employed the intraclass correlation coefficient and Bland-Altman analysis to evaluate reproducibility and repeatability, respectively. We assessed the agreement between dental age and chronological age and calculated 95% and 80% prediction intervals for each dental age stage. Sensitivity, specificity and predictive values were calculated to assess the performance of both methods for identifying threshold ages. RESULTS: The London Atlas has better reproducibility and repeatability (intraclass correlation coefficients: 0.98 and 0.99; 95% limits of agreement: - 1.34 to 1.56 and - 1.22 to 0.88, respectively). Dental age estimated using the London Atlas was closer to chronological age in both genders (median absolute error = 0.58). The 95% prediction intervals for chronological age were wide (0.99 to 9.89 years). CONCLUSION: The London Atlas has excellent reproducibility and repeatability. Thus, it might offer an alternative method for developmental assessment. We observed considerable variation in dental development in the East China population, which needs further research.

Evaluation of a machine learning algorithms for predicting the dental age of adolescent based on different preprocessing methods.

Background: Machine learning (ML) algorithms play a key role in estimating dental age. In this study, three ML models were used for dental age estimation, based on different preprocessing methods. Aim: The seven mandibular teeth on the digital panorama were measured and evaluated according to the Cameriere and the Demirjian method, respectively. Correlation data were used for decision tree (DT), Bayesian ridge regression (BRR), k-nearest neighbors (KNN) models for dental age estimation. An accuracy comparison was made among different methods. Subjects and methods: We analyzed 748 orthopantomographs (392 males and 356 females) from eastern China between the age of 5 and 13 years in this retrospective study. Three models, DT, BRR, and KNN, were used to estimate the dental age. The data in ML is obtained according to the Cameriere method and the Demirjian method. Coefficient of determination (R2), mean error (ME), root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE), the above five metrics were used to evaluate the accuracy of age estimation. Results: Our experimental results showed that the prediction accuracy of dental age was affected by ML algorithms. MD, MAD, MSE, RMSE of the dental age predicted by ML were significantly decreased. Among all the methods, the KNN model based on the Cameriere method had the highest accuracy (ME = 0.015, MAE = 0.473, MSE = 0.340, RMSE = 0.583, R2 = 0.94). Conclusion: The results show that the prediction accuracy of dental age is influenced by ML algorithms and preprocessing method. The KNN model based on the Cameriere method was able to infer dental age more accurately in a clinical setting.

Role of complement C1q/C3-CR3 signaling in brain injury after experimental intracerebral hemorrhage and the effect of minocycline treatment.

Aim: The complement cascade is activated and may play an important pathophysiologic role in brain injury after experimental intracerebral hemorrhage (ICH). However, the exact mechanism of specific complement components has not been well studied. This study determined the role of complement C1q/C3-CR3 signaling in brain injury after ICH in mice. The effect of minocycline on C1q/C3-CR3 signaling-induced brain damage was also examined. Methods: There were three parts to the study. First, the natural time course of C1q and CR3 expression was determined within 7 days after ICH. Second, mice had an ICH with CR3 agonists, LA-1 or vehicle. Behavioral score, neuronal cell death, hematoma volume, and oxidative stress response were assessed at 7 days after ICH. Third, the effect of minocycline on C1q/C3-CR3 signaling and brain damage was examined. Results: There were increased numbers of C1q-positive and CR3-positive cells after ICH. Almost all perihematomal C1q-positive and CR3-positive cells were microglia/macrophages. CR3 agonist LA-1 aggravated neurological dysfunction, neuronal cell death, and oxidative stress response on day 7 after ICH, as well as enhancing the expression of the CD163/HO-1 pathway and accelerating hematoma resolution. Minocycline treatment exerted neuroprotective effects on brain injury following ICH, partly due to the inhibition of C1q/C3-CR3 signaling, and that could be reversed by LA-1. Conclusions: The complement C1q/C3-CR3 signaling is upregulated after ICH. The activation of C1q/C3-CR3 signaling by LA-1 aggravates brain injury following ICH. The neuroprotection of minocycline, at least partly, is involved with the repression of the C1q/C3-CR3 signaling pathway.

Semaphorin 6D regulate corralling, hematoma compaction and white matter injury in mice after intracerebral hemorrhage.

OBJECTIVES: The Semaphorin 6D (SEMA6D) shows important roles in cell guidance and lipid metabolism, but the effects and mechanisms of SEMA6D on tissue repair, white matter injury and the recovery of neurological function after intracerebral hemorrhage have not been well studied. MATERIALS AND METHODS: In this study, the autologous whole blood injection model of intracerebral hemorrhage was established in C57 male mice. SEMA6D knockout CRISPR utilized in the study. Assessments included neurological score evaluation and immunofluorescence. RESULTS: SEMA6D increased and peaked at 7d after intracerebral hemorrhage, and mainly located in neurons, microglia and astrocytes. SEMA6D knockout CRISPR aggravated neurological function and showed signs of poorer corralling and hematoma resolution, with more compartments of well-established physical barrier and more extensive GFAP positive astrocytic border. Furthermore, SEMA6D can prevent the decrease of NF-H in the peri-hematoma region, while SEMA6D knockout aggravated WMI. CONCLUSIONS: Our study suggested that SEMA6D could influence the recovery of neurological function by regulating the corralling, hematoma compaction and WMI in mice after intracerebral hemorrhage.

Comparative assessment of the Willems dental age estimation methods: a Chinese population-based radiographic study.

BACKGROUND: The comparison of the two Willems dental age estimation methods (gender-specific (Willems I) and non-gender-specific (Willems II)) has not been fully investigated. Here we aimed to explore the applicability of the Willems dental age estimation in an Eastern Chinese population, which may cast light on the field of dental age estimation. METHODS: A total of 1211 oral panoramic radiographs (582 boys and 629 girls) of the Chinese Han population aged 11-16 years old were collected. Dental ages (DAs) were calculated using the Willems method. Statistical significance was set at a p-value < 0.05. Age differences between chronological age (CA) and dental age were analyzed by paired t-tests and mean absolute error (MAE). RESULTS: The differences between CA and DA determined by the Willems I method were + 0.44 and + 0.09 years for boys and girls, respectively. When using the Willems II method, these differences were + 0.57 and - 0.09. The MAEs of the Willems I method between DA and CA were 0.95 and 1.00 years in boys and girls, respectively. For Willems II, MAEs were 1.02 and 1.00 years in boys and girls. CONCLUSIONS: This study showed that the Willems I method was more accurate than the Willems II method in the boys' group for predicting age from a whole scale. In comparison, Willems II is more competitive in the girls' group. Neither method may be satisfactory for 11-to-16-year-old teenagers in Eastern China.

A stratification model of hepatocellular carcinoma based on expression profiles of cells in the tumor microenvironment.

BACKGROUND: A malignancy of the liver, hepatocellular carcinoma (HCC) is among the most common and second-leading causes of cancer-related deaths worldwide. A reliable prognosis model for guidance in choosing HCC therapies has yet to be established. METHODS: A consensus clustering approach was used to determine the number of immune clusters in the Cancer Genome Atlas and Liver Cancer-RIKEN, JP (LIRI_JP) datasets. The differentially expressed genes (DEGs) among these groups were identified based on RNA sequencing data. Then, to identify hub genes among signature genes, a co-expression network was constructed. The prognostic value and clinical characteristics of the immune clusters were also explored. Finally, the potential key genes for the immune clusters were determined. RESULTS: After conducting survival and correlation analyses of the DEGs, three immune clusters (C1, C2, and C3) were identified. Patients in C2 showed the longest survival time with the greatest abundance of tumor microenvironment (TME) cell populations. MGene mutations in Ffibroblast growth factor-19 (FGF19) and catenin (cadherin-associated protein),ß1(CTNNB1) were mostly observed in C2 and C3, respectively. The signature genes of C1, C2, and C3 were primarily enriched in 5, 23, and 26 pathways, respectively. CONCLUSIONS: This study sought to construct an immune-stratification model for the prognosis of HCC by dividing the expression profiles of patients from public datasets into three clusters and discovering the unique molecular characteristics of each. This stratification model provides insights into the immune and clinical characteristics of HCC subtypes, which is beneficial for the prognosis of HCC.

High-resolution mapping of wildfire drivers in California based on machine learning.

Wildfires are important natural disturbances of ecosystems; however, they threaten the sustainability of ecosystems, climate and humans worldwide. It is vital to quantify and map the controlling drivers of wildfires for effective wildfire prediction and risk management. However, high-resolution mapping of wildfire drivers remains challenging. Here we established machine-learning (Random Forests) models using 23 climate and land surface variables as model inputs to reconstruct the spatial variability and seasonality of wildfire occurrence and extent in California. The importance of individual drivers was then quantified based on the Shapley value method. Thus, we provided spatially resolved maps of wildfire drivers at high resolutions up to 0.004° × 0.004°. The results indicated that precipitation and soil moisture are the major drivers dominating 37% of the total burnt area for large and extreme wildfires in summer and 63% in autumn, while elevation plays a major role for 15-58% of burnt areas in small wildfires in all seasons. Winds are also an important contributor to summer wildfires, accounting for 41% of large and extreme burnt areas. This study enhanced our knowledge of spatial variability of wildfire drivers across diverse landscapes in a fine-scale mapping, providing valuable perspectives and case studies for other regions of the world with frequently occurred wildfire.

High Entropy Alloy Electrocatalytic Electrode toward Alkaline Glycerol Valorization Coupling with Acidic Hydrogen Production.

Electrochemical glycerol oxidation reaction (GOR) is an attractive alternative anodic reaction to oxygen evolution reaction for a variety of electrolytic synthesis, thanks to the possibility of mass production of glycerol from biomass and the relative low thermodynamic potential of GOR. The development of high-activity cheap electrocatalysts toward GOR yet faces a daunting challenge. Herein, we experimentally prepare a new range of high entropy alloy (HEA) self-supported electrodes with uniform HEA nanoparticles grown on carbon cloth. The systematic electrochemical studies verify that the HEA-CoNiCuMnMo electrode exhibits attractive performance for GOR electrocatalysis with low overpotential and high selectivity toward formate products. The surface atomic configurations of HEA-CoNiCuMnMo are studied by a self-developed machine learning-based Monte Carlo simulation, which points out the catalytic active center to be Mo sites coordinated by Mn, Mo, and Ni. We further develop a hybrid alkali/acid flow electrolytic cell by pairing alkaline GOR with acidic hydrogen evolution reaction using the HEA-CoNiCuMnMo and the commercial RhIr/Ti as the anode and the cathode, respectively, which only requires an applied voltage of 0.55 V to reach an electrolytic current density of 10 mA cm-2 and maintains long-term electrolysis stability over 12 days continuous running at 50 mA cm-2 with Faraday efficiencies of over 99% for H2 in the cathode and 92% for formate production in the anode.

MT1G inhibits the growth and epithelial-mesenchymal transition of gastric cancer cells by regulating the PI3K/AKT signaling pathway.

Gastric carcinoma (GC) is a malignant tumor that has high mortality and morbidity worldwide. Although many efforts have been focused on the development and progression of GC, the underlying functional regulatory mechanism of GC needs more clarification. Metallothionein 1G (MT1G) is a member of the metallothionein family (MTs), and hypermethylation of MT1G occurred in a variety of cancers, including gastric cancer. However, the functional mechanism of MT1G in GC remains unclear. Here, we demonstrated that MT1G was down-regulated in GC tissues and cells. Overexpression of MT1G inhibited cell proliferation, foci formation and cell invasion, while knockdown of MT1G increased cell proliferation, foci formation and cell invasion. In addition, MT1G overexpression inhibited cell cycle progression and MT1G deficiency exerted opposite phenotype. p-AKT was negatively regulated by MT1G. In summary, our study reveals that MT1G exerts crucial role in regulating of cell proliferation and migration of gastric cancer, providing new insights for MT1G-related pathogenesis and a basis for developing new strategies for treatment of GC.