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Although immunotherapy and targeted treatments have dramatically improved the survival of melanoma patients, the intra- or intertumoral heterogeneity and drug resistance have hindered the further expansion of clinical benefits.The 96 combination frames constructed by ten machine learning algorithms identified a prognostic consensus signature based on 1002 melanoma samples from nine independent cohorts. Clinical features and 26 published signatures were employed to compare the predictive performance of our model.A machine learning-based prognostic signature (MLPS) with the highest average C-index was developed via 96 algorithm combinations. The MLPS has a stable and excellent predictive performance for overall survival, superior to common clinical traits and 26 collected signatures. The low MLPS group with a better prognosis had significantly enriched immune-related pathways, tending to be an immune-hot phenotype and possessing potential immunotherapeutic responses to anti-PD-1, anti-CTLA-4, and MAGE-A3. On the contrary, the high MLPS group with more complex genomic alterations and poorer prognoses is more sensitive to the BRAF inhibitor dabrafenib, confirmed in patients with BRAF mutations.MLPS could independently and stably predict the prognosis of melanoma, considered a promising biomarker to identify patients suitable for immunotherapy and those with BRAF mutations who would benefit from dabrafenib.

Background Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract which seriously endangers the health of human beings worldwide. Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of GC. This study aimed to investigate the impact of epigenetically regulated genes on the prognosis, immune microenvironment, and potential treatment of GC. Results Under the premise of verifying significant co-regulation of the aberrant frequencies of microRNA (miRNA) correlated (MIRcor) genes and DNA methylation-correlated (METcor) genes. Four GC molecular subtypes were identified and validated by comprehensive clustering of MIRcor and METcor GEPs in 1521 samples from five independent multicenter GC cohorts: cluster 1 was characterized by up-regulated cell proliferation and transformation pathways, with good prognosis outcomes, driven by mutations, and was sensitive to 5-fluorouracil and paclitaxel; cluster 2 performed moderate prognosis and benefited more from apatinib and cisplatin; cluster 3 was featured by an up-regulated ligand–receptor formation-related pathways, poor prognosis, an immunosuppression phenotype with low tumor purity, resistant to chemotherapy (e.g., 5-fluorouracil, paclitaxel, and cisplatin), and targeted therapy drug (apatinib) and sensitive to dasatinib; cluster 4 was characterized as an immune-activating phenotype, with advanced tumor stages, benefit more from immunotherapy and displayed worst prognosis. Conclusions According to the epigenetically regulated GEPs, we developed four robust GC molecular subtypes, which facilitated the understanding of the epigenetic mechanisms underlying GC heterogeneity, offering an optimized decision-making and surveillance platform for GC patients.

Patients who survive initial esophagogastric variceal bleeding (EVB) are at an increased risk of recurrent bleeding and death; however, a reliable predictive model is lacking. We aimed to develop a model for rebleeding prediction in patients with EVB after modified percutaneous transhepatic variceal embolization (PTVE) with cyanoacrylate.A total of 122 patients with EVB who underwent PTVE from January 2015 to November 2020 were enrolled. Multivariate logistic analyses were conducted to determine independent risk factors for nomogram construction. The discrimination, calibration, and clinical utility of the nomogram were compared with the Model for End-stage Liver Disease score (MELD) and the Child-Pugh model. Risk stratification was performed according to the nomogram.Rebleeding within 3 months of PTVE occurred in 32 patients (26.2%). Independent rebleeding indicators included prior history of endoscopic therapy, Child-Pugh score, partial splenic embolization, and creatinine level. The nomogram incorporating these four predictors achieved excellent calibration and discriminatory abilities, with a concordance index of 0.85, which was confirmed to be 0.83 through bootstrapping validation. The nomogram demonstrated superior discrimination and clinical applicability than the MELD and Child-Pugh models. As shown in the Kaplan-Meier curves, high-risk patients had a high probability of rebleeding (P ​ ​0.001).The creatinine-based nomogram had a superior ability to predict rebleeding after PTVE in patients with EVB. Risk stratification may help identify high-risk patients and lead to the earlier implementation of aggressive treatments and formulation of intensive follow-up plans.

Approximately 10%-15% of stage II and 25%-30% of stage III colorectal cancer (CRC) patients experience recurrence within five years after surgery, while existing taxonomies are inadequate for daily clinical application. Therefore, a more reliable classification approach with higher accuracy and prognostic potential is urgently required to stratify stage II/III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alternatively, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, 304 normal samples, 1,386 stage II/III CRC patients, and 2,557 ligand-receptor pairs were retrospectively retrieved. Grounded on perturbations in ligand-receptor interactions, four well-characterized and robust ligand-receptor-driven subtypes (LRDS1-4) were established in the discovery cohort and validated in meta-GEO cohort comprising nine independent cohorts. Specifically, LRDS1 was characterized by an immune-cold phenotype, with cell proliferation and differentiation-related functions and higher tumor purity; LRDS2 was endowed with matrix activation-related pathways and sensitive to fluorouracil-based chemotherapy; LRDS3 was distinguished by elevated metabolic activities and frequent 13q12.2 amplification; LRDS4 was an immune-hot subtype, driven by mutations, and exhibiting dismal prognosis with MEIS2 as the prognostic feature gene. Overall, our study developed four heterogeneous LRDS and shed novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective.

Background Leiomyomatosis peritonealis disseminata (LPD) is a non-metastatic, homologous, multicentric benign disorder characterized by small leiomyomas scattered over the peritoneum and omentum. It is a rare and benign disease with invasive potential. LPD mainly attacks women of childbearing age, but it has also been reported in postmenopausal women, men, and young children. Non-specific clinical and imaging findings of LPD lead to difficult diagnoses and treatment. Case presentation This study reports the case of a patient with recurrent LPD with endometriosis after multiple myomectomies and hysterectomy, who presented recurrent abdominal pain with progressive exacerbation. Imaging examinations showed irregular shadows in the pelvic cavity and multiple nodular changes in the peritoneum, which were considered malignant lesions. A solid mass sized 10 mm × 9 mm × 10 mm in the inferior pelvis and nodules scattered over the surface of pelvic and abdominal organs and the peritoneum were detected during the surgery. The patient was treated with cytoreductive surgery (CRS), peritonectomy, ovarian ablation, and hyperthermic intraperitoneal chemotherapy (HIPEC). The surgery was challenging, and the intraoperative bleeding reached 900 ml. However, the patient recovered well and achieved a tumor-free survival of 13 months. Conclusions It was concluded that a combination of CRS, peritonectomy, ovarian ablation, and HIPEC is an effective therapeutic strategy for recurrent LPD.

The transformation of waste plastics into value-added aromatics could incentivize better waste plastic management. The reported studies had low selectivity for monocyclic aromatics because more polycyclic aromatic hydrocarbons and carbon residues were generated. The effects of temperature, pressure, and catalyst on monocyclic aromatic selectivity were explored using a central composite design (CCD) followed by the response surface methodology (RSM) at a high ramp rate of 15 °C/min. The liquid product yield and selectivity to aromatic hydrocarbons were enhanced by regulating the acidic properties of the catalyst and processing parameters. The proportion of monocyclic aromatics in the liquid product was up to 90%, and the yield of monocyclic aromatics based on the reactant mass was 51% at the optimized condition. The carbon deposit production was low (only approximately 1%), which allowed higher liquid yields. In addition, the coupling mechanism of multiple factors on the depolymerization/aromatization reactions was proposed. This conversion of polyethylene into high-yield monocyclic aromatics provides a viable plastic recycling approach.

Deep Learning (DL) has important applications to both commercial and military communications, such as software-defined radio, cognitive radio and spectrum surveillance. While DL has been intensively studied for modulation recognition, there are very few investigations for blind identification of Space-Time Block Codes (STBCs). This paper proposes a Residual Network (RN)-based model for identifying 6 kinds of STBC signals with a single receiving antenna, including the same length of coding matrix. In our work, we use the frequency-domain correlation function of a single time delay as the training data of DL model. Then, we explore the suitable RN structure for blind identification of STBCs. Finally, we compare the RN model with convolutional neural network and traditional method, and test the performance of RN model. Simulation results show that our RN-based model provides good performance with low sensitivity to decay of the dataset, such as sample length and data size. At the same time, better identification accuracy can be achieved under the condition of different modulation types and channel fading parameters at low Signal to Noise Ratio (SNR).

Pharmacogenomics is crucial for individualized drug therapy and plays an increasingly vital role in precision medicine decision-making. However, pharmacogenomics-based molecular subtypes and their potential clinical significance remain primarily unexplored in lung adenocarcinoma (LUAD).A total of 2065 samples were recruited from eight independent cohorts. Pharmacogenomics data were generated from the profiling of relative inhibition simultaneously in mixtures (PRISM) and the genomics of drug sensitivity in cancer (GDSC) databases. Multiple bioinformatics approaches were performed to identify pharmacogenomics-based subtypes and find subtype-specific properties.Three reproducible molecular subtypes were found, which were independent prognostic factors and highly associated with stage, survival status, and accepted molecular subtypes. Pharmacogenomics-based subtypes had distinct molecular characteristics: S-Ⅰ was inflammatory, proliferative, and immune-evasion; S-Ⅱ was proliferative and genetics-driven; S-III was metabolic and methylation-driven. Finally, our study provided subtype-guided personalized treatment strategies: Immune checkpoint blockers (ICBs), doxorubicin, tipifarnib, AZ628, and AZD6244 were for S-Ⅰ; Cisplatin, camptothecin, roscovitine, and A.443654 were for S-Ⅱ; Docetaxel, paclitaxel, vinorelbine, and BIBW2992 were for S-III.We provided a novel molecular classification strategy and revealed three pharmacogenomics-based subtypes for LUAD patients, which uncovered potential subtype-related and patient-specific therapeutic strategies.

We use a proprietary automatic Al–Mg alloy–water reaction test apparatus to compare the hydrogen evolution profiles of Al-xMg (x = 10%,20%) with different particle sizes, characterize the waste Al-xMg alloy dust particles before and after reaction through SEM, EDS, and XRD, and present a three-stage four-step hydrogen evolution model of Al-xMg (x ≤ 35%) alloy dust particles. It is discovered that the reaction of the Al–Mg alloy in water is a hydrogen evolution–adsorption–slow diffusion process. The particular β-Al3Mg2 in Al-xMg (x ≤ 35%) will adsorb the resulting hydrogen to form MgH+ and adhere to the surface of the particles. As the Mg content in the alloy increases, the hydrogen evolution reduces. The entire process lasts around 5–6 h, with maximum hydrogen conversion rate of 54% (Al–10%Mg, d (50) = 12 μm, α = 0.544). Our hydrogen evolution model provides very useful theoretical references for avoiding hydrogen explosion in Al–Mg alloy manufacturing facilities.

Cancer drug resistance represents the main obstacle in cancer treatment. Drug-resistant cancers exhibit complex molecular mechanisms to hit back therapy under pharmacological pressure. As a reversible epigenetic modification, N6-methyladenosine (m6A) RNA modification was regarded to be the most common epigenetic RNA modification. RNA methyltransferases (writers), demethylases (erasers), and m6A-binding proteins (readers) are frequently disordered in several tumors, thus regulating the expression of oncoproteins, enhancing tumorigenesis, cancer proliferation, development, and metastasis. The review elucidated the underlying role of m6A in therapy resistance. Alteration of the m6A modification affected drug efficacy by restructuring multidrug efflux transporters, drug-metabolizing enzymes, and anticancer drug targets. Furthermore, the variation resulted in resistance by regulating DNA damage repair, downstream adaptive response (apoptosis, autophagy, and oncogenic bypass signaling), cell stemness, tumor immune microenvironment, and exosomal non-coding RNA. It is highlighted that several small molecules targeting m6A regulators have shown significant potential for overcoming drug resistance in different cancer categories. Further inhibitors and activators of RNA m6A-modified proteins are expected to provide novel anticancer drugs, delivering the therapeutic potential for addressing the challenge of resistance in clinical resistance.

Various CRISPR/Cas12a-based biosensing systems have been developed in the past few years, and most of these systems used Taqman probes to report signals through fluorescence resonance energy transfer (FRET). In this study, we explored chemiluminescence resonance energy transfer (CRET) as the readout mode for CRISPR/Cas12a-based biosensing. The chemiluminescence (CL) reaction of bis(2,4,6-trichlorophenyl) oxalate (TCPO) and H

Two-photon absorption (2PA) spectra of liquid cyclohexane and hexanes are reported for the energy range 6.4-8.5 eV (177-145 nm), providing detailed information about their electronic structures in bulk liquid. Using a broadband pump-probe fashion, we measured the continuous 2PA spectra by simultaneous absorption of a 266 nm (4.6 eV) pump photon and one UV-vis probe photon from the white-light continuum (1.8-3.9 eV). Theoretical one-photon absorption (1PA) and 2PA cross sections of isolated gas phase molecules are computed by the equation of motion coupled-cluster method with single and double substitutions (EOM-CCSD) to substantiate the assignment of the experimental spectra, and the natural transition orbital (NTO) analysis provides visualization of the participating orbitals in a transition. Our analysis suggests that upon solvation transitions at the lowest excitation energy involving promotion of electron to the 3s Rydberg orbitals are blue-shifted (∼0.55 eV for cyclohexane and ∼0.18 eV for hexanes) to a greater extent as compared to those involving other Rydberg orbitals, which is similar to the behavior observed for water and alcohols. All other transitions experience negligible (cyclohexane) or minor red-shift by ∼0.15-0.2 eV (hexane) upon solvation. In both alkanes, the spectra are entirely dominated by Rydberg transitions: the most intense bands in 1PA and 2PA spectra are due to the excitation of electrons to the Rydberg "p" and "d" type orbitals, respectively, although one transition terminating in the 3s Rydberg has significant 2PA strength. This work demonstrates that the gas phase electronic transition properties in alkanes are not significantly altered upon solvation. In addition, electronic structure calculations using an isolated-molecule framework appear to provide a reasonable starting point for a semiquantitative picture for spectral assignment and also to analyze the solvatochromic shifts for liquid phase absorption spectra.

BACKGROUND: Failed mitral bioprosthesis has conventionally been treated with redo surgical mitral valve replacement (SMVR). Transcatheter mitral valve-in-valve implantation (TM-VIVI) is emerging as an alternative to SMVR in high-risk patients. We report our experience with transapical TM-VIVI using the J-Valve system. METHODS: From May 2020 to January 2021, 21 patients with a failed mitral bioprosthesis underwent transapical TM-VIVI without concomitant procedures at Guangdong Provincial People’s hospital. The mean age was 74.62 years. All patients were heavily symptomatic with severe mitral regurgitation and increased trans-prosthetic gradient. The Society of Thoracic Surgeons predicted risk of mortality (STS PROM) and European System for Cardiac Operative Risk Evaluation II (EuroScore II) scores were used and predicted high mortality (STS PROM, 12.91%±9.94%; EuroScore II, 12.04%±10.5%). All the procedures were performed in a hybrid room. RESULTS: The success rate was 100% with no conversion to median sternotomy and no intraprocedural death. The mean ventilation time and intensive care unit (ICU) stay were 25±21.44 minutes and 4.14±7.08 days, respectively. No major postoperative complications were observed, except 1 patient suffered pneumonia and required tracheostomy. All patients recovered well. Postoperative echocardiography revealed excellent hemodynamics with no residual mitral regurgitation in 19 patients and mild regurgitation in 2 patients. In a subgroup analysis, no significant differences among procedural and postoperative outcomes were detected in patients with previous aortic-mitral double valve replacement (DVR) compared to other patients. CONCLUSIONS: Our results demonstrate the safety and feasibility of transapical TM-VIVI using the J-Valve system, even in patients following DVR.

To accurately predict the prognosis and further improve the clinical outcomes of bladder cancer (BLCA), we leveraged large-scale data to develop and validate a robust signature consisting of small gene sets. Ten machine-learning algorithms were enrolled and subsequently transformed into 76 combinations, which were further performed on eight independent cohorts (n = 1218). We ultimately determined a consensus artificial intelligence-derived gene signature (AIGS) with the best performance among 76 model types. In this model, patients with high AIGS showed a higher risk of mortality, recurrence, and disease progression. AIGS is not only independent of traditional clinical traits [(e.g., American Joint Committee on Cancer (AJCC) stage)] and molecular features (e.g., TP53 mutation) but also demonstrated superior performance to these variables. Comparisons with 58 published signatures also indicated that AIGS possessed the best performance. Additionally, the combination of AIGS and AJCC stage could achieve better performance. Patients with low AIGS scores were sensitive to immunotherapy, whereas patients with high AIGS scores might benefit from seven potential therapeutics: BRD-K45681478, 1S,3R-RSL-3, RITA, U-0126, temsirolimus, MRS-1220, and LY2784544. Additionally, some mutations (TP53 and RB1), copy number variations (7p11.2), and a methylation-driven target were characterized by AIGS-related multi-omics alterations. Overall, AIGS provides an attractive platform to optimize decision-making and surveillance protocol for individual BLCA patients.

Using the DNA activator of Cas to label the secondary antibody of traditional ELISA, the CRISPR/Cas12a-based fluorescence immunoassay was presented. The sensing strategy ingeniously combines the efficient signal generation of the CRISPR/Cas12a system with antigen-antibody-specific recognition. This work provides an alternative strategy to expand the application of the CRISPR/Cas system for the detection of non-nucleic acid targets.

Cancer drug resistance represents the main obstacle in cancer treatment. Drug-resistant cancers exhibit complex molecular mechanisms to hit back therapy under pharmacological pressure. As a reversible epigenetic modification, N

This study applies intelligent ubiquitous network technology to the field of education and leads to the benign development of intelligent education and teachers’ professional informatization. This study proposes the concepts of eco-classroom, smart education, and flipped classroom and conducts practical research on the teaching effectiveness of the three elements of eco-classroom: teachers, students, and environment. Because of the problems of inaccurate positioning of data fusion, single application function, and difficulty of automatic correlation of data stored in multiple networks in the intelligent ubiquitous sensing environment, the method and path of multidimensional data fusion governance are proposed and put into practice to achieve good results in practice. Based on the characteristics of ubiquitous learning in time, space, and dimensional changes between reality and time, combined with the law of knotted learning and Bloom’s mastery learning theory, the five components of the teaching model and their correlations are sorted out, and the teaching model of higher education under the vision of ubiquitous learning is constructed to achieve the goal of students’ mastering knowledge and skills and promote the innovation of the education and teaching model. The model interaction site is created, a ranking system is developed, and professional standards for the new era are developed to help educators reconstruct their professional competencies. The concept and characteristics of knowledge sharing in the ubiquitous network environment are analyzed, the knowledge sharing model in the ubiquitous network learning environment is constructed, the status of knowledge sharing practice in the ubiquitous network environment is studied, and suggestions for improvement are put forward to optimize knowledge sharing in the ubiquitous network learning environment.

Circulating tumor DNA (ctDNA) sequencing holds considerable promise for early diagnosis and detection of surveillance and minimal residual disease. Blood ctDNA monitors specific cancers by detecting the alterations found in cancer cells, such as apoptosis and necrosis. Due to the short half-life, ctDNA reflects the actual burden of other treatments on tumors. In addition, ctDNA might be preferable to monitor tumor development and treatment compared with invasive tissue biopsy. ctDNA-based liquid biopsy brings remarkable strength to targeted therapy and precision medicine. Notably, multiple ctDNA analysis platforms have been broadly applied in clinical immunotherapy. Through targeted sequencing, early variations in ctDNA could predict response to immune checkpoint inhibitor (ICI). Several studies have demonstrated a correlation between ctDNA kinetics and anti-PD1 antibodies. The need for further research and development remains, although this biomarker holds significant prospects for early cancer detection. This review focuses on describing the basis of ctDNA and its current utilities in oncology and immunotherapy, either for clinical management or early detection, highlighting its advantages and inherent limitations.

BackgroundThe unknown etiology of sarcoidosis with variable clinical features leads to delayed diagnosis and limited therapeutic strategies. Hence, exploring the latent mechanisms and constructing an accessible and reliable diagnostic model of sarcoidosis is vital for innovative therapeutic approaches to improve prognosis.MethodsThis retrospective study analyzed transcriptomes from 11 independent sarcoidosis cohorts, comprising 313 patients and 400 healthy controls. The weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were performed to identify molecular biomarkers. Machine learning was employed to fit a diagnostic model. The potential pathogenesis and immune landscape were detected by bioinformatics tools.ResultsA 10-gene signature SARDS consisting of GBP1, LEF1, IFIT3, LRRN3, IFI44, LHFPL2, RTP4, CD27, EPHX2, and CXCL10 was further constructed in the training cohorts by the LASSO algorithm, which performed well in the four independent cohorts with the splendid AUCs ranging from 0.938 to 1.000. The findings were validated in seven independent publicly available gene expression datasets retrieved from whole blood, PBMC, alveolar lavage fluid cells, and lung tissue samples from patients with outstanding AUCs ranging from 0.728 to 0.972. Transcriptional signatures associated with sarcoidosis revealed a potential role of immune response in the development of the disease through bioinformatics analysis.ConclusionsOur study identified and validated molecular biomarkers for the diagnosis of sarcoidosis and constructed the diagnostic model SARDS to improve the accuracy of early diagnosis of the disease.

2'-Deoxy-5-formylcytidine (5fdCyd), a naturally occurring nucleoside found in mammalian DNA and mitochondrial RNA, exhibits important epigenetic functionality in biological processes. Because it efficiently generates triplet excited states, it is an endogenous photosensitizer capable of damaging DNA, but the intersystem crossing (ISC) mechanism responsible for ultrafast triplet state generation is poorly understood. In this study, time-resolved mid-IR spectroscopy and quantum mechanical calculations reveal the distinct ultrafast ISC mechanisms of 5fdCyd in water versus acetonitrile. Our experiment indicates that in water, ISC to triplet states occurs within 1 ps after 285 nm excitation. PCM-TD-DFT computations suggest that this ultrafast ISC is mediated by a singlet state with significant cytosine-to-formyl charge-transfer (CT) character. In contrast, ISC in acetonitrile proceeds via a dark 1 nπ* state with a lifetime of ∼3 ps. CT-induced ISC is not favored in acetonitrile because reaching the minimum of the gateway CT state is hampered by intramolecular hydrogen bonding, which enforces planarity between the aldehyde group and the aromatic group. Our study provides a comprehensive picture of the non-radiative decay of 5fdCyd in solution and new insights into the factors governing ISC in biomolecules. We propose that the intramolecular CT state observed here is a key to the excited-state dynamics of epigenetic nucleosides with modified exocyclic functional groups, paving the way to study their effects in DNA strands.

PurposeThe study aimed to construct and evaluate a CT-Based radiomics model for noninvasive detecting perineural invasion (PNI) of perihilar cholangiocarcinoma (pCCA) preoperatively.Materials and MethodsFrom February 2012 to October 2021, a total of 161 patients with pCCA who underwent resection were retrospectively enrolled in this study. Patients were allocated into the training cohort and the validation cohort according to the diagnostic time. Venous phase images of contrast-enhanced CT were used for radiomics analysis. The intraclass correlation efficient (ICC), the correlation analysis, and the least absolute shrinkage and selection operator (LASSO) regression were applied to select radiomics features and built radiomics signature. Logistic regression analyses were performed to establish a clinical model, a radiomics model, and a combined model. The performance of the predictive models was measured by area under the receiver operating characteristic curve (AUC), and pairwise ROC comparisons between models were tested using the Delong method. Finally, the model with the best performance was presented as a nomogram, and its calibration and clinical usefulness were assessed.ResultsFinally, 15 radiomics features were selected to build a radiomics signature, and three models were developed through logistic regression. In the training cohort, the combined model showed a higher predictive capability (AUC = 0.950) than the radiomics model and the clinical model (AUC: radiomics = 0.914, clinical = 0.756). However, in the validation cohort, the AUC of the radiomics model (AUC = 0.885) was significantly higher than the other two models (AUC: combined = 0.791, clinical = 0.567). After comprehensive consideration, the radiomics model was chosen to develop the nomogram. The calibration curve and decision curve analysis (DCA) suggested that the nomogram had a good consistency and clinical utility.ConclusionWe developed a CT-based radiomics model with good performance to noninvasively predict PNI of pCCA preoperatively.

BackgroundMolecular biomarkers are widely used for disease diagnosis and exploration of pathogenesis. Pulmonary arterial hypertension (PAH) is a rapidly progressive cardiopulmonary disease with delayed diagnosis. Studies were limited regarding molecular biomarkers correlated with PAH from a broad perspective.MethodsTwo independent microarray cohorts comprising 73 PAH samples and 36 normal samples were enrolled in this study. The weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules associated with PAH. The LASSO algorithm was employed to fit a diagnostic model. The latent biology mechanisms and immune landscape were further revealed via bioinformatics tools.ResultsThe WGCNA approach ultimately identified two key modules significantly associated with PAH. For genes within the two models, differential expression analysis between PAH and normal samples further determined nine key genes. With the expression profiles of these nine genes, we initially developed a PAH diagnostic signature (PDS) consisting of LRRN4, PI15, BICC1, PDE1A, TSHZ2, HMCN1, COL14A1, CCDC80, and ABCB1 in GSE117261 and then validated this signature in GSE113439. The ROC analysis demonstrated outstanding AUCs with 0.948 and 0.945 in two cohorts, respectively. Besides, patients with high PDS scores enriched plenty of Th17 cells and neutrophils, while patients with low PDS scores were dramatically related to mast cells and B cells.ConclusionOur study established a robust and promising signature PDS for diagnosing PAH, with key genes, novel pathways, and immune landscape offering new perspectives for exploring the molecular mechanisms and potential therapeutic targets of PAH.

In this study, a combined process of bio-inspired modification and magnetic treatment is presented for the preparation of a polydopamine (Pdop)-modified graphene (Pdop-G)-based adsorbent which incorporates ultra-small, active Fe3O4 nanoparticles (with an average size of 6.5 nm). Not only can the nanoparticles impart superparamagnetism to the modified graphene adsorbent but also enhance the adsorption performance. The ultra-small size of Fe3O4 nanoparticles allows the exposure of a high proportion of low-coordinated sites such as corners and edges. Additional active sites can thus be provided to bind methylene blue molecules, in addition to the active Pdop-G surface with catechol and amine groups which induce hydrogen bonding, electrostatic attraction, and π-π stacking interactions. The Pdop interface wraps graphene and immobilizes Fe3O4, endowing the magnetic Pdop-G (MPG) with high adsorption capacity, easy recyclability, and excellent reusability for the organic pollutant removal. In stark contrast, the counterpart without the interfacial Pdop layer suffers from severe Fe3O4 aggregation, causing its adsorption performance inferior to that of MPG. The MPG-based adsorption obeys the pseudo-second-order kinetics, and the intraparticle diffusion model also indicates the complex adsorption pathway, including the external and intraparticle mass transfer. The Langmuir isotherm can better fit the experimental data than the Freundlich isotherm, with the theoretical maximum adsorption capacities estimated to be 131.6, 140.3, and 152.0 mg/g at 30, 40, and 50 °C, respectively. The adsorption is endothermic and spontaneous, along with an increase in the randomness at the solid-solution interface. The separation factor (RL) reveals the favorable adsorption process with MPG. The superparamagnetism imparted via the Fe3O4 composition makes MPG easily recyclable. Furthermore, the removal rate can be maintained at about 90% after 5 runs of repeated usage of MPG. This study opens up a new avenue to the magnetization of adsorbents for enhancing adsorption performance in addition to imparting magnetism.

To understand influenza vaccination and its correlates among health-careworkers (HCWs) during the 2019/2020 season in China, we used a self-administeredelectronic questionnaire to collect information on demographics, occupational characteristics, influenza vaccination status and access to free vaccination on the “Breath Circles”, a Chinese media platform for respiratory medical professionals. The reported influenza vaccine coverage among HCWs during this season was 67%, with more HCWs in a workplace with free vaccination than those with no free vaccination (79% vs.34%,p < .001). The influenza vaccine coverage among HCWs who were required or encouraged to get vaccinated by the workplace was significantly higher than that without any intervention measures (80% & 70 vs.39%,p < .001). The vaccine coverage in the workplaces with free and required vaccination simultaneously was highest compared to that with neither free vaccination nor any intervention measures (OR = 14.86, 95% CI: 10.93–20.20). The influenza vaccination coverage of HCWs in high-riskdepartments was significantly higher than that of other departments (70% vs.58%,p =.023). HCWs’ vaccine coverage was related to personal opinions and attitudes toward influenza or influenza vaccines, as well as other constraints such as availability of influenza vaccines, workplace regulations, and access to free vaccines.

Though fullerene has been regarded as an effective radical scavenger, the hydrophobicity strongly limits its application in biological fields. Herein, we proposed a simple photoreduction method in preparing a highly water-soluble nanocomposite consisting of ultrasmall copper nanoparticles (CuNPs) and hydroxylated fullerene (fullerenol), which showed excellent radical scavenging performance compared with traditional antioxidants. The superb antioxidative behavior was believed to be due to the synergetic effect induced by the stable decoration of CuNPs onto the surface of fullerenol, while the low metal loading level would decrease the potential toxicity of the prepared composite. Our work will offer an alternative choice for efficient antioxidative agents with more biosafety.

DNA-templated silver clusters are chromophores in which the nucleobases encode the cluster spectra and brightness. We describe the coordination environments of two nearly identical Ag106+ clusters that form with 18-nucleotide strands CCCCA CCCCT CCCX TTTT, with X = guanosine and inosine. For the first time, femtosecond time-resolved infrared (TRIR) spectroscopy with visible excitation and mid-infrared probing is used to correlate the response of nucleobase vibrational modes to electronic excitation of the metal cluster. A rich pattern of transient TRIR peaks in the 1400-1720 cm-1 range decays synchronously with the visible emission. Specific infrared signatures associated with the single guanosine/inosine along with a subset of cytidines, but not the thymidines, are observed. These fingerprints suggest that the network of bonds between a silver cluster adduct and its polydentate DNA ligands can be deciphered to rationally tune the coordination and thus spectra of molecular silver chromophores.