Charge transport through the multiple end zigzag edge states of armchair graphene nanoribbons and heterojunctions.

This comprehensive study investigates charge transport through the multiple end zigzag edge states of finite-size armchair graphene nanoribbons/boron nitride nanoribbons (n-AGNR/w-BNNR) junctions under a longitudinal electric field, where n and w denote the widths of the AGNRs and the BNNRs, respectively. In 13-atom wide AGNR segments, the edge states exhibit a blue Stark shift in response to the electric field, with only the long decay length zigzag edge states showing significant interaction with the red Stark shift subband states. Charge tunneling through such edge states assisted by the subband states is elucidated in the spectra of the transmission coefficient. In the 13-AGNR/6-BNNR heterojunction, notable influences on the energy levels of the end zigzag edge states of 13-AGNRs induced by BNNR segments are observed. We demonstrate the modulation of these energy levels in resonant tunneling situations, as depicted by bias-dependent transmission coefficient spectra. Intriguing nonthermal broadening of tunneling current shows a significant peak-to-valley ratio. Our findings highlight the promising potential of n-AGNR/w-BNNR heterojunctions with long decay length edge states in the realm of GNR-based single electron transistors at room temperature.

Thermoelectric properties of armchair graphene nanoribbons with array characteristics.

The thermoelectric properties of armchair graphene nanoribbons (AGNRs) with array characteristics are investigated theoretically using the tight-binding model and Green's function technique. The AGNR structures with array characteristics are created by embedding a narrow boron nitride nanoribbon (BNNR) into a wider AGNR, resulting in two narrow AGNRs. This system is denoted as w-AGNR/n-BNNR, where 'w' and 'n' represent the widths of the wider AGNR and narrow BNNR, respectively. We elucidate the coupling effect between two narrow symmetrical AGNRs on the electronic structure of w-AGNR/i-BNNR. A notable discovery is that the power factor of the 15-AGNR/5-BNNR with the minimum width surpasses the quantum limitation of power factor for 1D ideal systems. The energy level degeneracy observed in the first subbands of w-AGNR/n-BNNR structures proves to be highly advantageous in enhancing the electrical power outputs of graphene nanoribbon devices.

A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography.

Importance: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans. Objective: To develop a deep-learning algorithm based on volumetric SD-OCT scans to predict the progression from iAMD to GA during the year following the scan. Design, Setting, and Participants: This retrospective cohort study included participants with iAMD at baseline and who either progressed or did not progress to GA within the subsequent 13 months. Participants were included from centers in 4 US states. Data set 1 included patients from the Age-Related Eye Disease Study 2 AREDS2 (Ancillary Spectral-Domain Optical Coherence Tomography) A2A study (July 2008 to August 2015). Data sets 2 and 3 included patients with imaging taken in routine clinical care at a tertiary referral center and associated satellites between January 2013 and January 2023. The stored imaging data were retrieved for the purpose of this study from July 1, 2022, to February 1, 2023. Data were analyzed from May 2021 to July 2023. Exposure: A position-aware convolutional neural network with proactive pseudointervention was trained and cross-validated on Bioptigen SD-OCT volumes (data set 1) and validated on 2 external data sets comprising Heidelberg Spectralis SD-OCT scans (data sets 2 and 3). Main Outcomes and Measures: Prediction of progression to GA within 13 months was evaluated with area under the receiver-operator characteristic curves (AUROC) as well as area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Results: The study included a total of 417 patients: 316 in data set 1 (mean [SD] age, 74 [8]; 185 [59%] female), 53 in data set 2, (mean [SD] age, 83 [8]; 32 [60%] female), and 48 in data set 3 (mean [SD] age, 81 [8]; 32 [67%] female). The AUROC for prediction of progression from iAMD to GA within 1 year was 0.94 (95% CI, 0.92-0.95; AUPRC, 0.90 [95% CI, 0.85-0.95]; sensitivity, 0.88 [95% CI, 0.84-0.92]; specificity, 0.90 [95% CI, 0.87-0.92]) for data set 1. The addition of expert-annotated SD-OCT features to the model resulted in no improvement compared to the fully autonomous model (AUROC, 0.95; 95% CI, 0.92-0.95; P = .19). On an independent validation data set (data set 2), the model predicted progression to GA with an AUROC of 0.94 (95% CI, 0.91-0.96; AUPRC, 0.92 [0.89-0.94]; sensitivity, 0.91 [95% CI, 0.74-0.98]; specificity, 0.80 [95% CI, 0.63-0.91]). At a high-specificity operating point, simulated clinical trial recruitment was enriched for patients progressing to GA within 1 year by 8.3- to 20.7-fold (data sets 2 and 3). Conclusions and Relevance: The fully automated, position-aware deep-learning algorithm assessed in this study successfully predicted progression from iAMD to GA over a clinically meaningful time frame. The ability to predict imminent GA progression could facilitate clinical trials aimed at preventing the condition and could guide clinical decision-making regarding screening frequency or treatment initiation.

Thermal rectification through the topological states of asymmetrical length armchair graphene nanoribbons heterostructures with vacancies.

We present a theoretical investigation of electron heat current in asymmetrical length armchair graphene nanoribbon (AGNR) heterostructures with vacancies, focusing on the topological states (TSs). In particular, we examine the 9-7-9 AGNR heterostructures where the TSs are well-isolated from the conduction and valence subbands. This isolation effectively mitigates thermal noise of subbands arising from temperature fluctuations during charge transport. Moreover, when the TSs exhibit an orbital off-set, intriguing electron heat rectification phenomena are observed, primarily attributed to inter-TS electron Coulomb interactions. To enhance the heat rectification ratio (ηQ), we manipulate the coupling strengths between the heat sources and the TSs by introducing asymmetrical lengths in the 9-AGNRs. This approach offers control over the rectification properties, enabling significant enhancements. Additionally, we introduce vacancies strategically positioned between the heat sources and the TSs to suppress phonon heat current. This arrangement effectively reduces the overall phonon heat current, while leaving the TSs unaffected. Our findings provide valuable insights into the behavior of electron heat current in AGNR heterostructures, highlighting the role of topological states, inter-TS electron Coulomb interactions, and the impact of structural modifications such as asymmetrical lengths and vacancy positioning. These results pave the way for the design and optimization of graphene-based devices with improved thermal management and efficient control of electron heat transport.

Determination of exciton binding energy using photocurrent spectroscopy of Ge quantum-dot single-hole transistors under CW pumping.

We reported exciton binding-energy determination using tunneling-current spectroscopy of Germanium (Ge) quantum dot (QD) single-hole transistors (SHTs) operating in the few-hole regime, under 405-1550 nm wavelength (λ) illumination. When the photon energy is smaller than the bandgap energy (1.46 eV) of a 20 nm Ge QD (for instance, λ = 1310 nm and 1550 nm illuminations), there is no change in the peak voltages of tunneling current spectroscopy even when the irradiation power density reaches as high as 10 µW/µm2. In contrast, a considerable shift in the first hole-tunneling current peak towards positive VG is induced (ΔVG ≈ 0.08 V at 0.33 nW/µm2 and 0.15 V at 1.4 nW/µm2) and even additional photocurrent peaks are created at higher positive VG values (ΔVG ≈ 0.2 V at 10 nW/µm2 irradiation) by illumination at λ = 850 nm (where the photon energy matches the bandgap energy of the 20 nm Ge QD). These experimental observations were further strengthened when Ge-QD SHTs were illuminated by λ = 405 nm lasers at much lower optical-power conditions. The newly-photogenerated current peaks are attributed to the contribution of exciton, biexciton, and positive trion complexes. Furthermore, the exciton binding energy can be determined by analyzing the tunneling current spectra.

Effects of Coulomb Blockade on the Charge Transport through the Topological States of Finite Armchair Graphene Nanoribbons and Heterostructures.

In this study, we investigate the charge transport properties of semiconducting armchair graphene nanoribbons (AGNRs) and heterostructures through their topological states (TSs), with a specific focus on the Coulomb blockade region. Our approach employs a two-site Hubbard model that takes into account both intra- and inter-site Coulomb interactions. Using this model, we calculate the electron thermoelectric coefficients and tunneling currents of serially coupled TSs (SCTSs). In the linear response regime, we analyze the electrical conductance (Ge), Seebeck coefficient (S), and electron thermal conductance (κe) of finite AGNRs. Our results reveal that at low temperatures, the Seebeck coefficient is more sensitive to many-body spectra than electrical conductance. Furthermore, we observe that the optimized S at high temperatures is less sensitive to electron Coulomb interactions than Ge and κe. In the nonlinear response regime, we observe a tunneling current with negative differential conductance through the SCTSs of finite AGNRs. This current is generated by electron inter-site Coulomb interactions rather than intra-site Coulomb interactions. Additionally, we observe current rectification behavior in asymmetrical junction systems of SCTSs of AGNRs. Notably, we also uncover the remarkable current rectification behavior of SCTSs of 9-7-9 AGNR heterostructure in the Pauli spin blockade configuration. Overall, our study provides valuable insights into the charge transport properties of TSs in finite AGNRs and heterostructures. We emphasize the importance of considering electron-electron interactions in understanding the behavior of these materials.

Effects of metallic electrodes on the thermoelectric properties of zigzag graphene nanoribbons with periodic vacancies.

We theoretically analyze the thermoelectric properties of graphene quantum dot arrays (GQDAs) with line- or surface-contacted metal electrodes. Such GQDAs are realized as zigzag graphene nanoribbons (ZGNRs) with periodic vacancies. Gaps and minibands are formed in these GQDAs, which can have metallic and semiconducting phases. The electronic states of the first conduction (valence) miniband with nonlinear dispersion may have long coherent lengths along the zigzag edge direction. With line-contacted metal electrodes, the GQDAs have the characteristics of serially coupled quantum dots (SCQDs) if the armchair edge atoms of the ZGNRs are coupled to the electrodes. By contrast, the GQDAs have the characteristics of parallel quantum dots if the zigzag edge atoms are coupled to the electrodes. The maximum thermoelectric power factors of SCQDs with line-contacted electrodes of Cu, Au, Pt, Pd, or Ti at room temperature were similar or greater than 0.186 nW K-1; their figures of merit were greater than three. GQDAs with line-contacted metal electrodes have much better thermoelectric performance than surface contacted metal electrodes.

Automated Detection of Posterior Vitreous Detachment on OCT Using Computer Vision and Deep Learning Algorithms.

Objective: To develop automated algorithms for the detection of posterior vitreous detachment (PVD) using OCT imaging. Design: Evaluation of a diagnostic test or technology. Subjects: Overall, 42 385 consecutive OCT images (865 volumetric OCT scans) obtained with Heidelberg Spectralis from 865 eyes from 464 patients at an academic retina clinic between October 2020 and December 2021 were retrospectively reviewed. Methods: We developed a customized computer vision algorithm based on image filtering and edge detection to detect the posterior vitreous cortex for the determination of PVD status. A second deep learning (DL) image classification model based on convolutional neural networks and ResNet-50 architecture was also trained to identify PVD status from OCT images. The training dataset consisted of 674 OCT volume scans (33 026 OCT images), while the validation testing set consisted of 73 OCT volume scans (3577 OCT images). Overall, 118 OCT volume scans (5782 OCT images) were used as a separate external testing dataset. Main Outcome Measures: Accuracy, sensitivity, specificity, F1-scores, and area under the receiver operator characteristic curves (AUROCs) were measured to assess the performance of the automated algorithms. Results: Both the customized computer vision algorithm and DL model results were largely in agreement with the PVD status labeled by trained graders. The DL approach achieved an accuracy of 90.7% and an F1-score of 0.932 with a sensitivity of 100% and a specificity of 74.5% for PVD detection from an OCT volume scan. The AUROC was 89% at the image level and 96% at the volume level for the DL model. The customized computer vision algorithm attained an accuracy of 89.5% and an F1-score of 0.912 with a sensitivity of 91.9% and a specificity of 86.1% on the same task. Conclusions: Both the computer vision algorithm and the DL model applied on OCT imaging enabled reliable detection of PVD status, demonstrating the potential for OCT-based automated PVD status classification to assist with vitreoretinal surgical planning. Financial Disclosures: Proprietary or commercial disclosure may be found after the references.

Contact Effects on Thermoelectric Properties of Textured Graphene Nanoribbons.

The transport and thermoelectric properties of finite textured graphene nanoribbons (t-GNRs) connected to electrodes with various coupling strengths are theoretically studied in the framework of the tight-binding model and Green's function approach. Due to quantum constriction induced by the indented edges, such t-GNRs behave as serially coupled graphene quantum dots (SGQDs). These types of SGQDs can be formed by tailoring zigzag GNRs (ZGNRs) or armchair GNRs (AGNRs). Their bandwidths and gaps can be engineered by varying the size of the quantum dot and the neck width at indented edges. Effects of defects and junction contact on the electrical conductance, Seebeck coefficient, and electron thermal conductance of t-GNRs are calculated. When a defect occurs in the interior site of textured ZGNRs (t-ZGNRs), the maximum power factor within the central gap or near the band edges is found to be insensitive to the defect scattering. Furthermore, we found that SGQDs formed by t-ZGNRs have significantly better electrical power outputs than those of textured ANGRs due to the improved functional shape of the transmission coefficient in t-ZGNRs. With a proper design of contact, the maximum power factor (figure of merit) of t-ZGNRs could reach 90% (95%) of the theoretical limit.

A Rapid Translational Immune Response Program in CD8 Memory T Lymphocytes.

The activation of memory T cells is a very rapid and concerted cellular response that requires coordination between cellular processes in different compartments and on different time scales. In this study, we use ribosome profiling and deep RNA sequencing to define the acute mRNA translation changes in CD8 memory T cells following initial activation events. We find that initial translation enables subsequent events of human and mouse T cell activation and expansion. Briefly, early events in the activation of Ag-experienced CD8 T cells are insensitive to transcriptional blockade with actinomycin D, and instead depend on the translation of pre-existing mRNAs and are blocked by cycloheximide. Ribosome profiling identifies ∼92 mRNAs that are recruited into ribosomes following CD8 T cell stimulation. These mRNAs typically have structured GC and pyrimidine-rich 5' untranslated regions and they encode key regulators of T cell activation and proliferation such as Notch1, Ifngr1, Il2rb, and serine metabolism enzymes Psat1 and Shmt2 (serine hydroxymethyltransferase 2), as well as translation factors eEF1a1 (eukaryotic elongation factor α1) and eEF2 (eukaryotic elongation factor 2). The increased production of receptors of IL-2 and IFN-γ precedes the activation of gene expression and augments cellular signals and T cell activation. Taken together, we identify an early RNA translation program that acts in a feed-forward manner to enable the rapid and dramatic process of CD8 memory T cell expansion and activation.

Internal carotid artery aneurysm presenting as diplopia via telemedicine during COVID-19.

A patient presented with acute onset of double vision during the start of the COVID-19 pandemic when elective medical care was restricted. Initially declining an in-person evaluation, she was examined using a telehealth video visit, incorporating multiple technological modalities to ascertain ophthalmic examination elements. Her findings prompted emergent neuroimaging, revealing a giant internal carotid artery aneurysm, which was successfully embolized to prevent debilitating and possibly fatal intracranial haemorrhage. This case report illustrates the successful use of telemedicine and remote patient data acquisition to make a life-saving diagnosis.

Examining concurrent validity between COMLEX-USA Level 2-Cognitive Evaluation and COMLEX-USA Level 2-Performance Evaluation.

CONTEXT: The Comprehensive Osteopathic Medical Licensing Examination of the United States of America (COMLEX-USA) is a three level examination used as a pathway to licensure for students in osteopathic medical education programs. COMLEX-USA Level 2 includes a written assessment of Fundamental Clinical Sciences for Osteopathic Medical Practice (Level 2-Cognitive Evaluation [L2-CE]) delivered in a computer based format and separate performance evaluation (Level 2-Performance Evaluation [L2-PE]) administered through live encounters with standardized patients. L2-PE was designed to augment L2-CE. It is expected that the two examinations measure related yet distinct constructs. OBJECTIVES: To explore the concurrent validity of L2-CE with L2-PE. METHODS: First attempt test scores were obtained from the National Board of Osteopathic Medical Examiners database for 6,639 candidates who took L2-CE between June 2019 and May 2020 and matched to the students' L2-PE scores. The sample represented all colleges of osteopathic medicine and 97.5% of candidates who took L2-CE during the complete 2019-2020 test cycle. We calculated disattenuated correlations between the total score for L2-CE, the L2-CE scores for the seven competency domains (CD1 through CD7), and the L2-PE scores for the Humanistic Domain (HM) and Biomedical/Biomechanical Domain (BM). All scores were on continuous scales. RESULTS: Pearson correlations ranged from 0.10 to 0.88 and were all statically significant (p<0.01). L2-CE total score was most strongly correlated with CD2 (0.88) and CD3 (0.85). Pearson correlations between the L2-CE competency domain subscores ranged from 0.17 to 0.70, and correlations which included either HM or BM ranged from 0.10 to 0.34 with the strongest of those correlations being between BM and L2-CE total score (0.34) as well as between HM and BM (0.28).The largest increase between corresponding Pearson and disattenuated correlations was for pairs of scores with lower reliabilities such as CD5 and CD6, which had a Pearson correlation of 0.17 and a disattenuated correlation of 0.68. The smallest increase in correlations was observed in pairs of scores with larger reliabilities such as L2-CE total score and HM, which had a Pearson correlation of 0.23 and a disattenuated correlation of 0.28. The reliability of L2-CE was 0.87, 0.81 for HM, and 0.73 for BM. The reliabilities for the L2-CE competency domain scores ranged from 0.22 to 0.74. The small to moderate correlations between the L2-CE total score and the two L2-PE support the expectation that these examinations measure related but distinct constructs. The correlations between L2-PE and L2-CE competency domain subscores reflect the distribution of items defined by the L2-PE blueprint, providing evidence that the examinations are performing as designed. CONCLUSIONS: This study provides evidence supporting the validity of the blueprints for constructing COMLEX-USA Levels 2-CE and 2-PE examinations in concert with the purpose and nature of the examinations.

Logistic Regression Classification of Primary Vitreoretinal Lymphoma versus Uveitis by Interleukin 6 and Interleukin 10 Levels.

PURPOSE: To assess the diagnostic performance and generalizability of logistic regression in classifying primary vitreoretinal lymphoma (PVRL) versus uveitis from intraocular cytokine levels in a single-center retrospective cohort, comparing a logistic regression model and previously published Interleukin Score for Intraocular Lymphoma Diagnosis (ISOLD) scores against the interleukin 10 (IL-10)-to-interleukin 6 (IL-6) ratio. DESIGN: Retrospective cohort study. PARTICIPANTS: Patient histories, pathology reports, and intraocular cytokine levels from 2339 patient entries in the National Eye Institute Histopathology Core database. METHODS: Patient diagnoses of PVRL versus uveitis and associated aqueous or vitreous IL-6 and IL-10 levels were collected retrospectively. From these data, cytokine levels were compared between diagnoses with the Mann-Whitney U test. A logistic regression model was trained to classify PVRL versus uveitis from aqueous and vitreous IL-6 and IL-10 samples and compared with ISOLD scores and IL-10-to-IL-6 ratios. MAIN OUTCOME MEASURES: Area under the receiver operating characteristic curve (AUC) for each classifier and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at the optimal cutoff (maximal Youden index) for each classifier. RESULTS: Seventy-seven lymphoma patients (10 aqueous samples, 67 vitreous samples) and 84 uveitis patients (19 aqueous samples, 65 vitreous samples) treated between October 5, 1999, and September 16, 2015, were included. Interleukin 6 levels were higher and IL-10 levels were lower in uveitis patients compared with lymphoma patients (P < 0.01). For vitreous samples, the logistic regression model, ISOLD score, and IL-10-to-IL-6 ratio achieved AUCs of 98.3%, 97.7%, and 96.3%, respectively. Sensitivity, specificity, PPV, and NPV at the optimal cutoffs for each classifier were 94.2%, 96.9%, 97%, and 94% for the logistic regression model; 92.7%, 100%, 100%, and 92.9% for the ISOLD score; and 94.2%, 95.3%, 95.6%, and 93.9% for the IL-10-to-IL-6 ratio. All models achieved complete separation between uveitis and lymphoma in the aqueous data set. CONCLUSIONS: The accuracy of the logistic regression model and generalizability of the ISOLD score to an independent patient cohort suggest that intraocular cytokine analysis by logistic regression may be a promising adjunct to cytopathologic analysis, the gold standard, for the early diagnosis of primary vitreoretinal lymphoma. Further validation studies are merited.

Stem Cell-Derived Endothelial Cell Model that Responds to Tobacco Smoke Like Primary Endothelial Cells.

To clarify how smoking leads to heart attack and stroke, we developed an endothelial cell model (iECs) generated from human induced Pluripotent Stem Cells (iPSC) and evaluated its responses to tobacco smoke. These iECs exhibited a uniform endothelial morphology, and expressed markers PECAM1/CD31, VWF/ von Willebrand Factor, and CDH5/VE-Cadherin. The iECs also exhibited tube formation and acetyl-LDL uptake comparable to primary endothelial cells (EC). RNA sequencing (RNA-Seq) revealed a robust correlation coefficient between iECs and EC (R = 0.76), whereas gene responses to smoke were qualitatively nearly identical between iECs and primary ECs (R = 0.86). Further analysis of transcriptional responses implicated 18 transcription factors in regulating responses to smoke treatment, and identified gene sets regulated by each transcription factor, including pathways for oxidative stress, DNA damage/repair, ER stress, apoptosis, and cell cycle arrest. Assays for 42 cytokines in HUVEC cells and iECs identified 23 cytokines that responded dynamically to cigarette smoke. These cytokines and cellular stress response pathways describe endothelial responses for lymphocyte attachment, activation of coagulation and complement, lymphocyte growth factors, and inflammation and fibrosis; EC-initiated events that collectively lead to atherosclerosis. Thus, these studies validate the iEC model and identify transcriptional response networks by which ECs respond to tobacco smoke. Our results systematically trace how ECs use these response networks to regulate genes and pathways, and finally cytokine signals to other cells, to initiate the diverse processes that lead to atherosclerosis and cardiovascular disease.

The serine hydroxymethyltransferase-2 (SHMT2) initiates lymphoma development through epigenetic tumor suppressor silencing.

Cancer cells adapt their metabolic activities to support growth and proliferation. However, increased activity of metabolic enzymes is not usually considered an initiating event in the malignant process. Here, we investigate the possible role of the enzyme serine hydroxymethyltransferase-2 (SHMT2) in lymphoma initiation. SHMT2 localizes to the most frequent region of copy number gains at chromosome 12q14.1 in lymphoma. Elevated expression of SHMT2 cooperates with BCL2 in lymphoma development; loss or inhibition of SHMT2 impairs lymphoma cell survival. SHMT2 catalyzes the conversion of serine to glycine and produces an activated one-carbon unit that can be used to support S-adenosyl methionine synthesis. SHMT2 induces changes in DNA and histone methylation patterns leading to promoter silencing of previously uncharacterized mutational genes, such as SASH1 and PTPRM. Together, our findings reveal that amplification of SHMT2 in cooperation with BCL2 is sufficient in the initiation of lymphomagenesis through epigenetic tumor suppressor silencing.

HBEGF+ macrophages in rheumatoid arthritis induce fibroblast invasiveness.

Macrophages tailor their function according to the signals found in tissue microenvironments, assuming a wide spectrum of phenotypes. A detailed understanding of macrophage phenotypes in human tissues is limited. Using single-cell RNA sequencing, we defined distinct macrophage subsets in the joints of patients with the autoimmune disease rheumatoid arthritis (RA), which affects ~1% of the population. The subset we refer to as HBEGF+ inflammatory macrophages is enriched in RA tissues and is shaped by resident fibroblasts and the cytokine tumor necrosis factor (TNF). These macrophages promoted fibroblast invasiveness in an epidermal growth factor receptor-dependent manner, indicating that intercellular cross-talk in this inflamed setting reshapes both cell types and contributes to fibroblast-mediated joint destruction. In an ex vivo synovial tissue assay, most medications used to treat RA patients targeted HBEGF+ inflammatory macrophages; however, in some cases, medication redirected them into a state that is not expected to resolve inflammation. These data highlight how advances in our understanding of chronically inflamed human tissues and the effects of medications therein can be achieved by studies on local macrophage phenotypes and intercellular interactions.

Cost-effectiveness of afatinib, gefitinib, erlotinib and pemetrexed-based chemotherapy as first-line treatments for advanced non-small cell lung cancer in China.

PURPOSE: Tyrosine kinase inhibitors (TKI) of the epidermal growth factor receptor (EGFR) are becoming the standard treatments for Chinese patients with advanced non-small cell lung cancer (NSCLC) harboring an EGFR mutation. However, the economic impact is unclear yet in China. MATERIALS AND METHODS: A decision-analytic model was developed to simulate 1-month patient transitions in a 10-year time horizon from Chinese heath care system perspective. The health and economic outcomes of four first-line strategies (pemetrexed plus cisplatin [PC], gefitinib, erlotinib, and afatinib) among NSCLC patients harboring EGFR mutations were estimated and assessed via indirect comparisons. Costs in the Chinese setting were estimated by using local hospital data and literatures. A 5% annual discount rate was applied to both costs and outcomes. The primary outcome was the incremental cost-effectiveness ratio (ICER). Sensitivity analyses were performed. RESULTS: Afatinib achieved additional 0.382, 0.216 and 0.174 quality-adjusted life-years (QALYs) with marginal $7930, $3680 and $2818 costs in comparison with PC, gefitinib and erlotinib, which resulted in the ICERs of $20,758, $17,693 and $16,197 per QALY gained, respectively. The hazard ratios (HR) of overall survival (OS) of afatinib against gefitinib, erlotinib and PC strategy had substantial influential parameters. CONCLUSIONS: First-line afatinib is cost-effective compared with gefitinib, erlotinib and PC treatment for Chinese patients with EGFR mutation-positive NSCLC.

Small-molecule AgrA inhibitors F12 and F19 act as antivirulence agents against Gram-positive pathogens.

Small-molecule antivirulence agents represent a promising alternative or adjuvant to antibiotics. These compounds disarm pathogens of disease-causing toxins without killing them, thereby diminishing survival pressure to develop resistance. Here we show that the small-molecule antivirulence agents F12 and F19 block staphylococcal transcription factor AgrA from binding to its promoter. Consequently, toxin expression is inhibited, thus preventing host cell damage by Gram-positive pathogens. Broad spectrum efficacy against Gram-positive pathogens is due to the existence of AgrA homologs in many Gram-positive bacteria. F12 is more efficacious in vitro and F19 works better in vivo. In a murine MRSA bacteremia/sepsis model, F19 treatment alone resulted in 100% survival while untreated animals had 70% mortality. Furthermore, F19 enhances antibiotic efficacy in vivo. Notably, in a murine MRSA wound infection model, combination of F19 with antibiotics resulted in bacterial load reduction. Thus, F19 could be used alone or in combination with antibiotics to prevent and treat infections of Gram-positive pathogens.

Residual heart rate variability measures can better differentiate patients with acute myocardial infarction from patients with patent coronary artery.

PURPOSE: It has been shown that the power spectral density (PSD) of heart rate variability (HRV) can be decomposed into a power-law function and a residual PSD (rPSD) with a more prominent high-frequency component than that in traditional PSD. This study investigated whether the residual HRV (rHRV) measures can better discriminate patients with acute myocardial infarction (AMI) from patients with patent coronary artery (PCA) than traditional HRV measures. MATERIALS AND METHODS: The rHRV and HRV measures of 48 patients with AMI and 69 patients with PCA were compared. RESULTS: The high-frequency power of rHRV spectrum was significantly enhanced while the low-frequency and very low-frequency powers of rHRV spectrum were significantly suppressed, as compared to their corresponding traditional HRV spectrum in both groups of patients. The normalized residual high-frequency power (nrHFP = residual high-frequency power/residual total power) was significantly greater than the corresponding normalized high-frequency power in both groups of patients. Between-groups comparison showed that the nrHFP in AMI patients was significantly smaller than that in PCA patients. Receiver operating characteristic curve analysis showed that the nrHFP or nrHFP + normalized residual very low-frequency power (residual very low-frequency power/rTP) had better discrimination capability than the corresponding HRV measures for predicting AMI. CONCLUSIONS: Compared with traditional HRV measures, the rHRV measures can slightly better differentiate AMI patients from PCA patients, especially the nrHFP or nrHFP + normalized residual very low-frequency power.