Frequency domain near-infrared multiwavelength imager design using high-speed, direct analog-to-digital conversion

Frequency domain near-infrared spectroscopy (FD-NIRS) has proven to be a reliable method for quantification of tissue absolute optical properties. We present a full-sampling direct analog-to-digital conversion FD-NIR imager. While we developed this instrument with a focus on high-speed optical breast tomographic imaging, the proposed design is suitable for a wide-range of biophotonic applications where fast, accurate quantification of absolute optical properties is needed. Simultaneous dual wavelength operation at 685 and 830 nm is achieved by concurrent 67.5 and 75 MHz frequency modulation of each laser source, respectively, followed by digitization using a high-speed (180  MS/s) 16-bit A/D converter and hybrid FPGA-assisted demodulation. The instrument supports 25 source locations and features 20 concurrently operating detectors. The noise floor of the instrument was measured at <1.4  pW/√Hz, and a dynamic range of 115+ dB, corresponding to nearly six orders of magnitude, has been demonstrated. Titration experiments consisting of 200 different absorption and scattering values were conducted to demonstrate accurate optical property quantification over the entire range of physiologically expected values.United States. National Institutes of Health (R01-CA142575)United States. National Institutes of Health (R01-CA097305)United States. National Institutes of Health (R01-CA187595)United States. National Institutes of Health (R00-EB011889

Recent Advances in Electrospun Sustainable Composites for Biomedical, Environmental, Energy, and Packaging Applications.

Electrospinning has gained constant enthusiasm and wide interest as a novel sustainable material processing technique due to its ease of operation and wide adaptability for fabricating eco-friendly fibers on a nanoscale. In addition, the device working parameters, spinning solution properties, and the environmental factors can have a significant effect on the fibers\u27 morphology during electrospinning. This review summarizes the newly developed principles and influence factors for electrospinning technology in the past five years, including these factors\u27 interactions with the electrospinning mechanism as well as its most recent applications of electrospun natural or sustainable composite materials in biology, environmental protection, energy, and food packaging materials

How to Evaluate the Generalization of Detection? A Benchmark for Comprehensive Open-Vocabulary Detection

Object detection (OD) in computer vision has made significant progress in recent years, transitioning from closed-set labels to open-vocabulary detection (OVD) based on large-scale vision-language pre-training (VLP). However, current evaluation methods and datasets are limited to testing generalization over object types and referral expressions, which do not provide a systematic, fine-grained, and accurate benchmark of OVD models' abilities. In this paper, we propose a new benchmark named OVDEval, which includes 9 sub-tasks and introduces evaluations on commonsense knowledge, attribute understanding, position understanding, object relation comprehension, and more. The dataset is meticulously created to provide hard negatives that challenge models' true understanding of visual and linguistic input. Additionally, we identify a problem with the popular Average Precision (AP) metric when benchmarking models on these fine-grained label datasets and propose a new metric called Non-Maximum Suppression Average Precision (NMS-AP) to address this issue. Extensive experimental results show that existing top OVD models all fail on the new tasks except for simple object types, demonstrating the value of the proposed dataset in pinpointing the weakness of current OVD models and guiding future research. Furthermore, the proposed NMS-AP metric is verified by experiments to provide a much more truthful evaluation of OVD models, whereas traditional AP metrics yield deceptive results. Data is available at \url{https://github.com/om-ai-lab/OVDEval}Comment: Long paper accepted at AAAI 202

The prospected air quality measurements for further unconventional natural gas developments in China based on the United States experience

The technological innovation of horizontal drilling and high-volume hydraulic fracturing has promoted the development of unconventional natural gas (UNG) production worldwide, and hence has aroused public concern about the air pollution it may bring about. In this study, we have provided (1) an overview of the study on air pollutants from UNG emissions in the USA, focusing on both the air pollutant characterization and their related observation technologies/platforms; and (2) the potential air quality measurements of UNG development emerging in China. This study will provide useful information for Chinese environmental researchers and the local governments to deal with related air quality issues

Virtual screening–based discovery of AI-2 quorum sensing inhibitors that interact with an allosteric hydrophobic site of LsrK and their functional evaluation

Introduction: Quorum sensing (QS) is a bacterial intracellular and intercellular communication system that regulates virulence factor production, biofilm formation, and antibiotic sensitivity. Quorum-sensing inhibitors (QSIs) are a novel class of antibiotics that can effectively combat antibiotic resistance. Autoinducer-2 (AI-2) is a universal signaling molecule that mediates inter- and intraspecies QS systems among different bacteria. Furthermore, LsrK plays an important role in regulating the activity and stability of the intracellular AI-2 signaling pathway. Thus, LsrK is considered an important target for the development of QSIs.Methods: We designed a workflow integrating molecular dynamic (MD) simulations, virtual screening, LsrK inhibition assays, cell-based AI-2-mediated QS interference assays, and surface plasmon resonance (SPR)-based protein affinity assays to screen for potential LsrK kinase inhibitors.Results: MD simulation results of the LsrK/ATP complex revealed hydrogen bonds and salt bridge formation among four key residues, namely, Lys 431, Tyr 341, Arg 319, and Arg 322, which are critical for the binding of ATP to LsrK. Furthermore, MD simulation results indicated that the ATP-binding site has an allosteric pocket that can become larger and be occupied by small molecule compounds. Based on these MD simulation results, a constraint of forming at least one hydrogen bond with Arg 319, Arg 322, Lys 431, or Tyr 341 residues was introduced when performing virtual screening using Glide’s virtual screening workflow (VSW). In the meantime, compounds with hydrophobic group likely to interact with the allosteric hydrophobic pocket are preferred when performing visual inspection. Seventy-four compounds were selected for the wet laboratory assays based on virtual screening and the absorption, distribution, metabolism, and excretion (ADME) properties of these compounds. LsrK inhibition assays revealed 12 compounds inhibiting LsrK by more than 60% at a 200 μM concentration; four of these (Y205-6768, D135-0149, 3284–1358, and N025-0038) had IC50 values below 50 μM and were confirmed as ATP-competitive inhibitors. Six of these 12 LsrK inhibitors exhibited high AI-2 QS inhibition, of which, Y205-6768 had the highest activity with IC50 = 11.28 ± 0.70 μM. The SPR assay verified that compounds Y205-6768 and N025-0038 specifically bound to LsrK. MD simulation analysis of the docking complexes of the four active compounds with LsrK further confirmed the importance of forming hydrogen bonds and salt bridges with key basic amino acid residues including Lys 431, Tyr 341, Arg 319, and Arg 322 and filling the allosteric hydrophobic pocket next to the purine-binding site of LsrK.Discussion: Our study clarified for the first time that there is an allosteric site near the ATP-binding site of Lsrk and that it enriches the structure–activity relationship information of Lsrk inhibitors. The four identified compounds showed novel structures, low molecular weights, high activities, and novel LsrK binding modes, rendering them suitable for further optimization for effective AI-2 QSIs. Our work provides a valuable reference for the discovery of QSIs that do not inhibit bacterial growth, thereby avoiding the emergence of drug resistance

Diagnostic value of circulating miR-155 for breast cancer: a meta-analysis

BackgroundsThe value of circulating microRNA (miR)-155 for breast cancer (BC) diagnosis may differ in different studies. Therefore, we conducted this systematic review and meta-analysis to evaluate the potential application of circulating miR-155 in the diagnosis of BC.MethodsArticles published before December 2023 and in English were searched in these databases: PubMed, Web of Science, Medline, EMBASE and Google Scholar. A summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR) were calculated from the true positive (TP), true negative (TN), false positive (FP) and false negative (FN) of each study. Additionally, the summary receive-operating characteristics (SROC) curve was constructed to summarize the TP and FP rates.ResultsThe pooled parameters calculated were as follows: sensitivity, 0.93 (95% CI: 0.83-0.97); specificity, 0.85 (95% CI: 0.74-0.92); PLR, 6.4 (95% CI: 3.4-11.9); NLR, 0.09 (95% CI: 0.04-0.20); and DOR, 74 (95% CI: 22-247). The analysis showed a significant heterogeneity (sensitivity, I2 = 95.19%, p &lt; 0.001; specificity, I2 = 95.29%, p &lt; 0.001; DOR, I2 = 92.9%, p &lt; 0.001). The SROC curve was with an area under curve (AUC) of 0.95 (95% CI: 0.93-0.97).ConclusionCirculating miR-155 has a potential in the diagnosis of BC