Ultrafast isolated molecule imaging without crystallization.

Crystallography is the standard for determining the atomic structure of molecules. Unfortunately, many interesting molecules, including an extensive array of biological macromolecules, do not form crystals. While ultrashort and intense X-ray pulses from free-electron lasers are promising for imaging single isolated molecules with the so-called "diffraction before destruction" technique, nanocrystals are still needed for producing sufficient scattering signal for structure retrieval as implemented in serial femtosecond crystallography. Here, we show that a femtosecond laser pulse train may be used to align an ensemble of isolated molecules to a high level transiently, such that the diffraction pattern from the highly aligned molecules resembles that of a single molecule, allowing one to retrieve its atomic structure with a coherent diffraction imaging technique. In our experiment with CO2 molecules, a high degree of alignment is maintained for about 100 fs, and a precisely timed ultrashort relativistic electron beam from a table-top instrument is used to record the diffraction pattern within that duration. The diffraction pattern is further used to reconstruct the distribution of CO2 molecules with atomic resolution. Our results mark a significant step toward imaging noncrystallized molecules with atomic resolution and open opportunities in the study and control of dynamics in the molecular frame that provide information inaccessible with randomly oriented molecules.

High-precision tumor resection down to few-cell level guided by NIR-IIb molecular fluorescence imaging.

In vivo fluorescence/luminescence imaging in the near-infrared-IIb (NIR-IIb, 1,500 to 1,700 nm) window under <1,000 nm excitation can afford subcentimeter imaging depth without any tissue autofluorescence, promising high-precision intraoperative navigation in the clinic. Here, we developed a compact imager for concurrent visible photographic and NIR-II (1,000 to 3,000 nm) fluorescence imaging for preclinical image-guided surgery. Biocompatible erbium-based rare-earth nanoparticles (ErNPs) with bright down-conversion luminescence in the NIR-IIb window were conjugated to TRC105 antibody for molecular imaging of CD105 angiogenesis markers in 4T1 murine breast tumors. Under a ∼940 ± 38 nm light-emitting diode (LED) excitation, NIR-IIb imaging of 1,500- to 1,700-nm emission afforded noninvasive tumor­to­normal tissue (T/NT) signal ratios of ∼40 before surgery and an ultrahigh intraoperative tumor-to-muscle (T/M) ratio of ∼300, resolving tumor margin unambiguously without interfering background signal from surrounding healthy tissues. High-resolution imaging resolved small numbers of residual cancer cells during surgery, allowing thorough and nonexcessive tumor removal at the few-cell level. NIR-IIb molecular imaging afforded 10-times-higher and 100-times-higher T/NT and T/M ratios, respectively, than imaging with IRDye800CW-TRC105 in the ∼900- to 1,300-nm range. The vastly improved resolution of tumor margin and diminished background open a paradigm of molecular imaging-guided surgery.

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease.

Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

Deep learning for in vivo near-infrared imaging.

Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial and temporal resolution through millimeter tissue depths. Imaging in the NIR-IIb window (1,500-1,700 nm) is the most effective one-photon approach to suppressing light scattering and maximizing imaging penetration depth, but relies on nanoparticle probes such as PbS/CdS containing toxic elements. On the other hand, imaging the NIR-I (700-1,000 nm) or NIR-IIa window (1,000-1,300 nm) can be done using biocompatible small-molecule fluorescent probes including US Food and Drug Administration-approved dyes such as indocyanine green (ICG), but has a caveat of suboptimal imaging quality due to light scattering. It is highly desired to achieve the performance of NIR-IIb imaging using molecular probes approved for human use. Here, we trained artificial neural networks to transform a fluorescence image in the shorter-wavelength NIR window of 900-1,300 nm (NIR-I/IIa) to an image resembling an NIR-IIb image. With deep-learning translation, in vivo lymph node imaging with ICG achieved an unprecedented signal-to-background ratio of >100. Using preclinical fluorophores such as IRDye-800, translation of ∼900-nm NIR molecular imaging of PD-L1 or EGFR greatly enhanced tumor-to-normal tissue ratio up to ∼20 from ∼5 and improved tumor margin localization. Further, deep learning greatly improved in vivo noninvasive NIR-II light-sheet microscopy (LSM) in resolution and signal/background. NIR imaging equipped with deep learning could facilitate basic biomedical research and empower clinical diagnostics and imaging-guided surgery in the clinic.

In vivo NIR-II structured-illumination light-sheet microscopy.

Noninvasive optical imaging with deep tissue penetration depth and high spatiotemporal resolution is important to longitudinally studying the biology at the single-cell level in live mammals, but has been challenging due to light scattering. Here, we developed near-infrared II (NIR-II) (1,000 to 1,700 nm) structured-illumination light-sheet microscopy (NIR-II SIM) with ultralong excitation and emission wavelengths up to ∼1,540 and ∼1,700 nm, respectively, suppressing light scattering to afford large volumetric three-dimensional (3D) imaging of tissues with deep-axial penetration depths. Integrating structured illumination into NIR-II light-sheet microscopy further diminished background and improved spatial resolution by approximately twofold. In vivo oblique NIR-II SIM was performed noninvasively for 3D volumetric multiplexed molecular imaging of the CT26 tumor microenvironment in mice, longitudinally mapping out CD4, CD8, and OX40 at the single-cell level in response to immunotherapy by cytosine-phosphate-guanine (CpG), a Toll-like receptor 9 (TLR-9) agonist combined with OX40 antibody treatment. NIR-II SIM affords an additional tool for noninvasive volumetric molecular imaging of immune cells in live mammals.

Assessment of vegetation net primary productivity variation and influencing factors in the Beijing-Tianjin-Hebei region.

Exploring the spatiotemporal variations of vegetation net primary productivity (NPP) and analyzing the relationships between NPP and its influencing factors are vital for ecological protection in the Beijing-Tianjin-Hebei (BTH) region. In this study, we employed the CASA model in conjunction with spatiotemporal analysis techniques to estimate and analyze the spatiotemporal variations of NPP in BTH and different ecological function sub-regions over the past two decades. Subsequently, we established three scenarios (actual, climate-driven and land cover-driven) to assess the influencing factors and quantify their relative contributions. The results indicated that the overall NPP in BTH exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 3.83 gC·m-2a-1. Furthermore, all six sub-regions exhibited an increase. The Bashang Plateau Ecological Protection Zone (BP) exhibited the highest growth rate (5.03 gC·m-2a-1), while the Low Plains Ecological Restoration Zone (LP) exhibited the lowest (2.07 gC·m-2a-1). Geographically, the stability of NPP exhibited a spatial pattern of gradual increase from west to east. Climate and land cover changes collectively increased NPP by 0.04 TgC·a-1 and 0.07 TgC·a-1, respectively, in the BTH region. Climate factors were found to have the greatest influence on NPP variations, contributing 40.49% across the BTH region. This influence exhibited a decreasing trend from northwest to southeast, with precipitation identified as the most influential climatic factor compared to temperature and solar radiation. Land cover change has profound effects on ecosystems, which is an important factor on NPP. From 2000 to 2020, 15.45% area of the BTH region underwent land cover type change, resulting in a total increase in NPP of 1.33 TgC. The conversion of grass into forest brought about the 0.89 TgC increase in NPP, which is the largest of all change types. In the area where land cover had undergone change, the land cover factor has been found to be the dominant factor influencing variations in NPP, with an average contribution of 49.37%. In contrast, in the south-central area where there has been no change in land cover, the residual factor has been identified as the most influential factor influencing variations in NPP. Our study highlights the important role of land cover change in influencing NPP variations in BTH. It also offers a novel approach to elucidating the influences of diverse factors on NPP, which is crucial for the scientific assessment of vegetation productivity and carbon sequestration capacity.

Dissecting the molecular features of bovine-arrested eight-cell embryos using single-cell multi-omics sequencing†.

The regulation of mammalian early-embryonic development is a complex, coordinated process that involves widespread transcriptomic and epigenetic remodeling. The main cause of developmental failure in preimplantation embryos after in vitro fertilization is the irreversible arrested-at-cleavage stage. To deepen our understanding of this embryonic block, we profiled a single-cell multi-omics map of copy number variations (CNVs), the transcriptome, the DNA methylome, and the chromatin state of bovine eight-cell embryos with a two-cell fate that either arrested or developed into blastocysts. To do this, we sequenced a biopsied blastomere and tracked the developmental potential of the remaining cells. Aneuploid embryos inferred by CNVs from DNA- and RNA-library data tended to lose their developmental potency. Analysis of distinct genomic regions of DNA methylation and chromatin accessibility revealed that enrichment of gene function and signaling pathways, such as the MAPK signaling pathway, was altered in arrested euploid eight-cell embryos compared with blastocyst-developed euploid eight-cell embryos. Moreover, the RNA expression and chromatin accessibility of embryonic genome activation-associated genes were lower in arrested euploid embryos than in blastocyst-developed embryos. Taken together, our results indicate that the developmental block of eight-cell embryos can be caused by multiple molecular layers, including CNVs, abnormality of DNA methylation and chromatin accessibility, and insufficient expression of embryonic genome activation-associated genes. Our integrated and comprehensive data set provides a valuable resource to further dissect the exact mechanisms underlying the arrest of bovine eight-cell embryos in vitro.

Identification of metabolism-related subtypes and feature genes in Alzheimer's disease.

BACKGROUND: Owing to the heterogeneity of Alzheimer's disease (AD), its pathogenic mechanisms are yet to be fully elucidated. Evidence suggests an important role of metabolism in the pathophysiology of AD. Herein, we identified the metabolism-related AD subtypes and feature genes. METHODS: The AD datasets were obtained from the Gene Expression Omnibus database and the metabolism-relevant genes were downloaded from a previously published compilation. Consensus clustering was performed to identify the AD subclasses. The clinical characteristics, correlations with metabolic signatures, and immune infiltration of the AD subclasses were evaluated. Feature genes were screened using weighted correlation network analysis (WGCNA) and processed via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Furthermore, three machine-learning algorithms were used to narrow down the selection of the feature genes. Finally, we identified the diagnostic value and expression of the feature genes using the AD dataset and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) analysis. RESULTS: Three AD subclasses were identified, namely Metabolism Correlated (MC) A (MCA), MCB, and MCC subclasses. MCA contained signatures associated with high AD progression and may represent a high-risk subclass compared with the other two subclasses. MCA exhibited a high expression of genes related to glycolysis, fructose, and galactose metabolism, whereas genes associated with the citrate cycle and pyruvate metabolism were downregulated and associated with high immune infiltration. Conversely, MCB was associated with citrate cycle genes and exhibited elevated expression of immune checkpoint genes. Using WGCNA, 101 metabolic genes were identified to exhibit the strongest association with poor AD progression. Finally, the application of machine-learning algorithms enabled us to successfully identify eight feature genes, which were employed to develop a nomogram model that could bring distinct clinical benefits for patients with AD. As indicated by the AD datasets and qRT-PCR analysis, these genes were intimately associated with AD progression. CONCLUSION: Metabolic dysfunction is associated with AD. Hypothetical molecular subclasses of AD based on metabolic genes may provide new insights for developing individualized therapy for AD. The feature genes highly correlated with AD progression included GFAP, CYB5R3, DARS, KIAA0513, EZR, KCNC1, COLEC12, and TST.

Light-sheet microscopy in the near-infrared II window.

Non-invasive deep-tissue three-dimensional optical imaging of live mammals with high spatiotemporal resolution is challenging owing to light scattering. We developed near-infrared II (1,000-1,700 nm) light-sheet microscopy with excitation and emission of up to approximately 1,320 nm and 1,700 nm, respectively, for optical sectioning at a penetration depth of approximately 750 µm through live tissues without invasive surgery and at a depth of approximately 2 mm in glycerol-cleared brain tissues. Near-infrared II light-sheet microscopy in normal and oblique configurations enabled in vivo imaging of live mice through intact tissue, revealing abnormal blood flow and T-cell motion in tumor microcirculation and mapping out programmed-death ligand 1 and programmed cell death protein 1 in tumors with cellular resolution. Three-dimensional imaging through the intact mouse head resolved vascular channels between the skull and brain cortex, and allowed monitoring of recruitment of macrophages and microglia to the traumatic brain injury site.

Bright NIR-II Photoluminescence in Rod-Shaped Icosahedral Gold Nanoclusters.

Fluorophores with high quantum yields, extended maximum emission wavelengths, and long photoluminescence (PL) lifetimes are still lacking for sensing and imaging applications in the second near-infrared window (NIR-II). In this work, a series of rod-shaped icosahedral nanoclusters with bright NIR-II PL, quantum yields up to ≈8%, and a peak emission wavelength of 1520 nm are reported. It is found that the bright NIR-II emission arises from a previously ignored state with near-zero oscillator strength in the ground-state geometry and the central Au atom in the nanoclusters suppresses the non-radiative transitions and enhances the overall PL efficiency. In addition, a framework is developed to analyze and relate the underlying transitions for the absorptions and the NIR-II emissions in the Au nanoclusters based on the experimentally defined absorption coefficient. Overall, this work not only shows good performance of the rod-shaped icosahedral series of Au nanoclusters as NIR-II fluorophores, but also unravels the fundamental electronic transitions and atomic-level structure-property relations for the enhancement of the NIR-II PL in gold nanoclusters. The framework developed here also provides a simple method to analyze the underlying electronic transitions in metal nanoclusters.

Bright quantum dots emitting at ∼1,600 nm in the NIR-IIb window for deep tissue fluorescence imaging.

With suppressed photon scattering and diminished autofluorescence, in vivo fluorescence imaging in the 1,500- to 1,700-nm range of the near-IR (NIR) spectrum (NIR-IIb window) can afford high clarity and deep tissue penetration. However, there has been a lack of NIR-IIb fluorescent probes with sufficient brightness and aqueous stability. Here, we present a bright fluorescent probe emitting at ∼1,600 nm based on core/shell lead sulfide/cadmium sulfide (CdS) quantum dots (CSQDs) synthesized in organic phase. The CdS shell plays a critical role of protecting the lead sulfide (PbS) core from oxidation and retaining its bright fluorescence through the process of amphiphilic polymer coating and transferring to water needed for imparting aqueous stability and compatibility. The resulting CSQDs with a branched PEG outer layer exhibited a long blood circulation half-life of 7 hours and enabled through-skin, real-time imaging of blood flows in mouse vasculatures at an unprecedented 60 frames per second (fps) speed by detecting ∼1,600-nm fluorescence under 808-nm excitation. It also allowed through-skin in vivo confocal 3D imaging of tumor vasculatures in mice with an imaging depth of ∼1.2 mm. The PEG-CSQDs accumulated in tumor effectively through the enhanced permeation and retention effect, affording a high tumor-to-normal tissue ratio up to ∼32 owing to the bright ∼1,600-nm emission and nearly zero autofluorescence background resulting from a large ∼800-nm Stoke's shift. The aqueous-compatible CSQDs are excreted through the biliary pathway without causing obvious toxicity effects, suggesting a useful class of ∼1,600-nm emitting probes for biomedical research.

Breaking 50 Femtosecond Resolution Barrier in MeV Ultrafast Electron Diffraction with a Double Bend Achromat Compressor.

We propose and demonstrate a novel scheme to produce ultrashort and ultrastable MeV electron beam. In this scheme, the electron beam produced in a photocathode radio frequency (rf) gun first expands under its own Coulomb force with which a positive energy chirp is imprinted in the beam longitudinal phase space. The beam is then sent through a double bend achromat with positive longitudinal dispersion where electrons at the bunch tail with lower energies follow shorter paths and thus catch up with the bunch head, leading to longitudinal bunch compression. We show that with optimized parameter sets, the whole beam path from the electron source to the compression point can be made isochronous such that the time of flight for the electron beam is immune to the fluctuations of rf amplitude. With a laser-driven THz deflector, the bunch length and arrival time jitter for a 20 fC beam after bunch compression are measured to be about 29 fs (FWHM) and 22 fs (FWHM), respectively. Such an ultrashort and ultrastable electron beam allows us to achieve 50 femtosecond (FWHM) resolution in MeV ultrafast electron diffraction where lattice oscillation at 2.6 THz corresponding to Bismuth A_{1g} mode is clearly observed without correcting both the short-term timing jitter and long-term timing drift. Furthermore, oscillating weak diffuse scattering signal related to phonon coupling and decay is also clearly resolved thanks to the improved temporal resolution and increased electron flux. We expect that this technique will have a strong impact in emerging ultrashort electron beam based facilities and applications.

Molecular imaging of biological systems with a clickable dye in the broad 800- to 1,700-nm near-infrared window.

Fluorescence imaging multiplicity of biological systems is an area of intense focus, currently limited to fluorescence channels in the visible and first near-infrared (NIR-I; ∼700-900 nm) spectral regions. The development of conjugatable fluorophores with longer wavelength emission is highly desired to afford more targeting channels, reduce background autofluorescence, and achieve deeper tissue imaging depths. We have developed NIR-II (1,000-1,700 nm) molecular imaging agents with a bright NIR-II fluorophore through high-efficiency click chemistry to specific molecular antibodies. Relying on buoyant density differences during density gradient ultracentrifugation separations, highly pure NIR-II fluorophore-antibody conjugates emitting ∼1,100 nm were obtained for use as molecular-specific NIR-II probes. This facilitated 3D staining of ∼170-µm histological brain tissues sections on a home-built confocal microscope, demonstrating multicolor molecular imaging across both the NIR-I and NIR-II windows (800-1,700 nm).

Cross-Link-Functionalized Nanoparticles for Rapid Excretion in Nanotheranostic Applications.

Most NIR-IIb fluorophores are nanoparticle-based probes with long retention (≈1 month or longer) in the body. Here, we applied a novel cross-linked coating to functionalize core/shell lead sulfide/cadmium sulfide quantum dots (PbS/CdS QDs) emitting at ≈1600 nm. The coating was comprised of an amphiphilic polymer followed by three crosslinked amphiphilic polymeric layers (P3 coating), imparting high biocompatibility and >90 % excretion of QDs within 2 weeks of intravenous administration. The P3 -QDs were conjugated to an engineered anti-CD8 diabody (Cys-diabody) for in vivo molecular imaging of CD8+ cytotoxic T lymphocytes (CTLs) in response to anti-PD-L1 therapy. Two-plex molecular imaging in combination with down-conversion Er nanoparticles (ErNPs) was performed for real-time in vivo monitoring of PD-L1 positive tumor cells and CTLs with cellular resolution by non-invasive NIR-IIb light sheet microscopy. Imaging of angiogenesis in the tumor microenvironment and of lymph nodes deep in the body with a signal-to-background ratio of up to ≈170 was also achieved using P3 -QDs.

Donor Engineering for NIR-II Molecular Fluorophores with Enhanced Fluorescent Performance.

Organic fluorophores have been widely used for biological imaging in the visible and the first near-infrared windows. However, their application in the second near-infrared window (NIR-II, 1000-1700 nm) is still limited mainly due to low fluorescence quantum yields (QYs). Here, we explore molecular engineering on the donor unit to develop high performance NIR-II fluorophores. The fluorophores are constructed by a shielding unit-donor(s)-acceptor-donor(s)-shielding unit structure. Thiophene is introduced as the second donor connected to the shielding unit, which can increase the conjugation length and red-shift the fluorescence emission. Alkyl thiophene is employed as the first donor connected to the acceptor unit. The bulky and hydrophobic alkyl thiophene donor affords larger distortion of the conjugated backbone and fewer interactions with water molecules compared to other donor units studied before. The molecular fluorophore IR-FTAP with octyl thiophene as the first donor and thiophene as the second donor exhibits fluorescence emission peaked at 1048 nm with a QY of 5.3% in aqueous solutions, one of the highest for molecular NIR-II fluorophore reported so far. Superior temporal and spatial resolutions have been demonstrated with IR-FTAP fluorophore for NIR-II imaging of the blood vessels of a mouse hindlimb.

Near-Infrared IIb Fluorescence Imaging of Vascular Regeneration with Dynamic Tissue Perfusion Measurement and High Spatial Resolution.

Real-time optical imaging is a promising approach for visualizing in vivo hemodynamics and vascular structure in mice with experimentally induced peripheral arterial disease (PAD). We report the application of a novel fluorescence-based all-optical imaging approach in the near-infrared IIb (NIR-IIb, 1500-1700 nm emission) window, for imaging hindlimb microvasculature and blood perfusion in a mouse model of PAD. In phantom studies, lead sulfide/cadmium sulfide (PbS/CdS) quantum dots showed better retention of image clarity, in comparison with single-walled nanotube (SWNT) NIR-IIa (1000-1400nm) dye, at varying depths of penetration. When systemically injected to mice, PbS/CdS demonstrated improved clarity of the vasculature, compared to SWNTs, as well as higher spatial resolution than in vivo microscopic computed tomography. In a mouse model of PAD, NIR-IIb imaging of the ischemic hindlimb vasculature showed significant improvement in blood perfusion over the course of 10 days (P<0.05), as well as a significant increase in microvascular density over the first 7 days after induction of PAD. In conclusion, NIR-IIb imaging of PbS/CdS vascular contrast agent is a useful multi-functional imaging approach for high spatial resolution imaging of the microvasculature and quantification of blood perfusion recovery.

Developing a Bright NIR-II Fluorophore with Fast Renal Excretion and Its Application in Molecular Imaging of Immune Checkpoint PD-L1.

Fluorescence imaging in the second near-infrared (NIR-II) window holds impressive advantages of enhanced penetration depth and improved signal-to-noise ratio. Bright NIR-II fluorophores with renal excretion ability and low tissue accumulation are favorable for in vivo molecular imaging applications as they can render the target-mediated molecular imaging process easily distinguishable. Here, a probe (anti-PD-L1-BGP6) comprising a fluorophore (IR-BGP6) covalently bonded to the programmed cell death ligand-1 monoclonal antibody (PD-L1 mAb) for molecular imaging of immune checkpoint PD-L1 (a targeting site upregulated in various tumors for cancer imaging) in the NIR-II window is reported. Through molecular optimization, the bright NIR-II fluorophore IR-BGP6 with fast renal excretion (≈91% excretion in general through urine within the first 10 h postinjection) is developed. The conjugate anti-PD-L1-BGP6 succeeds in profiling PD-L1 expression and realizes efficient noninvasive molecular imaging in vivo, achieving a tumor to normal tissue (T/NT) signal ratio as high as ≈9.5. Compared with the NIR-II fluorophore with high nonspecific tissue accumulation, IR-BGP6 derived PD-L1 imaging significantly enhances the molecular imaging performance, serving as a strong tool for potentially studying underlying mechanism of immunotherapy. The work provides rationales to design renal-excreted NIR-II fluorophores and illustrate their advantages for in vivo molecular imaging.

Pido: Predictive Delay Optimization for Intertidal Wireless Sensor Networks.

Intertidal habitats are among the harshest environments on the planet, and have emerged as a model system for exploring the ecological impacts of global climate change. Deploying reliable instrumentation to measure environmental conditions such as temperature is challenging in this environment. The application of wireless sensor networks (WSNs) shows considerable promise as a means of optimizing continuous data collection, but poor link quality and unstable connections between nodes, caused by harsh physical environmental conditions, bring about a delay problem. In this paper, we model and analyze the components of delays in an intertidal wireless sensor network system (IT-WSN). We show that, by properly selecting routing pathways, it is feasible to improve delay. To this end, we propose a Predictive Delay Optimization (Pido) framework, which provides a new metric for routing path selection. Pido incorporates delay introduced by both link quality and node conditions, and designs a classifier to predict future conditions of nodes, i.e., the likely time of aerial exposure at low tide in this case. We evaluate the performance of Pido in both a real IT-WSN system and a large-scale simulation, the result demonstrates that Pido decreases up to 73% of delays on average with limited overhead.

Hydrogen sulfide detection based on reflection: from a poison test approach of ancient China to single-cell accurate localization.

With the inspiration of an ancient Chinese poison test approach, we report a rapid hydrogen sulfide detection strategy in specific areas of live cells using silver needles with good spatial resolution of 2 × 2 µm(2). Besides the accurate-localization ability, this reflection-based strategy also has attractive merits of convenience and robust response when free pretreatment and short detection time are concerned. The success of endogenous H2S level evaluation in cellular cytoplasm and nuclear of human A549 cells promises the application potential of our strategy in scientific research and medical diagnosis.

Identification and experimental validation of m7G-related molecular subtypes, immune signature, and feature genes in Alzheimer's disease.

Background: Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored. Methods: The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses. Results: Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes (AEBP1, CARTPT, AK5, NPTX2, and COPG2IT1) were identified, which were used to construct a nomogram model with good ability to predict AD. The animal experiment analyses further confirmed that these feature genes were associated with AD development. Conclusion: To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.