Deep-learning-augmented microscopy for super-resolution imaging of nanoparticles.

Conventional optical microscopes generally provide blurry and indistinguishable images for subwavelength nanostructures. However, a wealth of intensity and phase information is hidden in the corresponding diffraction-limited optical patterns and can be used for the recognition of structural features, such as size, shape, and spatial arrangement. Here, we apply a deep-learning framework to improve the spatial resolution of optical imaging for metal nanostructures with regular shapes yet varied arrangement. A convolutional neural network (CNN) is constructed and pre-trained by the optical images of randomly distributed gold nanoparticles as input and the corresponding scanning-electron microscopy images as ground truth. The CNN is then learned to recover reversely the non-diffracted super-resolution images of both regularly arranged nanoparticle dimers and randomly clustered nanoparticle multimers from their blurry optical images. The profiles and orientations of these structures can also be reconstructed accurately. Moreover, the same network is extended to deblur the optical images of randomly cross-linked silver nanowires. Most sections of these intricate nanowire nets are recovered well with a slight discrepancy near their intersections. This deep-learning augmented framework opens new opportunities for computational super-resolution optical microscopy with many potential applications in the fields of bioimaging and nanoscale fabrication and characterization. It could also be applied to significantly enhance the resolving capability of low-magnification scanning-electron microscopy.

Distortion-free amplification of 100†GHz mode-locked optical frequency comb using quantum dot technology.

Semiconductor mode-locked optical frequency comb (ML-OFC) sources with extremely high repetition rates are central to many high-frequency applications, such as dense wavelength-division multiplexing. Dealing with distortion-free amplification of ultra-fast pulse trains from such ML-OFC sources in high-speed data transmission networks requires the deployment of semiconductor optical amplifiers (SOAs) with ultrafast gain recovery dynamics. Quantum dot (QD) technology now lies at the heart of many photonic devices/systems owing to their unique properties at the O-band, including low alpha factor, broad gain spectrum, ultrafast gain dynamics, and pattern-effect free amplification. In this swork, we report on ultrafast and pattern-free amplification of ∼100 GHz pulsed trains from a passively ML-OFC and up to 80 Gbaud/s non-return-to-zero (NRZ) data transmission using an SOA. Most significantly, both key photonic devices presented in this work are fabricated from identical InAs/GaAs QD materials operating at O-band, which paves the way for future advanced photonic chips, where ML-OFCs could be monolithically integrated with SOAs and other photonic components, all originated from the same QD-based epi-wafer.

MXene-based chemical gas sensors: Recent developments and challenges.

The long-running Covid-19 pandemic has forced researchers across the globe to develop novel sensors and sensor materials for detecting minute quantities of biogenic viruses with high accuracy in a short period. In this context, MXene galleries comprising carbon/nitride two-dimensional nanolayered materials have emerged as excellent host materials in chemical gas sensors owing to their multiple advantages, including high surface area, high electrical conductivity, good thermal/chemical conductivity and chemical stability, composition diversity, and layer-spacing tunability; furthermore, they are popular in clinical, medical, food production, and chemical industries. This review summarizes recent advances in the synthesis, structure, and gas-sensing properties of MXene materials. Current opportunities and future challenges for obtaining MXene-based chemical gas sensors with high sensitivity, selectivity, response/recovery time, and chemical durability are addressed. This review provides a rational and in-depth understanding of the relationship between the gas-sensing properties of MXenes and structure/components, which will promote the further development of two-dimensional MXene-based gas sensors for technical device fabrication and industrial processing applications.

Plasmoelectric Potential in Plasmon-Mediated Electrochemistry.

Plasmon-mediated chemical reactions have attracted intensive research interest as a means of achieving desirable reaction yields and selectivity. The energetic charge carriers and elevated local temperature induced by the nonradiative decay of surface plasmons are thought to be responsible for improving reaction outcomes. This study reports that the plasmoelectric potential is another key contributor in plasmon-mediated electrochemistry. Additionally, we disclose a convenient and reliable method for quantifying the specific contributions of the plasmoelectric potential, hot electrons, and photothermal heating to the electroreduction of oxygen at the plasmonic Ag electrode, revealing that the plasmoelectric potential is the dominating nonthermal factor under short-wavelength illumination and moderate electrode bias. This work elucidates novel mechanistic understandings of plasmon-mediated electrochemistry, facilitating high-performance plasmonic electrocatalyst design optimization.

Using Aggregation to Chaperone Nanoparticles Across Fluid Interfaces.

Nanoparticles (NPs) transfer is usually induced by adding ligands to modify NP surfaces, but aggregation of NPs oftentimes hampers the transfer. Here, we show that aggregation during NP phase transfer does not necessarily result in transfer failure. Using a model system comprising gold NPs and amphiphilic polymers, we demonstrate an unusual mechanism by which NPs can undergo phase transfer from the aqueous phase to the organic phase via a single-aggregation-single pathway. Our discovery challenges the conventional idea that aggregation inhibits NP transfer and provides an unexpected pathway for transferring larger-sized NPs (>20 nm). The charged amphiphilic polymers effectively act as chaperons for the NP transfer and offer a unique way to manipulate the dispersion and distribution of NPs in two immiscible liquids. Moreover, by intentionally jamming the NP-polymer assembly at the liquid/liquid interface, the transfer process can be inhibited.

Extracellular vesicle-mediated transfer of lncRNA CLDN10-AS1 aggravates low-density lipoprotein-induced vascular endothelial injury.

Oxidized low-density lipoprotein (ox-LDL) stimulation impairs the oxidation-reduction equilibrium in vascular endothelial cells (VECs) and contributes to atherosclerosis (AS). This study probed the mechanisms of extracellular vesicle (EV)-mediated transfer of lncRNA CLDN10 antisense RNA 1 (CLDN10-AS1) in ox-LDL-induced VEC injury. Initially, VEC injury models were established by treating human umbilical vein endothelial cells (HUVECs) with ox-LDL. EVs were isolated from HUVECs (HUVECs-EVs) and identified. CLDN10-AS1, microRNA (miR)-186, and Yin Yang 1 (YY1) expressions in ox-LDL-treated HUVECs and EVs derived from these cells (ox-EVs) were measured. HUVECs were incubated with EVs, after which the cell viability, apoptosis, and concentrations of proinflammatory cytokines and oxidative stress markers were measured. We discovered that CLDN10-AS1 and YY1 were upregulated in ox-LDL-treated HUVECs, whereas miR-186 was downregulated. ox-EVs treatment elevated CLDN10-AS1 expression in HUVECs and ox-EVs overexpressing CLDN10-AS1 promoted VEC injury. Besides, CLDN10-AS1 is competitively bound to miR-186 and promoted YY1 expression. Rescue experiments revealed that miR-186 overexpression or YY1 suppression partially reversed the roles of ox-EVs overexpressing CLDN10-AS1 in ox-LDL-induced VEC injury. Lastly, clinical serum samples were collected for verification. Overall, CLDN10-AS1 carried by HUVECs-EVs into HUVECs competitively bound to miR-186 to elevate YY1 expression, thereby aggravating ox-LDL-induced VEC injury.

Enhanced Electrochemical O2 -to-H2 O2 Synthesis Via Cu-Pb Synergistic Interplay.

Electrocatalytic reduction of oxygen (O2 ) to produce hydrogen peroxide (H2 O2 ) frequently suffers from the low activity and poor selectivity of catalysts owing to the lack of systematic strategies. The resulting enhancement to enable the further design of a new bimetallic catalyst with the synergistic interplay, as exemplified by Cu-Pb catalyst for two-electron oxygen reduction reaction (2e- ORR), is reported here. Critically, in-depth evidence, including density functional theory (DFT) calculations, electrochemical signals, in-situ Raman, and H2 O2 -proof work, allude to a catalytic favor to the 2e- ORR of Cu-Pb.

Strain-Modulated Seeded Growth of Highly Branched Black Au Superparticles for Efficient Photothermal Conversion.

Creating highly branched plasmonic superparticles can effectively induce broadband light absorption and convert light to heat regardless of the light wavelength, angle, and polarization. However, their direct synthesis in a controllable manner remains a significant challenge. In this work, we propose a strain modulation strategy to produce branched Au nanostructures that promotes the growth of Au on Au seeds in the Volmer-Weber (island) mode instead of the typical Frank-van der Merwe (layer-by-layer) mode. The key to this strategy is to continuously deposit polydopamine formed in situ on the growing surface of the seeds to increase the chemical potential of the subsequent deposition of Au, thus achieving continuous heterogeneous nucleation and growth. The branched Au superparticles exhibit a photothermal conversion efficiency of 91.0% thanks to their small scattering cross-section and direction-independent absorption. Even at a low light power of 0.5 W/cm2 and a low dosage of 25 ppm, these particles show an excellent efficacy in photothermal cancer therapy. This work provides the fundamental basis for designing branched plasmonic nanostructures and expands the application scope of the plasmonic photothermal effect.

Analysis of ultrasonic imaging changes and factors related to malignant transformation in postmenopausal patients with endometrial polyps.

OBJECTIVE: To examine the ultrasonic changes in postmenopausal endometrial polyps and analyze factors related to their malignant transformation. METHODS: This retrospective study analyzed clinical data from 200 postmenopausal patients with endometrial polyps treated at Jinan Maternity and Child Care Hospital and Pingyin Hospital of Traditional Chinese Medicine from December 2020 to December 2023. All patients underwent pathological biopsies to diagnose the nature of the endometrial polyps. This study compared the clinical and ultrasonic imaging features of these patients and analyzed factors influencing the malignant transformation of postmenopausal endometrial polyps. RESULTS: Pathological findings classified 160 patients (80.00%) into the benign group and 40 patients (20.00%) into the malignant group. Significant differences were noted in endometrial thickness, polyp diameter, heterogeneity of lesion echogenicity, and vascularization between the groups (all P<0.05). The malignant group exhibited notably higher blood flow (Grade II+III constituted 70.00% compared to 29.38% in the benign group, P<0.05). The time average velocity (TAV), pulse index (PI), and resistance index (RI) were significantly lower in the malignant group (all P<0.05). The area under curve (AUC) values for TAV, PI, and RI in diagnosing malignant endometrial polyps were 0.754, 0.713, and 0.771, respectively. Increased body mass index (BMI), irregular premenopausal menstruation, and ≥2 occurrences of postmenopausal bleeding were identified as risk factors for malignant transformation (all P<0.05). These six indicators were used to create a predictive model for malignant transformation, achieving an AUC of 0.942. CONCLUSION: Malignancy in postmenopausal endometrial polyps is uncommon, yet distinct differences exist in the transvaginal color Doppler ultrasound characteristics between benign and malignant cases. Factors such as increased BMI, irregular premenopausal menstruation, and ≥2 occurrences of postmenopausal bleeding significantly contribute to the risk of malignant transformation. These findings, combined with ultrasound features, provide a robust basis for screening and monitoring these patients.

Adherence to the EAT-Lancet diet and incident depression and anxiety.

High-quality diets have been increasingly acknowledged as a promising candidate to counter the growing prevalence of mental health disorders. This study aims to investigate the prospective associations of adhering to the EAT-Lancet reference diet with incident depression, anxiety and their co-occurrence in 180,446 UK Biobank participants. Degrees of adherence to the EAT-Lancet diet were translated into three different diet scores. Over 11.62 years of follow-up, participants in the highest adherence group of the Knuppel EAT-Lancet index showed lower risks of depression (hazard ratio: 0.806, 95% CI: 0.730-0.890), anxiety (0.818, 0.751-0.892) and their co-occurrence (0.756, 0.624-0.914), compared to the lowest adherence group. The corresponding hazard ratios (95% CIs) were 0.711 (0.627-0.806), 0.765 (0.687-0.852) and 0.659 (0.516-0.841) for the Stubbendorff EAT-Lancet index, and 0.844 (0.768-0.928), 0.825 (0.759-0.896) and 0.818 (0.682-0.981) for the Kesse-Guyot EAT-Lancet diet index. Our findings suggest that higher adherence to the EAT-Lancet diet is associated with lower risks of incident depression, anxiety and their co-occurrence.

Optimizing invasive plant biomass valorization: Deep eutectic solvents pre-treatment coupled with ZSM-5 catalyzed fast pyrolysis for superior bio-oil quality.

The primary objective of this study is to explore the application of a deep eutectic solvent, synthesized from lactic acid and choline chloride, in combination with a pre-treatment involving ZSM-5 catalytic fast pyrolysis, aimed at upgrading the quality of bio-oil. Characterization results demonstrate a reduction in lignin content post-treatment, alongside a significant decrease in carboxyls and carbonyls, leading to an increase in the C/O ratio and noticeable enhancement in crystallinity. During catalytic fast pyrolysis experiments, the pre-treatment facilitates the production of oil fractions, achieving yields of 54.53% for total hydrocarbons and 39.99% for aromatics hydrocarbons under optimized conditions. These findings validate the positive influence of the deep eutectic solvent pre-treatment combined with ZSM-5 catalytic fast pyrolysis on the efficient production of bio-oil and high-value chemical derivatives. .

Rapid fabrication of gold microsphere arrays with stable deep-pressing anisotropic conductivity for advanced packaging.

Smooth metal microspheres with uniform sizes are ideal for constructing particle-arrayed anisotropic conductive films (ACF), but synthesis is hindered by challenges in controlling anisotropic metal growth. Here, we present a positioned transient-emulsion self-assembly and laser-irradiation strategy to fabricate pure gold microsphere arrays with smooth surfaces and uniform sizes. The fabrication involves assembling gold nanoparticles into uniform colloidosomes within a pre-designed microhole array, followed by rapid transformation into well-defined microspheres through laser heating. The gold nanoparticles melt and merge in a layer-by-layer manner due to the finite skin depth of the laser, leading to a localized photothermal effect. This strategy circumvents anisotropic growth, enables tunable control of microsphere size and positioning, and is compatible with conventional lithography. Importantly, these pure gold microspheres exhibit stable conductivity under deep compression, offering promising applications in soldering micro-sized chips onto integrated circuits.

Monocular Metasurface for Structured Light Generation and 3D Imaging with a Large Field-of-View.

Structured light three-dimensional (3D) imaging technology captures the geometric information on 3D objects by recording waves reflected from the objects' surface. The projection angle and point number of the laser dots directly determine the field-of-view (FOV) and the resolution of the reconstructed image. Conventionally, diffractive optical elements with micrometer-scale pixel size have been used to generate laser dot arrays, leading to limited FOV and point number within the projection optical path. Here, we theoretically put forward and experimentally demonstrate a monocular geometric phase metasurface composed of deep subwavelength meta-atoms to generate a 10 798 dot array within an FOV of 163°. Attributed to the vast number and high-density point cloud generated by the metasurface, the 3D reconstructed results showcase a maximum relative error in depth of 5.3 mm and a reconstruction error of 6.07%. Additionally, we propose a spin-multiplexed metasurface design method capable of doubling the number of lattice points. We demonstrate its application in the field of 3D imaging through experiments, where the 3D reconstructed results show a maximum relative depth error of 0.44 cm and a reconstruction error of 2.78%. Our proposed metasurface featuring advanced point cloud generation holds substantial potential for various applications such as facial recognition, autonomous driving, virtual reality, and beyond.

Structured-Light 3D Imaging Based on Vector Iterative Fourier Transform Algorithm.

Quasi-continuous-phase metasurfaces overcome the side effects imposed by high-order diffraction on imaging and can impart optical parameters such as amplitude, phase, polarization, and frequency to incident light at sub-wavelength scales with high efficiency. Structured-light three-dimensional (3D) imaging is a hot topic in the field of 3D imaging because of its advantages of low computation cost, high imaging accuracy, fast imaging speed, and cost-effectiveness. Structured-light 3D imaging requires uniform diffractive optical elements (DOEs), which could be realized by quasi-continuous-phase metasurfaces. In this paper, we design a quasi-continuous-phase metasurface beam splitter through a vector iterative Fourier transform algorithm and utilize this device to realize structured-light 3D imaging of a target object with subsequent target reconstruction. A structured-light 3D imaging system is then experimentally implemented by combining the fabricated quasi-continuous-phase metasurface illuminated by the vertical-cavity surface-emitting laser and a binocular recognition system, which eventually provides a new technological path for the 3D imaging field.

Habitual Coffee, Tea, and Caffeine Consumption, Circulating Metabolites, and the Risk of Cardiometabolic Multimorbidity.

CONTEXT: Cardiometabolic multimorbidity (CM) is an increasing public health concern. Previous observational studies have suggested inverse associations between coffee, tea, and caffeine intake and risks of individual cardiometabolic diseases; however, their associations with CM and related biological markers are unknown. METHODS: This prospective study involved 172 315 (for caffeine analysis) and 188 091 (tea and coffee analysis) participants free of any cardiometabolic diseases at baseline from the UK Biobank; 168 metabolites were measured among 88 204 and 96 393 participants. CM was defined as the coexistence of at least 2 of the following conditions: type 2 diabetes, coronary heart disease, and stroke. RESULTS: Nonlinear inverse associations of coffee, tea, and caffeine intake with the risk of new-onset CM were observed. Compared with nonconsumers or consumers of less than 100 mg caffeine per day, consumers of moderate amount of coffee (3 drinks/d) or caffeine (200-300 mg/d) had the lowest risk for new-onset CM, with respective hazard ratios (95% CIs) of 0.519 (0.417-0.647) and 0.593 (0.499-0.704). Multistate models revealed that moderate coffee or caffeine intake was inversely associated with risks of almost all developmental stages of CM, including transitions from a disease-free state to single cardiometabolic diseases and subsequently to CM. A total of 80 to 97 metabolites, such as lipid components within very low-density lipoprotein, histidine, and glycoprotein acetyls, were identified to be associated with both coffee, tea, or caffeine intake and incident CM. CONCLUSION: Habitual coffee or caffeine intake, especially at a moderate level, was associated with a lower risk of new-onset CM and could play important roles in almost all transition phases of CM development. Future studies are warranted to validate the implicated metabolic biomarkers underlying the relation between coffee, tea, and caffeine intake and CM.

Self-Confined Dewetting Mechanism in Wafer-Scale Patterning of Gold Nanoparticle Arrays with Strong Surface Lattice Resonance for Plasmonic Sensing.

A self-confined solid-state dewetting mechanism is reported that can fundamentally reduce the use of sophisticated nanofabrication techniques, enabling efficient wafer-scale patterning of non-closely packed (ncp) gold nanoparticle arrays. When combined with a soft lithography process, this approach can address the reproducibility challenges associated with colloidal crystal self-assembly, allowing for the batch fabrication of ncp gold arrays with consistent ordering and even optical properties. The resulting dewetted ncp gold nanoparticle arrays exhibit strong surface lattice resonance properties when excited in inhomogeneous environments under normal white-light incidence. With these SLR properties, the sensitive plasmonic sensing of molecular interactions is achieved using a simple transmission setup. This study will advance the development of miniaturized and portable devices.

Quantifying depressive symptoms on incidence of common chronic diseases and multimorbidity patterns in middle-aged and elderly Chinese adults.

BACKGROUND: Depressive symptoms are highly prevalent and increase risks of various morbidities. However, the extent to which depressive symptoms could account for incidence of these chronic conditions, in particular multimorbidity patterns, remains to be examined and quantified. METHODS: For this cohort analysis, we included 9024-14,093 participants aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the longitudinal associations between depressive symptoms and 13 common chronic diseases and 4 multimorbidity patterns. Population attributable fractions (PAFs) combining the information on both exposure prevalence and risk association were estimated to quantify the magnitude of the burden of these conditions attributable to depressive symptoms. RESULTS: Depressive symptoms were associated with increased risks of liver disease, stroke, heart problem, asthma, diabetes, arthritis, kidney disease, chronic lung disease, digestive disease, dyslipidemia, and memory-related disease, and the adjusted HRs (95% CIs) and PAFs (95% CIs) ranged from 1.15 (1.05-1.26) to 1.64 (1.38-1.96) and 5% (0-10%) to 17% (6-28%), respectively. In addition, individuals with depressive symptoms had elevated risks of the cardiometabolic-cancer pattern, the cerebrovascular-memory pattern, the articular-visceral organ pattern, and the respiratory pattern, with respective HRs (95% CIs) of 1.26 (1.11-1.42), 1.34 (1.07-1.69), 1.45 (1.29-1.63), and 2.01 (1.36-2.96), and respective PAFs (95% CIs) of 5% (0-10%), 8% (-4-21%), 12% (7-17%), and 20% (5-35%). CONCLUSION: Depressive symptoms contribute substantially to the burden across a broad range of chronic diseases as well as different multimorbidity patterns in middle-aged and older Chinese.

Application of transposon insertion site sequencing method in the exploration of gene function in microalgae.

Microalgae are a large group of organisms that can produce various useful substances through photosynthesis. Microalgae need to be genetically modified at the molecular level to become "Chassis Cells" for food, medicine, energy, and environmental protection and, consequently, obtain benefits from microalgae resources. Insertional mutagenesis of microalgae using transposons is a practical possibility for understanding the function of microalgae genes. Theoretical and technical support is provided in this manuscript for applying transposons to microalgae gene function by summarizing the sequencing method of transposon insertion sites.

Double-sided plasmonic metasurface for simultaneous biomolecular separation and SERS detection.

Porous membrane-based nanofiltration separation of small biomolecules is a widely used biotechnology for which size-based selectivity is a critical parameter of technological relevance. Efficient determination of size selectivity calls for an advanced detection method capable of performing sensitive, rapid, and on-membrane examination. Surface-enhanced Raman spectroscopy (SERS) is such a detection method that has been widely recognized as an ultrasensitive technique for trace-level detection with sensitivity down to the single-molecule level. In this work, we for the first time develop a double-sided hierarchical porous membrane-like plasmonic metasurface to realize high-selectivity bimolecular separation and simultaneous ultrasensitive SERS detection. This highly flexible device, consisting of subwavelength nanocone pairs surrounded by randomly orientated sub-5 nm nanogrooves, was prepared by combining customized "top-down" fabrication of conical nanopores in an ion-track registered polycarbonate membrane and self-assembly of nanogrooves on the membrane surface through physical vapor deposition. The unique tip-to-tip oriented conical nanopores in the device enables excellent size-based molecular selectivity; the hierarchical groove-pore structure supports a peculiar cascaded electromagnetic near-field enhancement mechanism, endowing the device with SERS-based molecular detection of ultrahigh sensitivity, uniformity, repeatability, and polarization independence. With such dual structural merits and performance enhancement, we demonstrate effective nanofiltration separation of small-sized adenine from big-sized ss-DNA and synergistic SERS determination of their species. We experimentally demonstrate an ultrasensitive detection of 4-mercaptopyridine down to 10 pM. Together with its unparalleled mechanical flexibility, this double-side-responsive plasmonic metasurface membrane can find great potential in real-world molecular filtration and detection under extremely complex working conditions.

Super-resolution multicolor fluorescence microscopy enabled by an apochromatic super-oscillatory lens with extended depth-of-focus.

Planar super-oscillatory lens (SOL), a far-field subwavelength-focusing diffractive device, holds great potential for achieving sub-diffraction-limit imaging at multiple wavelengths. However, conventional SOL devices suffer from a numerical-aperture-related intrinsic tradeoff among the depth of focus (DoF), chromatic dispersion and focusing spot size. Here, we apply a multi-objective genetic algorithm (GA) optimization approach to design an apochromatic binary-phase SOL having a prolonged DoF, customized working distance (WD), minimized main-lobe size, and suppressed side-lobe intensity. Experimental implementation demonstrates simultaneous focusing of blue, green and red light beams into an optical needle of ~0.5λ in diameter and DOF > 10λ at WD = 428 µm. By integrating this SOL device with a commercial fluorescence microscope, we perform, for the first time, three-dimensional super-resolution multicolor fluorescence imaging of the "unseen" fine structures of neurons. The present study provides not only a practical route to far-field multicolor super-resolution imaging but also a viable approach for constructing imaging systems avoiding complex sample positioning and unfavorable photobleaching.