Photothermal Nanomaterials: A Powerful Light-to-Heat Converter.

All forms of energy follow the law of conservation of energy, by which they can be neither created nor destroyed. Light-to-heat conversion as a traditional yet constantly evolving means of converting light into thermal energy has been of enduring appeal to researchers and the public. With the continuous development of advanced nanotechnologies, a variety of photothermal nanomaterials have been endowed with excellent light harvesting and photothermal conversion capabilities for exploring fascinating and prospective applications. Herein we review the latest progresses on photothermal nanomaterials, with a focus on their underlying mechanisms as powerful light-to-heat converters. We present an extensive catalogue of nanostructured photothermal materials, including metallic/semiconductor structures, carbon materials, organic polymers, and two-dimensional materials. The proper material selection and rational structural design for improving the photothermal performance are then discussed. We also provide a representative overview of the latest techniques for probing photothermally generated heat at the nanoscale. We finally review the recent significant developments of photothermal applications and give a brief outlook on the current challenges and future directions of photothermal nanomaterials.

A Multilayered Mesoporous Gold Nanoarchitecture for Ultraeffective Near-Infrared Light-Controlled Chemo/Photothermal Therapy for Cancer Guided by SERS Imaging.

Surface-enhanced Raman scattering (SERS) imaging has emerged as a promising tool for guided cancer diagnosis and synergistic therapies, such as combined chemotherapy and photothermal therapy (chemo-PTT). Yet, existing therapeutic agents often suffer from low SERS sensitivity, insufficient photothermal conversion, or/and limited drug loading capacity. Herein, a multifunctional theragnostic nanoplatform consisting of mesoporous silica-coated gold nanostar with a cyclic Arg-Gly-Asp (RGD)-coated gold nanocluster shell (named RGD-pAS@AuNC) is reported that exhibits multiple "hot spots" for pronouncedly enhanced SERS signals and improved near-infrared (NIR)-induced photothermal conversion efficiency (85.5%), with a large capacity for high doxorubicin (DOX) loading efficiency (34.1%, named RGD/DOX-pAS@AuNC) and effective NIR-triggered DOX release. This nanoplatform shows excellent performance in xenograft tumor model of HeLa cell targeting, negligible cytotoxicity, and good stability both in vitro and in vivo. By SERS imaging, the optimal temporal distribution of injected RGD/DOX-pAS@AuNCs at the tumor site is identified for NIR-triggered local chemo-PTT toward the tumor, achieving ultraeffective therapy in tumor cells and tumor-bearing mouse model with 5 min of NIR irradiation (0.5 W cm-2 ). This work offers a promising approach to employing SERS imaging for effective noninvasive tumor treatment by on-site triggered chemo-PTT.

Chiral Gold Nanorods with Five-Fold Rotational Symmetry and Orientation-Dependent Chiroptical Properties of Their Monomers and Dimers.

Chiral plasmonic nanoparticles have attracted much attention because of their strong chiroptical responses and broad scientific applications. However, the types of chiral plasmonic nanoparticles have remained limited. Herein we report on a new type of chiral nanoparticle, chiral Au nanorod (NR) with five-fold rotational symmetry, which is synthesized using chiral molecules. Three different types of Au seeds (Au elongated nanodecahedrons, nanodecahedrons, and nanobipyramids) are used to study the growth behaviors. Different synthesis parameters, including the chiral molecules, surfactant, reductant, seeds, and Au precursor, are systematically varied to optimize the chiroptical responses of the chiral Au NRs. The chiral scattering measurements on the individual chiral Au NRs and their dimers are performed. Intriguingly, the chiroptical signals of the individual chiral Au NRs and their end-to-end dimers are similar, while those of the side-by-side dimers are largely reduced. Theoretical calculations and numerical simulations reveal that the different chiroptical responses of the chiral NR dimers are originated from the coupling effect between the plasmon resonance modes. Our study enriches chiral plasmonic nanoparticles and provides valuable insight for the design of plasmonic nanostructures with desired chiroptical properties.

Smooth graph learning for functional connectivity estimation.

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) signals is important in understanding neural representation and information processing in cortical networks. However, due to a lack of "ground truth" FC pattern, the reliability and robustness of FC estimates are usually examined in downstream FC analysis tasks, such as performing participant's identification (also known as "fingerprinting"). In this paper, we propose to learn FC via a smooth graph learning framework. In particular, we treat each time frame of the fMRI time series as a graph signal on an underlying functional brain graph, and estimate the smooth graph functional connectivity (SGFC) by learning the weighted graph adjacency matrix based on graph signal smoothness assumption. We demonstrate that our approach gives rise to a natural and sparse graph representation of FC from which reliable graph measures can be extracted. Reliability of SGFC is evaluated in the context of fingerprinting and compared to correlation FC (CFC). SGFC achieves higher fingerprinting accuracy across several different experiment settings; the improvement is even more significant when a shorter fMRI scanning length is used for FC estimation. In addition to being reliable, we also validate the cognitive relevance of SGFC by using it to predict fluid intelligence. Finally, in evaluating topological measures of the sparse graph, SGFC reveals a more small-world and modular structure compared to CFC. Together, our results suggest that the smooth graph learning framework produces a naturally sparse, reliable, and cognitive-relevant representation of functional connectivity.

Rapid geometric feature signaling in the simulated spiking activity of a complete population of tactile nerve fibers.

Tactile feature extraction is essential to guide the dexterous manipulation of objects. The longstanding theory is that geometric features at each location of contact between hand and object are extracted from the spatial layout of the response of populations of tactile nerve fibers. However, recent evidence suggests that some features (e.g., edge orientation) are extracted very rapidly (<200 ms), casting doubt that this information relies on a spatial code, which ostensibly requires integrating responses over time. An alternative hypothesis is that orientation is conveyed in precise temporal spiking patterns. Here we simulate, using a recently developed and validated model, the responses of the two relevant subpopulations of tactile fibers from the entire human fingertip (~800 afferents) to edges indented into the skin. We show that edge orientation can be quickly (<50 ms) and accurately (<3°) decoded from the spatial pattern of activation across the afferent population, starting with the very first spike. Next, we implement a biomimetic decoder of edge orientation, consisting of a bank of oriented Gabor filters, designed to mimic the documented responses of cortical neurons. We find that the biomimetic approach leads to orientation decoding performance that approaches the limit set by optimal decoders and is actually more robust to changes in other stimulus features. Finally, we show that orientation signals, measured from single units in the somatosensory cortex of nonhuman primates (2 macaque monkeys, 1 female), follow a time course consistent with that of their counterparts in the nerve. We conclude that a spatial code is fast and accurate enough to support object manipulation. NEW & NOTEWORTHY The dexterous manipulation of objects relies on the rapid and accurate extraction of the objects' geometric features by the sense of touch. Here we simulate the responses of all the nerve fibers that innervate the fingertip when an edge is indented into the skin and characterize the time course over which signals about its orientation evolve in this neural population. We show that orientation can be rapidly and accurately decoded from the spatial pattern of afferent activation using spatial filters that mimic the response properties of neurons in cortical somatosensory neurons along a time course consistent with that observed in cortex. We conclude that the classical model of tactile feature extraction is rapid and accurate enough to support object manipulation.

The neural code for tactile roughness in the somatosensory nerves.

Roughness is the most salient perceptual dimension of surface texture but has no well-defined physical basis. We seek to determine the neural determinants of tactile roughness in the somatosensory nerves. Specifically, we record the patterns of activation evoked in tactile nerve fibers of anesthetized Rhesus macaques to a large and diverse set of natural textures and assess what aspect of these patterns of activation can account for psychophysical judgments of roughness, obtained from human observers. We show that perceived roughness is determined by the variation in the population response, weighted by fiber type. That is, a surface will feel rough to the extent that the activity varies across nerve fibers and varies across time within nerve fibers. We show that this variation-based neural code can account not only for magnitude estimates of roughness but also for roughness discrimination performance.NEW & NOTEWORTHY Our sense of touch endows us with an exquisite sensitivity to the microstructure of surfaces, the most salient aspect of which is roughness. We analyze the responses evoked in tactile fibers of monkeys by natural textures and compare them to judgments of roughness obtained for the same textures from human observers. We then describe how texture signals from three populations of nerve fibers are integrated to culminate in a percept of roughness.

Long-wavelength traveling waves of vasomotion modulate the perfusion of cortex.

Brain arterioles are active, multicellular complexes whose diameters oscillate at ∼ 0.1 Hz. We assess the physiological impact and spatiotemporal dynamics of vaso-oscillations in the awake mouse. First, vaso-oscillations in penetrating arterioles, which source blood from pial arterioles to the capillary bed, profoundly impact perfusion throughout neocortex. The modulation in flux during resting-state activity exceeds that of stimulus-induced activity. Second, the change in perfusion through arterioles relative to the change in their diameter is weak. This implies that the capillary bed dominates the hydrodynamic resistance of brain vasculature. Lastly, the phase of vaso-oscillations evolves slowly along arterioles, with a wavelength that exceeds the span of the cortical mantle and sufficient variability to establish functional cortical areas as parcels of uniform phase. The phase-gradient supports traveling waves in either direction along both pial and penetrating arterioles. This implies that waves along penetrating arterioles can mix, but not directionally transport, interstitial fluids.

Orientation-Dependent Interaction between the Magnetic Plasmons in Gold Nanocups and the Excitons in WS2 Monolayer and Multilayer.

The integration of two-dimensional transition metal dichalcogenides with plasmonic nanostructures is extremely attractive for the investigation of the resonance coupling between plasmons and excitons, which offers a framework for the study of cavity quantum electrodynamics and is of great potential for exploring diverse quantum technologies. Herein we report on the coupling between the magnetic plasmons supported by individual asymmetric Au nanocups and the excitons in WS2 monolayer and multilayer. Resonance coupling with the strength varying from weak to strong regimes is realized by adjusting the orientation of the individual Au nanocups on WS2 monolayer. Different energy detunings between the magnetic plasmons and the excitons are achieved by varying the size of the Au nanocup. The Rabi splitting energies extracted at zero detuning are up to 106 meV. The anticrossing feature is observed in the measured scattering spectra and simulated absorption spectra, which indicates that the resonance coupling between the magnetic plasmons in the Au nanocup and the excitons in WS2 monolayer enters the strongly coupled regime. A dependence of the coupling strength on the layer number is further observed when the Au nanocups are coupled with WS2 multilayer. Our study suggests a promising approach toward the realization of different coupling regimes in a simple hybrid system made of individual Au nanocups and two-dimensional materials.

Ignored microplastic sources from plastic bottle recycling.

The recovery and recycling of plastic products has increased dramatically in recent years as a strategy to achieve sustainable production and minimization of plastic pollution. However, the release of microplastics during plastic recycling has received little attention. We evaluated the generation and fate of microplastics in three typical facilities which make polyethylene terephthalate (PET) flakes using post-consumer PET bottles as raw material. Microplastics, 0.1- 5.0 mm in size, were detected in production wastewater at concentrations ranging from 23.43 ± 1.04 mg/L to 1836.37 ± 31.73 mg/L, while decreased to (8.13 ± 0.42-83.83 ± 0.93) mg/L in discharge effluent and (52,166 ± 2858-68,866 ± 2500) µg/g in sludge. Interestingly, the profiles of microplastics in samples from production wastewater, effluents, and sludge showed significant differences. Although, in all three compartments, the mass of microplastics increased, and the particle number decreased with increasing particle size. Overall, the removal ratio of total microplastics from the production wastewater was 53.47 ± 4.48% to 99.56 ± 0.02% in mass, and from 90.08 ± 0.82% to 99.56 ± 0.05% in quantity. The loss of microplastics from wastewater resulted in their concentration in sludge. Factors that influence the transfer of microplastics from wastewater to sludge should be identified and utilized to maintain a high level of removal and prevent leakage of these particles into the environment.

A CRISPR-Cas12a integrated SERS nanoplatform with chimeric DNA/RNA hairpin guide for ultrasensitive nucleic acid detection.

Background: CRISPR-Cas12a has been integrated with nanomaterial-based optical techniques, such as surface-enhanced Raman scattering (SERS), to formulate a powerful amplification-free nucleic acid detection system. However, nanomaterials impose steric hindrance to limit the accessibility of CRISPR-Cas12a to the narrow gaps (SERS hot spots) among nanoparticles (NPs) for producing a significant change in signals after nucleic acid detection. Methods: To overcome this restriction, we specifically design chimeric DNA/RNA hairpins (displacers) that can be destabilized by activated CRISPR-Cas12a in the presence of target DNA, liberating excessive RNA that can disintegrate a core-satellite nanocluster via toehold-mediated strand displacement for orchestrating a promising "on-off" nucleic acid biosensor. The core-satellite nanocluster comprises a large gold nanoparticle (AuNP) core surrounded by small AuNPs with Raman tags via DNA hybridization as an ultrabright Raman reporter, and its disassembly leads to a drastic decrease of SERS intensity as signal readouts. We further introduce a magnetic core to the large AuNPs that can facilitate their separation from the disassembled nanostructures to suppress the background for improving detection sensitivity. Results: As a proof-of-concept study, our findings showed that the application of displacers was more effective in decreasing the SERS intensity of the system and attained a better limit of detection (LOD, 10 aM) than that by directly using activated CRISPR-Cas12a, with high selectivity and stability for nucleic acid detection. Introducing magnetic-responsive functionality to our system further improves the LOD to 1 aM. Conclusion: Our work not only offers a platform to sensitively and selectively probe nucleic acids without pre-amplification but also provides new insights into the design of the CRISPR-Cas12a/SERS integrated system to resolve the steric hindrance of nanomaterials for constructing biosensors.

Hypertension Exacerbates Severity and Outcomes of COVID-19 in Elderly Patients: A Retrospective Observational Study.

OBJECTIVE: To evaluate the impact of hypertension on the clinical outcome of COVID-19 patients aged 60 years old and older. METHODS: This single-center retrospective cohort study enrolled consecutive COVID-19 patients aged 60 years old and older, who were admitted to Liyuan Hospital from January 1, 2020 to April 25, 2020. All included patients were divided into two groups: hypertension and nonhypertension group. The baseline demographic characteristics, laboratory test results, chest computed tomography (CT) images and clinical outcomes were collected and analyzed. The prognostic value of hypertension was determined using binary logistic regression. RESULTS: Among the 232 patients included in the analysis, 105 (45.3%) patients had comorbid hypertension. Compared to the nonhypertension group, patients in the hypertension group had higher neutrophil-to-lymphocyte ratios, red cell distribution widths, lactate dehydrogenase, high-sensitivity C-reactive protein, D-dimer and severity of lung lesion, and lower lymphocyte counts (all P<0.05). Furthermore, the hypertension group had a higher proportion of intensive care unit admissions [24 (22.9%) vs. 14 (11.0%), P=0.02) and deaths [16 (15.2%) vs. 3 (2.4%), P<0.001] and a significantly lower probability of survival (P<0.001) than the nonhypertension group. Hypertension (OR: 4.540, 95% CI: 1.203-17.129, P=0.026) was independently correlated with all-cause in-hospital death in elderly patients with COVID-19. CONCLUSION: The elderly COVID-19 patients with hypertension tend to have worse conditions at baseline than those without hypertension. Hypertension may be an independent prognostic factor of poor clinical outcome in elderly COVID-19 patients.

Assessment of peripheral neuropathy in type 2 diabetes by diffusion tensor imaging: A case-control study.

OBJECTIVES: This study aimed to evaluate diabetes peripheral neuropathy (DPN) by diffusion tensor imaging (DTI) and explore the correlation between DTI parameters and electrophysiological parameters. METHODS: We examined tibial nerve (TN) and common peroneal nerve (CPN) of 32 DPN patients and 23 healthy controls using T1-weighted magnetic resonance imaging and DTI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) of TN and CPN were measured and compared between groups. Spearman correlation coefficient was used to explore the relationship between DTI parameters and electrophysiology parameters in the DPN group. Diagnostic value was assessed by receiver operating characteristic (ROC) analysis. RESULTS: In the DPN group, FA was decreased (p < 0.0001) and MD and RD were increased (p < 0.05, p < 0.001) in the TN and CPN compared with the values of healthy control group. Moreover, in the DPN group, FA was positively correlated with motor nerve conduction velocity (MCV) (p < 0.0001), and both MD and RD were negatively correlated with MCV (p < 0.05, p < 0.001). However, there was no correlation between AD and any electrophysiological parameters. Among all DTI parameters, FA displayed the best diagnostic accuracy, with an area under the ROC curve of 0.882 in TN and 0.917 in CPN. CONCLUSION: FA and RD demonstrate appreciable diagnostic accuracy. Furthermore, they both have a moderate correlation with MCV.

Nanoengineering 2D Dendritic PdAgPt Nanoalloys with Edge-Enriched Active Sites for Enhanced Alcohol Electroxidation and Electrocatalytic Hydrogen Evolution.

Lots of research studies reveal that the surface atoms on the top/bottom facets of the nanosheets are the key features in enhancing electrocatalytic activity while the edge and corner sites of electrocatalysts often possess superior activity. Herein, we report 2D dendritic PdAgPt ternary nanoalloys with abundant crystal defects such as steps, twin boundary, and atomic holes, which can effectively work as catalytic active-sites. The morphology of PdAgPt nanoalloys can be regulated readily from dendritic nanosheets to nanowheels. Compared with binary Pd68Ag32 nanodendrites, Pd62Pt38 nanospheres, and Pt/C catalyst, the composition- and morphology-optimized Pd43Ag21Pt36 nanowheels exhibit the best mass/specific activity and stability for methanol/ethanol oxidation reaction (MOR/EOR). The mass peak current density for EOR/MOR of Pd43Ag21Pt36 is 7.08/3.50 times of the Pt/C catalyst. Simultaneously, the hydrogen evolution reaction performance of the Pd43Ag21Pt36 nanowheels in terms of the lowest overpotential of 9 mv at a current density of 10 mA/cm2 and high electrochemical stability is much better than that of binary Pd68Ag32 nanodendrites, Pd62Pt38 nanospheres, and Pt/C.