Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases

IMPORTANCE

The lack of experienced ophthalmologists limits the early diagnosis of retinal diseases. Artificial intelligence can be an efficient real-time way for screening retinal diseases.

OBJECTIVE

To develop and prospectively validate a deep learning (DL) algorithm that, based on ocular fundus images, recognizes numerous retinal diseases simultaneously in clinical practice.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter, diagnostic study at 65 public medical screening centers and hospitals in 19 Chinese provinces included individuals attending annual routine medical examinations and participants of population-based and community-based studies.

EXPOSURES

Based on 120 002 ocular fundus photographs, the Retinal Artificial Intelligence Diagnosis System (RAIDS) was developed to identify 10 retinal diseases. RAIDS was validated in a prospective collected data set, and the performance between RAIDS and ophthalmologists was compared in the data sets of the population-based Beijing Eye Study and the community-based Kailuan Eye Study.

MAIN OUTCOMES AND MEASURES

The performance of each classifier included sensitivity, specificity, accuracy, F1 score, and Cohen κ score.

RESULTS

In the prospective validation data set of 208 758 images collected from 110 784 individuals (median [range] age, 42 [8-87] years; 115 443 [55.3%] female), RAIDS achieved a sensitivity of 89.8% (95% CI, 89.5%-90.1%) to detect any of 10 retinal diseases. RAIDS differentiated 10 retinal diseases with accuracies ranging from 95.3% to 99.9%, without marked differences between medical screening centers and geographical regions in China. Compared with retinal specialists, RAIDS achieved a higher sensitivity for detection of any retinal abnormality (RAIDS, 91.7% [95% CI, 90.6%-92.8%]; certified ophthalmologists, 83.7% [95% CI, 82.1%-85.1%]; junior retinal specialists, 86.4% [95% CI, 84.9%-87.7%]; and senior retinal specialists, 88.5% [95% CI, 87.1%-89.8%]). RAIDS reached a superior or similar diagnostic sensitivity compared with senior retinal specialists in the detection of 7 of 10 retinal diseases (ie, referral diabetic retinopathy, referral possible glaucoma, macular hole, epiretinal macular membrane, hypertensive retinopathy, myelinated fibers, and retinitis pigmentosa). It achieved a performance comparable with the performance by certified ophthalmologists in 2 diseases (ie, age-related macular degeneration and retinal vein occlusion). Compared with ophthalmologists, RAIDS needed 96% to 97% less time for the image assessment.

CONCLUSIONS AND RELEVANCE

In this diagnostic study, the DL system was associated with accurately distinguishing 10 retinal diseases in real time. This technology may help overcome the lack of experienced ophthalmologists in underdeveloped areas.

Heart rate prediction from facial video with masks using eye location and corrected by convolutional neural networks

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications. The emergence of novel coronavirus pneumonia COVID-19 has attracted worldwide attentions. Contact photoplethysmography (cPPG) methods need to contact the detection equipment with the patient, which may accelerate the spread of the epidemic. In the future, the non-contact heart rate detection will be an urgent need. However, existing heart rate measuring methods from facial videos are vulnerable to the less-constrained scenarios (e.g., with head movement and wearing a mask). In this paper, we proposed a method of heart rate detection based on eye location of region of interest (ROI) to solve the problem of missing information when wearing masks. Besides, a model to filter outliers based on residual network was conceived first by us and the better heart rate measurement accuracy was generated. To validate our method, we also created a mask dataset. The results demonstrated that after using our method for correcting the heart rate (HR) value measured with the traditional method, the accuracy reaches 4.65 bpm, which is 0.42 bpm higher than that without correction.

Fabrication of Hierarchical Quaternary Architectures of Metal-Organic Frameworks through Programmed Transformation

A new method to construct hierarchical architectures has been developed by programmed transformation of metal-organic frameworks (MOFs). A MOF precursor was fabricated by reaction of Cu(OAC)₂ and 2,5-dihydroxyterephthalic acid (H₄DOBDC), which could perform transformation in pure methanol solvent and the sodium dodecyl benzene sulfonate (SDBS) solution of methanol, respectively. Interestingly, two kinds of immersion solutions could induce the transformation of the MOF precursor into MOF-74, which resulted in different morphologies: nanoneedles for the methanol and nanosheets for the SDBS. Herein, nanosheets-mesorods-microcuboid hierarchical quaternary architectures of MOF have been successfully achieved by sequential immersion of the precursor in two kinds of transformation solutions, which demonstrates well-defined hierarchy from the nanoscale to mesoscale to microscale. A unique hierarchical architecture could be recognized as quaternary structures, taking the MOF unit cell as the primary structure, the nanosheets as the secondary structure, the mesorods as the tertiary structure, and the microcuboid as the quaternary structure. Our study indicated the potential of programmed transformation between MOFs in the construction of hierarchical architectures, offering a new approach to sophisticated materials.

Numerical simulation of iron ore sintering process with coke oven gas injection and oxygen enrichment

Oxygen enrichment is believed to improve productivity and reduce fuel consumption, while gas fuel injection is assumed to improve the product yield and quality in iron ore sintering process. It is important to understand the mutual effect of oxygen enrichment and gas fuel injection for combined usage of these two techniques. A mathematical model is developed to simulate the sintering process with coke oven gas (COG) injection and oxygen enrichment, particularly focusing on predicting the quality and yield of sinter production, as well as NO x emission. The model is validated by comparing the model predictions with sintering pot test data, and numerical simulations are carried out to investigate the mutual effect of oxygen enrichment and COG injection. The results show that, compared with the conventional sintering process, with 0.5% COG injection and 30% oxygen enrichment, the mean melt quantity index (MQI) is increased by 4.1% and the mean cooling rate (CR) is decreased by 62.5%, showing that the sinter quality is improved significantly. The sinter yield is increased by 44.5%, whereas the NO x emission is increased by 8.3%. With the increase of oxygen enrichment from 21% to 30%, the sinter yield increases prominently first and then decreases a little, attaining its maximum at 30% of oxygen concentration. In addition, increasing oxygen concentration will increase the conversion rate of coke-N to NO x . Therefore, excessive oxygen enrichment is not only bad for sinter strength and yield, but also increases NO x emission.

Assembly of gold nanorods functionalized by zirconium-based metal-organic frameworks for surface enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) is a promising detection technique providing outstanding molecular fingerprint identification and high sensitivity of analytes. Developing sensitive and stable SERS substrates is highly desirable but remains a challenge. We herein report a wet-chemistry approach for the preparation of (Au nanorod core)@(Zr-based metal-organic framework shell) (Au nanorod@Zr-MOF) nanostructures with the Zr-MOF shell thickness ranging from 3 nm to 90 nm. The stacked Au nanorod@Zr-MOF composites exhibit remarkably improved SERS sensitivity because the MOF shell enriches the molecules to the abundant plasmonic hotspots between the Au nanorod cores. The optimized Au nanorod@Zr-MOF structures exhibit superior SERS activity for detecting 4'-mercaptobiphenylcarbonitrile molecules at a concentration as low as 2 × 10^-10 M, with the SERS enhancement factor 2 and 8 times as high as that of ordered bare Au nanorod arrays and random stacking bare Au nanorods, respectively. This study enriches the library of hybrid nanostructures of plasmonic nanocrystals and MOFs, providing an integrated SERS platform with molecular enrichment capability for the realization of sensitive and quantitative analyte identification.

Gut Microbiota Targeted Approach in the Management of Chronic Liver Diseases

The liver is directly connected to the intestines through the portal vein, which enables the gut microbiota and gut-derived products to influence liver health. There is accumulating evidence of decreased gut flora diversity and alcohol sensitivity in patients with various chronic liver diseases, including non-alcoholic/alcoholic liver disease, chronic hepatitis virus infection, primary sclerosing cholangitis and liver cirrhosis. Increased intestinal mucosal permeability and decline in barrier function were also found in these patients. Followed by bacteria translocation and endotoxin uptake, these will lead to systemic inflammation. Specific microbiota and microbiota-derived metabolites are altered in various chronic liver diseases studies, but the complex interaction between the gut microbiota and liver is missing. This review article discussed the bidirectional relationship between the gut and the liver, and explained the mechanisms of how the gut microbiota ecosystem alteration affects the pathogenesis of chronic liver diseases. We presented gut-microbiota targeted interventions that could be the new promising method to manage chronic liver diseases.

Circulating MicroRNAs as Quantitative Biomarkers for Diagnosis and Prognosis of Uveal Melanoma

For uveal melanoma (UM) patients, it is significant to establish diagnosis and prognosis evaluation systems through imaging techniques. However, imaging examinations are short of quantitative biomarkers and it is difficult to finish early diagnosis of UM. In order to discover new molecular biomarkers for the diagnosis and prognostic evaluation of UM, six circulating miRNAs (mir-132-3p, mir-21-5p, mir-34a-5p, mir-126-3p, mir-199a-3p, mir-214-3p) were chosen as candidates for independent validation. Validation of these miRNAs was performed in a cohort of 20 patients, including 10 spindle-shaped melanoma and 10 epithelioid cell melanoma, and 10 healthy donors. Then 5 patients with metastatic UM were included to validate the performance of miRNAs in advanced UM. Serum levels of miRNAs were determined using quantitative real-time PCR. We confirmed significantly higher levels of three miRNAs in serum of UM patients in comparison to healthy controls, and miR-199a-3p had the best performance (p < 0.0001; AUC = 0.985). MiR-214-3p and miR-21-5p were significantly upregulated in serum of epithelioid cell melanoma patients compared to spindle-shaped melanoma patients and miR-132-3p and, conversely, were significantly downregulated in serum of epithelioid cell melanoma patients. MiR-21-5p shows their best performance (p < 0.0001; AUC = 0.980). Both miR-199a-3p and miR-21-5p showed great performance in advanced UM. Significantly higher levels of miR-21-5p (p < 0.001) were found in serum of metastatic UM patients compared to patients with localized spindle-shaped melanoma, and significantly higher levels of miR-199a-3p (p < 0.001) were detected in serum of metastatic UM patients compared to healthy controls. Our preliminary data indicate promising diagnostic utility of circulating miR-199a-3p and promising prognostic utility of circulating miR-21-5p in both early and advanced UM patients.

Prediction of the Fundus Tessellation Severity With Machine Learning Methods

Purpose

To predict the fundus tessellation (FT) severity with machine learning methods.

Methods

A population-based cross-sectional study with 3,468 individuals (mean age of 64.6 ± 9.8 years) based on Beijing Eye Study 2011. Participants underwent detailed ophthalmic examinations including fundus images. Five machine learning methods including ordinal logistic regression, ordinal probit regression, ordinal log-gamma regression, ordinal forest and neural network were used.

Main Outcome Measure

FT precision, recall, F1-score, weighted-average F1-score and AUC value.

Results

Observed from the in-sample fitting performance, the optimal model was ordinal forest, which had correct classification rate (precision) of 81.28%, while 34.75, 93.73, 70.03, and 24.82% in each classified group by FT severity. The AUC value was 0.7249. And the F1-score was 65.05%, weighted-average F1-score was 79.64% on the whole dataset. For out-of-sample prediction performance, the optimal model was ordinal logistic regression, which had precision of 77.12% on the validation dataset, while 19.57, 92.68, 64.74, and 6.76% in each classified group by FT severity. The AUC value was 0.7187. The classification accuracy of light FT group was the highest, while that of severe FT group was the lowest. And the F1-score was 54.46%, weighted-average F1-score was 74.19% on the whole dataset.

Conclusions

The ordinal forest and ordinal logistic regression model had the strong prediction in-sample and out-sample performance, respectively. The threshold ranges of the ordinal forest model for no FT and light, moderate, severe FT were [0, 0.3078], [0.3078, 0.3347], [0.3347, 0.4048], [0.4048, 1], respectively. Likewise, the threshold ranges of ordinal logistic regression model were ≤ 3.7389, [3.7389, 10.5053], [10.5053, 13.9323], > 13.9323. These results can be applied to guide clinical fundus disease screening and FT severity assessment.

User-friendly microfluidic manufacturing of hydrogel microspheres with sharp needle

Hydrogel microspheres are flexible microstructures with many fascinating functions, such as 3D cell culture, injection therapy, drug delivery, organoids and microtissues construction. The traditional methods of manufacturing hydrogel microspheres more or less have some shortcomings, such as atomization/emulsion method with uneven sizes; piezoelectric-/thermal-/electric-assisted inkjet with high cell damage and unknown cell growth effects; microfluidic manufacturing with sophisticated microdevices etc., which lead to poor user experiences. Here, we designed a user-friendly microfluidic device to generate hydrogel microspheres with sharp needles that can be replaced at will. Specifically, a commercial tapered opening sharp needle was inserted into a transparent silicone tube with the tapered opening facing the upper wall of the silicone tube. Then, GelMA solution and paraffin oil were pumped into the sharp needle and the silicone tube respectively. GelMA microdroplets were formed under the shear stress of the silicone tube and the oil phase, and after being photo-crosslinked in situ, GelMA microspheres with uniform and adjustable sizes can be generated. Due to the simplicity of our original device, heterogeneous microspheres such as Janus, core-shell and hollow microspheres can be easily manufactured by simple modification of the device. In addition, we demonstrated the strong flexibility and maneuverability of the microspheres through macroscopic free assembly. Finally, we prepared different cell-laden GelMA microspheres, and the cells showed stretching behavior similar to that in vivo after a short period culture, which indicated the high bioactivity of GelMA microspheres. Meanwhile, we cultured the Janus cell-laden GelMA microspheres and the assembly of cell-laden GelMA microspheres, where the cells stretched and interacted, demonstrating the potential of GelMA microspheres for co-culture and fabrication of large-scale tissue constructs. In view of the above results, our user-friendly microfluidic manufacturing method of hydrogel microspheres with sharp needles will provide great convenience to relevant researchers.

Phonon Thermal Transport in Silicene/Graphene Heterobilayer Nanostructures: Effect of Interlayer Interactions

Heterostructuring, as a promising route to optimize the physical properties of 2D materials, has attracted great attention from the academic community. In this paper, we investigated the room-temperature in-plane and cross-plane phonon thermal transport in silicene/graphene van der Waals (vdW) heterostructures using molecular dynamics simulations. Our simulation results demonstrated that heat current along the graphene layer is remarkably larger than that along the silicene layer, which suggests that graphene dominates the thermal transport in silicene/graphene heterostructures. The in-plane phonon thermal conductivity of the silicene/graphene heterostructures could be a compromise between monolayer graphene and monolayer silicene. Heterostructuring can remarkably reduce the in-plane thermal conductivity of the graphene layer but increase the in-plane thermal conductivity of the silicene layer in heterobilayers compared with the freestanding monolayer counterparts because of their different structures. We also simulated the interlayer interaction strength effect on the in-plane phonon thermal conductivity and cross-plane interfacial thermal resistance of silicene/graphene heterostructures. Total in-plane phonon thermal conductivity and interfacial thermal resistance both decrease with the increase in the interlayer interaction strength in the silicene/graphene heterobilayers. In addition, the calculated interfacial thermal resistance shows the effect of the thermal transport direction across the interface. This study provides a useful reference for the thermal management regulation of 2D vdW heterostructures.

Development and Prospect of Esophageal Tissue Engineering

Currently, patients with esophageal cancer, especially advanced patients, usually use autologous tissue for esophageal alternative therapy. However, an alternative therapy is often accompanied by serious complications such as ischemia and leakage, which seriously affect the prognosis of patients. Tissue engineering has been widely studied as one of the ideal methods for the treatment of esophageal cancer. In view of the complex multi-layer structure of the natural esophagus, how to use the tissue engineering method to design the scaffold with structure and function matching with the natural tissue is the principle that the tissue engineering method must follow. This article will analyze and summarize the construction methods, with or without cells, and repair effects of single-layer scaffold and multi-layer scaffold. Especially in the repair of full-thickness and circumferential esophageal defects, the flexible design method and the binding force between the layers of the scaffold are very important. In short, esophageal tissue engineering technology has broad prospects and plays a more and more important role in the treatment of esophageal diseases.

All-State Switching of the Mie Resonance of Conductive Polyaniline Nanospheres

Polyaniline (PANI), a conductive polymer, is a promising active material for optical switching. In most studies, active switching has so far been realized only between two states, whereas PANI has a total of six states. The optical properties of nanoscale PANI in all six states have remained unclear. Herein we report on all-state switching of the Mie resonance on PANI nanospheres (NSs) and active plasmon switching on PANI-coated Au nanodisks (NDs). All-state switching of differently sized PANI NSs is achieved by proton doping/dedoping and electrochemical methods. Theoretical studies show that the scattering peaks of the individual PANI NSs originate from Mie resonances. All-state switching is further demonstrated on PANI-coated circular Au NDs, where an unprecedentedly large plasmon peak shift of ∼200 nm is realized. Our study not only provides a fundamental understanding of the optical properties of PANI but also opens the probability for developing high-performance dynamic media for active plasmonics.

Exploring Lorentz Invariance Violation from Ultrahigh-Energy γ Rays Observed by LHAASO

Recently, the LHAASO Collaboration published the detection of 12 ultrahigh-energy γ-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV γ rays from astrophysical sources may provide a very sensitive probe of the effect of the Lorentz invariance violation (LIV), which results in decay of high-energy γ rays in the superluminal scenario and hence a sharp cutoff of the energy spectrum. Two highest energy sources are studied in this work. No signature of the existence of the LIV is found in their energy spectra, and the lower limits on the LIV energy scale are derived. Our results show that the first-order LIV energy scale should be higher than about 10^{5} times the Planck scale M_{Pl} and that the second-order LIV scale is >10^{-3}M_{Pl}. Both limits improve by at least one order of magnitude the previous results.

[Misdiagnosis of Acute Renal Artery Thrombosis as Acute Abdominal Disease:Report of One Case]

Renal artery thrombosis can cause acute occlusion of unilateral or bilateral renal arteries,and kidney failure would be induced if it is not diagnosed and treated in time.Therefore,rapid and correct treatment is especially important for renal artery thrombosis.Due to the lack of specificity of clinical manifestations,this disease in commonly misdiagnosed or missed and thus has a low early diagnosis rate.Here we report a case of acute renal artery thrombosis to improve the diagnosis and treatment.

Pediatric Osteosarcoma: Pearls and Pitfalls

Osteosarcoma is a malignant bone tumor most commonly presenting in children. It has a bimodal distribution with a peak incidence occurring during the ages of 10-14 years old and in adults greater than age 65. The first peak of osteosarcoma correlates with the increased proliferation of bone during the pubertal growth period. Osteosarcoma most frequently presents with localized bone pain, swelling, and an antalgic gait. The patient may attribute symptoms to trauma or strenuous exercise, causing the patient to be managed conservatively. In these cases, the pain persists and eventually leads to further evaluation. The most common type of osteosarcoma is the conventional high-grade osteosarcoma. For conventional osteosarcoma, the diagnosis is typically made or strongly suggested based upon the initial radiographic appearance. Other types of osteosarcomas include low grade central, telangiectatic, small-cell, surface and intracortical. Consequently, it is important for radiologists to be aware of these subtypes and the imaging features that differentiate them from other etiologies to prevent a delay in treatment.

Degradation of Bisphenol A by ozonation in a rotating packed bed: Modeling by response surface methodology and artificial neural network

The ozonation process of Bisphenol A (BPA) in a rotating packed bed (RPB) was modeled by response surface methodology (RSM) and artificial neural network (ANN). Experiments were performed according to the Box-Behnken design, and the interactive effects of various parameters including ozone concentration, pH, rotation speed of RPB and liquid flow rate on BPA degradation efficiency were investigated. Ozone concentration and pH had the most significant interactive effects on BPA degradation efficiency while rotation speed of RPB had no significant interactive effects with other variables. A second order polynomial equation was obtained to predict BPA degradation efficiency. Also, a multi-layered feed-forward ANN model was constructed based on the data of RSM experiments. Six neurons in hidden layer had the highest correlation coefficient (R_ANN = 0.99158). A comparison between RSM and ANN models suggested that both can accurately predict BPA degradation efficiency (R_RSM = 0.99559). The highest BPA degradation efficiency (99.52 %) was achieved under the conditions of ozone concentration of 20 mg L^-1, pH of 11, liquid flow rate of 10 L h^-1 and rotation speed of RPB of 800 rpm, which was well predicted by the RSM model (99.54 %) and the ANN model (99.82 %). However, the RSM model was slightly better than the ANN model owing to its higher determination coefficient (R²_RSM = 0.9912, R²_ANN = 0.9827) and lower mean square error (MSE_RSM = 0.0001684, MSE_ANN = 0.0003305).

A Schottky-Barrier-Free Plasmonic Semiconductor Photocatalyst for Nitrogen Fixation in a "One-Stone-Two-Birds" Manner

Plasmonic photocatalysis has received much attention owing to attractive plasmonic enhancement effects in improving the solar-to-chemical conversion efficiency. However, the photocatalytic efficiencies have remained low mainly due to the short carrier lifetime caused by the rapid recombination of plasmon-generated hot charge carriers. Although plasmonic metal-semiconductor heterostructures can improve the separation of hot charge carriers, a large portion of the hot charge carriers are lost when they cross the Schottky barrier. Herein, a Schottky-barrier-free plasmonic semiconductor photocatalyst, MoO_{3- x} , which allows for efficient N₂ photofixation in a "one-stone-two-birds" manner, is demonstrated. The oxygen vacancies in MoO_{3- x} serve as the "stone." They "kill two birds" by functioning as the active sites for the chemisorption of N₂ molecules and inducing localized surface plasmon resonance for the generation of hot charge carriers. Benefiting from this unique strategy, plasmonic MoO_{3- x} exhibits a remarkable photoreactivity for NH₃ production up to the wavelength of 1064 nm with apparent quantum efficiencies over 1%, and a solar-to-ammonia conversion efficiency of 0.057% without any hole scavenger. This work shows the great potential of plasmonic semiconductors to be directly used for photocatalysis. The concept of the Schottky-barrier-free design will pave a new path for the rational design of efficient photocatalysts.

Metal–organic framework (MOF)-derived hollow hybrid Cu2O/Cu/Au for non-enzymatic H2O2 sensing

Hollow Cu2O/Cu/Au is synthesized using hollow Cu2O/Cu derived from hollow Cu-MOF-74 as a self-sacrificial template with a uniform dispersion of Au particles. It integrates high sensitivity and wide detection range for H2O2 non-enzymatic sensing.

In vivo Imaging of Retina and Choroid in Guinea Pigs

Purpose: To evaluate the feasibility of in-vivo imaging of the retina and choroid using spectral domain optical coherence tomography (OCT) in guinea pigs. Methods: The study included 19 pigmented guinea pigs (age: 3-4 weeks) which underwent sonographic axial length measurements and OCT imaging. At study end, the animals were sacrificed and histomorphometric examinations of the retina and choroid were performed. We assessed the reproducibility of the OCT measurements and compared in-vivo measurements to histomorphometric data. Results: The mean thickness of the retina and choroid near the optic nerve head was 175.6 ± 25.8 and 63.4 ± 16.5 μm, respectively, and mean Bruch's membrane opening (BMO) diameter was 831 ± 121 μm. The intra-observer comparison of measurements of retinal thickness (intraclass correlation coefficient (ICC) = 0.92, 95% CI: 0.86-0.96; P < 0.001), choroidal thickness (ICC = 0.92, 95% CI: 0.86-0.96; P < 0.001), and BMO diameter (ICC = 0.92, 95% CI: 0.86-0.96; P < 0.001) showed a high correlation. A high agreement was present also for the inter-observer reproducibility of the measurements of retinal thickness (Pearson correlation coefficient (R) = 0.98; P < 0.001), choroidal thickness (R = 0.96; P < 0.001), and BMO diameter (R = 0.98; P < 0.001). The Bland-Altman plots showed that 2.6% (1/38), 5.3% (2/38), and 7.9% (3/38) of the measurement points of retinal thickness, choroidal thickness and BMO diameter, respectively, were located outside of the 95% limits of agreement. The OCT-based thickness measurements of retina and choroid were significantly higher than those measured by histomorphometry (both P-values <0.01). Conclusion: OCT-based in-vivo morphometric imaging of the retina and choroid in guinea pigs is feasible with an acceptable intra-observer repeatability and inter-observer reproducibility.

Mechanochemical Solvent-Free Suzuki-Miyaura Cross-Coupling of Amides via Highly Chemoselective N-C Cleavage

Although cross-coupling reactions of amides by selective N-C cleavage are one of the most powerful and burgeoning areas in organic synthesis due to the ubiquity of amide bonds, the development of mechanochemical, solid-state methods remains a major challenge. Herein, we report the first mechanochemical strategy for highly chemoselective, solvent-free palladium-catalyzed cross-coupling of amides by N-C bond activation. The method is conducted in the absence of external heating, for short reaction time and shows excellent chemoselectivity for σ N-C bond activation. The reaction shows excellent functional group tolerance and can be applied to late-stage functionalization of complex APIs and sequential orthogonal cross-couplings exploiting double solventless solid-state methods. The results extend mechanochemical reaction environments to advance the chemical repertoire of N-C bond interconversions to solid-state environmentally friendly mechanochemical methods.

Plasmon-Enhanced, Self-Traced Nanomotors on the Surface of Silicon

Light-driven nanomotors have attracted much attention due to their potential applications. The movement of conventional nanomotors typically occurs in the solution phase, which limits their application fields. Utilizing visible light to drive nanomotors at the solid-liquid interface represents a grand challenge due to the large friction force between the nanomotor and the solid surface. Based on the attractive plasmon resonance of Au nanocrystals, for the first time, plasmon-enhanced Au nanocrystal-based nanomotors moving at the silicon-aqueous solution interface have been developed. Such nanomotors move with a clear trace engraved on the Si surface, representing an excellent and exceptional self-traced nanomotor system. In addition, the nanomotor trace on the Si surface also provides a unique and promising approach to the fabrication of nanoscale Si patterns, which is central to many applications, including microelectronics, sensing, information storage, and optoelectronics.