Freeform direct-write and rewritable photonic integrated circuits in phase-change thin films.

Photonic integrated circuits (PICs) with rapid prototyping and reprogramming capabilities promise revolutionary impacts on a plethora of photonic technologies. We report direct-write and rewritable photonic circuits on a low-loss phase-change material (PCM) thin film. Complete end-to-end PICs are directly laser-written in one step without additional fabrication processes, and any part of the circuit can be erased and rewritten, facilitating rapid design modification. We demonstrate the versatility of this technique for diverse applications, including an optical interconnect fabric for reconfigurable networking, a photonic crossbar array for optical computing, and a tunable optical filter for optical signal processing. By combining the programmability of the direct laser writing technique with PCM, our technique unlocks opportunities for programmable photonic networking, computing, and signal processing. Moreover, the rewritable photonic circuits enable rapid prototyping and testing in a convenient and cost-efficient manner, eliminate the need for nanofabrication facilities, and thus promote the proliferation of photonics research and education to a broader community.

Novel nanocomposite-superlattices for low energy and high stability nanoscale phase-change memory.

Data-centric applications are pushing the limits of energy-efficiency in today's computing systems, including those based on phase-change memory (PCM). This technology must achieve low-power and stable operation at nanoscale dimensions to succeed in high-density memory arrays. Here we use a novel combination of phase-change material superlattices and nanocomposites (based on Ge4Sb6Te7), to achieve record-low power density ≈ 5 MW/cm2 and ≈ 0.7 V switching voltage (compatible with modern logic processors) in PCM devices with the smallest dimensions to date (≈ 40 nm) for a superlattice technology on a CMOS-compatible substrate. These devices also simultaneously exhibit low resistance drift with 8 resistance states, good endurance (≈ 2 × 108 cycles), and fast switching (≈ 40 ns). The efficient switching is enabled by strong heat confinement within the superlattice materials and the nanoscale device dimensions. The microstructural properties of the Ge4Sb6Te7 nanocomposite and its high crystallization temperature ensure the fast-switching speed and stability in our superlattice PCM devices. These results re-establish PCM technology as one of the frontrunners for energy-efficient data storage and computing.

Energy Efficient Neuro-Inspired Phase-Change Memory Based on Ge4 Sb6 Te7 as a Novel Epitaxial Nanocomposite.

Phase-change memory (PCM) is a promising candidate for neuro-inspired, data-intensive artificial intelligence applications, which relies on the physical attributes of PCM materials including gradual change of resistance states and multilevel operation with low resistance drift. However, achieving these attributes simultaneously remains a fundamental challenge for PCM materials such as Ge2 Sb2 Te5 , the most commonly used material. Here bi-directional gradual resistance changes with ≈10× resistance window using low energy pulses are demonstrated in nanoscale PCM devices based on Ge4 Sb6 Te7 , a new phase-change nanocomposite material . These devices show 13 resistance levels with low resistance drift for the first 8 levels, a resistance on/off ratio of ≈1000, and low variability. These attributes are enabled by the unique microstructural and electro-thermal properties of Ge4 Sb6 Te7 , a nanocomposite consisting of epitaxial SbTe nanoclusters within the Ge-Sb-Te matrix, and a higher crystallization but lower melting temperature than Ge2 Sb2 Te5 . These results advance the pathway toward energy-efficient analog computing using PCM.

Screening of key pathogenic genes in advanced knee osteoarthritis based on bioinformatics analysis.

Background: At present, the progression mechanism of knee osteoarthritis (KOA) has not been fully elucidated, and there is a clinical need for late KOA-specific diagnostic markers to provide reference for preventive treatment. This study aimed to analyze the sequencing results of early- and late-stage KOA synovial tissue based on the key genes of late-stage KOA in combination with a machine learning algorithm. Methods: The whole transcriptome sequencing results of synovial tissue from KOA patients (GSE176223 and GSE32317) were downloaded from the gene expression omnibus (GEO) database. Thirty-nine early KOA synovial tissue samples and 31 late KOA synovial tissue samples were included in this study. The diagnostic criteria and baseline data balance of early and late KOA were referred to the data source literature, and the two groups of data had good baseline data balance. R software (V3.5.1) and R packages were used for screening and enrichment analysis of differentially expressed genes (DEGs). The key genes were screened by weighted correlation network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression analysis. A receiver operating characteristic curve (ROC) curve was used to evaluate the diagnostic efficacy of key genes for advanced KOA. Results: A total of 211 DEGs related to knee arthritis were screened out. Compared with synovial tissue of early knee arthritis, 111 genes were upregulated and 100 genes were downregulated in the synovial tissue of late knee arthritis. Sixty-six key genes were screened out through WGCNA and 34 key genes were screened out in the LASSO analysis. The genes obtained by the two algorithms combined with three overlapping genes, namely interleukin- 6 (IL-6), C-X-C chemokine ligand 12 (CXCL12), and macrophage migration inhibitor factor (MIF). The areas under the ROC curves of CXCL12, IL-6, and MIF were 0.96, 0.944, and 0.961, respectively (P<0.001). Conclusions: IL-6, CXCL12, and MIF are the key pathogenic genes of KOA, which have good diagnostic efficacy for advanced KOA.

Development and Evaluation of a Rapid Neutralizing Antibody Assay for COVID-19 Vaccination.

SARS-CoV-2 neutralizing antibodies have excellent application prospects in the prevention and treatment of COVID-19. This study established a competitive colloidal gold immunochromatography assay (GICA) to detect neutralizing antibodies against the receptor-binding domain (RBD) of SARS-CoV-2 in postvaccination serum. The sensitivity, stability, and specificity of GICA were evaluated using neutralizing antibody solution reference material and positive serum. The consistency and correlation between GICA, pseudovirus neutralization (PN) assay, and ELISA were compared. Consistency analysis of serum neutralizing antibody and specific IgG antibody titers was conducted, and changes in neutralizing antibodies and specific IgG antibodies in serum after inoculation with the homologous booster inactivated vaccine and recombinant vaccine were noted. The sensitivity of the reagent was 20.66 IU/L, and the specificity was 100%. There was a strong consistency and correlation between GICA and PN (κ = 0.886, n = 165; r = 0.918, P < 0.001). The correlation coefficient of serum anti-RBD antibody and specific IgG antibody titers was 0.5253 (P < 0.001). The specific IgG antibody titers in serum after (W4) inoculation with homologous booster inactivated vaccine were 10.80 (S/CO).The anti-RBD antibody titers were 28.33. The anti-RBD omicron variant (B.1.1.529) antibody titers were 11.67. After inoculation with the recombinant vaccine, the specific IgG antibody titers in the serum of W4 were 10.68. The serum anti-RBD antibody titers of W4 were 103.30. The serum anti-RBD omicron variant (B.1.1.529) antibody titers of W4 were 56.67. Therefore, vaccination of the third dose of the homologous booster inactivated vaccine and recombinant vaccine can enhance the level of neutralizing antibodies against the omicron variant (B.1.1.529). This study demonstrates that a GICA kit for neutralizing antibodies against the RBD of SARS-CoV-2 can be used for COVID-19 vaccine evaluation. Changes in titers enable long-term monitoring of a population's immunity and guide interventions when their immunity declines.

lncRNA LINC000466 Predicts the Prognosis and Promotes the Progression of Triple-negative Breast Cancer via Modulating miR-539-5p.

BACKGROUND: Triple-negative breast cancer (TNBC) is one of the most malignant subtypes of breast cancer with an unsatisfied prognosis. Effective biomarkers could predict the risk and improve patients' survival. Whether LINC00466 possesses the potential to serve as a biomarker of the progression and prognosis of TNBC was evaluated. MATERIALS AND METHODS: A total of 122 TNBC patients were included in this study and provided paired clinical tissues. The expression of LINC00466 in TNBC was evaluated by RT-qPCR and evaluated the clinical significance with a series of statistical analyses. The biological effects and the mechanism were investigated in TNBC cells with CCK8, Transwell, and luciferase reporter assays. RESULTS: LINC00466 was significantly upregulated in TNBC and showed close association with the clinical features of patients, which indicates the development, and severity of patients. LINC00466 functioned as a prognostic biomarker predicting the survival of patients and a tumor promoter improving the proliferation, migration, and invasion of TNBC cells through sponging miR-539-5p. CONCLUSION: LINC00466 promotes the progression of TNBC via regulating miR-539-5p. The inhibition of LINC00466 might be a novel therapeutic strategy for TNBC.

Scaling of the strange-metal scattering in unconventional superconductors.

Marked evolution of properties with minute changes in the doping level is a hallmark of the complex chemistry that governs copper oxide superconductivity as manifested in the celebrated superconducting domes and quantum criticality taking place at precise compositions1-4. The strange-metal state, in which the resistivity varies linearly with temperature, has emerged as a central feature in the normal state of copper oxide superconductors5-9. The ubiquity of this behaviour signals an intimate link between the scattering mechanism and superconductivity10-12. However, a clear quantitative picture of the correlation has been lacking. Here we report the observation of precise quantitative scaling laws among the superconducting transition temperature (Tc), the linear-in-T scattering coefficient (A1) and the doping level (x) in electron-doped copper oxide La2-xCexCuO4 (LCCO). High-resolution characterization of epitaxial composition-spread films, which encompass the entire overdoped range of LCCO, has enabled us to systematically map its structural and transport properties with unprecedented accuracy and with increments of Δx = 0.0015. We have uncovered the relations Tc ~ (xc - x)0.5 ~ (A1□)0.5, where xc is the critical doping in which superconductivity disappears and A1□ is the coefficient of the linear resistivity per CuO2 plane. The striking similarity of the Tc versus A1□ relation among copper oxides, iron-based and organic superconductors may be an indication of a common mechanism of the strange-metal behaviour and unconventional superconductivity in these systems.

Harnessing optoelectronic noises in a photonic generative network.

Integrated optoelectronics is emerging as a promising platform of neural network accelerator, which affords efficient in-memory computing and high bandwidth interconnectivity. The inherent optoelectronic noises, however, make the photonic systems error-prone in practice. It is thus imperative to devise strategies to mitigate and, if possible, harness noises in photonic computing systems. Here, we demonstrate a photonic generative network as a part of a generative adversarial network (GAN). This network is implemented with a photonic core consisting of an array of programable phase-change memory cells to perform four-element vector-vector dot multiplication. The GAN can generate a handwritten number ("7") in experiments and full 10 digits in simulation. We realize an optical random number generator, apply noise-aware training by injecting additional noise, and demonstrate the network's resilience to hardware nonidealities. Our results suggest the resilience and potential of more complex photonic generative networks based on large-scale, realistic photonic hardware.

Feasibility of modified radical mastectomy with nipple-areola preservation combined with stage I prosthesis implantation using air cavity-free suspension hook in patients with breast cancer.

BACKGROUND: Mastoscopic surgery is proven to have lower incidence of postoperative complications and better postoperative recovery than traditional breast cancer surgery. This study aimed to examine the feasibility of mastoscopic modified radical mastectomy (MRM) with skin nipple-areola preservation under air cavity-free suspension hook and stage I silicone prosthesis implantation (SMALND) compared with routine MRM. METHODS: This was a retrospective study of patients who underwent MRM for breast cancer at the Shengjing Hospital Affiliated to China Medical University between January 1, 2019, and June 30, 2019. Surgical outcomes, complications, satisfaction, and quality of life (Functional Assessment of Cancer Therapy-Breast [FACT-B] [Chinese version]) were compared between the two groups. RESULTS: A total of 87 patients were enrolled, with 30 underwent SMALND and 57 underwent routine MRM. The intraoperative blood loss in the SMALND group was lower than in the control group (165.3±44.1 vs. 201.4±52.7 ml, P=0.001), the operation time was longer (220.5±23.9 vs. 155.6±9.2 min, P<0.001), daily axillary drainage volume was smaller (20.2±3.6 vs. 24.1±3.0 ml, P<0.001), daily subcutaneous drainage volume was smaller (15.5±2.3 vs. 19.3±3.5 ml, P<0.001), the discharge time was shorter (7.5±1.6 vs. 9.0±1.8 days, P<0.001), and FACT-B scores were higher (83.8±5.6 vs. 72.1±4.6, P<0.001). The overall satisfaction was higher in the SMALND group than in the controls (76.7% vs. 54.4%, P=0.041). Compared with the controls, the occurrence rates of nipple and flap necrosis, upper limb edema, and paraesthesia in the SMALND group were lower within 6 months (all P<0.05). CONCLUSIONS: Compared with traditional MRM, SMALND had better surgical outcomes, higher satisfaction, higher quality of life, and lower complication rates.

Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network.

Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics for machine learning algorithms, such as neural networks of various types. Integrated photonic networks are particularly powerful in performing analog computing of matrix-vector multiplication (MVM) as they afford unparalleled speed and bandwidth density for data transmission. Incorporating nonvolatile phase-change materials in integrated photonic devices enables indispensable programming and in-memory computing capabilities for on-chip optical computing. Here, we demonstrate a multimode photonic computing core consisting of an array of programable mode converters based on on-waveguide metasurfaces made of phase-change materials. The programmable converters utilize the refractive index change of the phase-change material Ge2Sb2Te5 during phase transition to control the waveguide spatial modes with a very high precision of up to 64 levels in modal contrast. This contrast is used to represent the matrix elements, with 6-bit resolution and both positive and negative values, to perform MVM computation in neural network algorithms. We demonstrate a prototypical optical convolutional neural network that can perform image processing and recognition tasks with high accuracy. With a broad operation bandwidth and a compact device footprint, the demonstrated multimode photonic core is promising toward large-scale photonic neural networks with ultrahigh computation throughputs.

On-the-fly closed-loop materials discovery via Bayesian active learning.

Active learning-the field of machine learning (ML) dedicated to optimal experiment design-has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on another major challenge, the discovery of advanced materials against the exceedingly complex synthesis-processes-structure-property landscape. We demonstrate an autonomous materials discovery methodology for functional inorganic compounds which allow scientists to fail smarter, learn faster, and spend less resources in their studies, while simultaneously improving trust in scientific results and machine learning tools. This robot science enables science-over-the-network, reducing the economic impact of scientists being physically separated from their labs. The real-time closed-loop, autonomous system for materials exploration and optimization (CAMEO) is implemented at the synchrotron beamline to accelerate the interconnected tasks of phase mapping and property optimization, with each cycle taking seconds to minutes. We also demonstrate an embodiment of human-machine interaction, where human-in-the-loop is called to play a contributing role within each cycle. This work has resulted in the discovery of a novel epitaxial nanocomposite phase-change memory material.

The effects of oxygen in spinel oxide Li1+xTi2-xO4-δ thin films.

The evolution from superconducting LiTi2O4-δ to insulating Li4Ti5O12 thin films has been studied by precisely tuning the oxygen pressure in the sample fabrication process. In superconducting LiTi2O4-δ films, with the increase of oxygen pressure, the oxygen vacancies are filled gradually and the c-axis lattice constant decreases. When the oxygen pressure increases to a certain critical value, the c-axis lattice constant becomes stable, which implies that the sample has been completely converted to Li4Ti5O12 phase. The two processes can be manifested by the angular bright-field images of the scanning transmission electron microscopy techniques. The transition temperature (T ch ) of magnetoresistance from the positive to the negative shows a nonmonotonic behavior, i.e. first decrease and then increase, with the increase of oxygen pressure. We suggest that the decrease Tch can be attributed to the suppressing of orbital-related state, and the inhomogeneous phase separated regions contribute positive MR and thereby lead to the reverse relation between Tch and oxygen pressure.

Healing Effect of Controlled Anti-Electromigration on Conventional and High-Tc Superconducting Nanowires.

The electromigration process has the potential capability to move atoms one by one when properly controlled. It is therefore an appealing tool to tune the cross section of monoatomic compounds with ultimate resolution or, in the case of polyatomic compounds, to change the stoichiometry with the same atomic precision. As demonstrated here, a combination of electromigration and anti-electromigration can be used to reversibly displace atoms with a high degree of control. This enables a fine adjustment of the superconducting properties of Al weak links, whereas in Nb the diffusion of atoms leads to a more irreversible process. In a superconductor with a complex unit cell (La2-x Cex CuO4 ), the electromigration process acts selectively on the oxygen atoms with no apparent modification of the structure. This allows to adjust the doping of this compound and switch from a superconducting to an insulating state in a nearly reversible fashion. In addition, the conditions needed to replace feedback controlled electromigration by a simpler technique of electropulsing are discussed. These findings have a direct practical application as a method to explore the dependence of the characteristic parameters on the exact oxygen content and pave the way for a reversible control of local properties of nanowires.