Metalens enhanced ray optics: an end-to-end wave-ray co-optimization framework.

We present a fully differentiable framework for seamlessly integrating wave optical components with geometrical lenses, offering an approach to enhance the performance of large-scale end-to-end optical systems. In this study, we focus on the integration of a metalens, a geometrical lens, and image data. Through the use of gradient-based optimization techniques, we demonstrate the design of nonparaxial imaging systems and the correction of aberrations inherent in geometrical optics. Our framework enables efficient and effective optimization of the entire optical system, leading to improved overall performance.

Identification of DNA variants at ultra-low variant allele frequencies via Taq polymerase cleavage of wild-specific blockers.

Detecting mutations related to tumors holds immense clinical significance for cancer diagnosis and treatment. However, the presence of highly redundant wild DNA poses a challenge for the advancement of low-copy mutant ctDNA genotyping in cancer cases. To address this, a Taqman qPCR strategy to identify rare mutations at low variant allele fractions (VAFs) has been developed. This strategy combines mutant-specific primers with wild-specific blockers. Diverging from other blocker-mediated PCRs, which rely on primer-induced strand displacement or the use of modified oligos resistant to Taq polymerase, our innovation is built upon the cleavage of specific blockers by Taq polymerase. Given its unique design, which does not hinge on strand displacement or base modification, we refer to this novel method as unmodified-blocker cleavage PCR (UBC-PCR). Multiple experiments consistently confirmed that variant distinction was improved significantly by introduction of 5' unmatched blockers into the reaction. Moreover, UBC-PCR successfully detected mutant DNA at VAFs as low as 0.01% across six different variant contexts. Multiplex UBC-PCR was also performed to identify a reference target and three mutations with a sensitivity of 0.01% VAFs in one single tube. In profiling the gene status from 12 lung cancer ctDNA samples and 22 thyroid cancer FNA DNA samples, UBC-PCR exhibited a 100% concordance rate with ddPCR and a commercial ARMS kit, respectively. Our work demonstrates that UBC-PCR can identify low-abundance variants with high sensitivity in multiplex reactions, independent of strand displacement and base modification. This strategy holds the potential to significantly impact clinical practice and precision medicine.

Highly Sensitive Enrichment of Low-Frequency Variants by Hairpin Competition Amplification.

Gene mutations are inevitably accumulated in cells of the human body. It is of great significance to detect mutations at the earliest possible time in physiological and pathological processes. However, genotyping low-copy tumor DNA (ctDNA) in patients is challenging due to abundant wild DNA backgrounds. One novel strategy to enrich rare mutations at low variant allele fractions (VAFs) with quantitative polymerase chain reaction (qPCR) and Sanger sequencing was contrived by introducing artificial hairpins into amplicons to compete with primers, coined as the hairpin competition amplification (HCA) system. The influence imposed by artificial hairpins on primer-binding in a high-temperature PCR system was investigated for the first time in this work, paving the way for the optimization of HCA. HCA differs from the previously reported work in which hairpins are formed to inhibit extension of wild-type DNA using 5-exonuclease-negative polymerase, where the readout is dependent on melting curve analysis after asymmetric PCR. Targeted at six different variants, HCA qPCR and HCA Sanger-enriched mutant DNA at VAFs as low as 0.1 or 0.01% were performed. HCA demonstrated advantages in multiplex reaction and temperature robustness. In profiling gene status from 12 lung cancer ctDNA samples and 16 thyroid cancer FNA DNA samples, HCA demonstrated a 100% concordance rate compared to ddPCR and commercial ARMS kit. HCA qPCR and Sanger sequencing can enrich low-abundance variants with high sensitivity and temperature robustness, presenting a novel and effective tool for precision diagnosis and treatment of rare variant diseases.

Maximized Frequency Doubling through the Inverse Design of Nonlinear Metamaterials.

The conventional process for developing an optimal design for nonlinear optical responses is based on a trial-and-error approach that is largely inefficient and does not necessarily lead to an ideal result. Deep learning can automate this process and widen the realm of nonlinear geometries and devices. This research illustrates a deep learning framework used to create an optimal plasmonic design for a nonlinear metamaterial. The algorithm produces a plasmonic pattern that can maximize the second-order nonlinear effect of a nonlinear metamaterial. A nanolaminate metamaterial is used as a nonlinear material, and plasmonic patterns are fabricated on the prepared nanolaminate to demonstrate the validity and efficacy of the deep learning algorithm. The optimal pattern produced yielded second-harmonic generation from the nanolaminate with normal incident fundamental light. The deep learning architecture applied in this research can be expanded to other optical responses and light-matter interaction processes.

Feasibility of Methylated CLIP4 in Stool for Early Detection of Colorectal Cancer: A Training Study in Chinese Population.

BACKGROUND: Early detection of colorectal cancer (CRC) and precancerous lesion is vitally important for mitigating CRC morbidity and mortality. Aberrant DNA methylations in certain promoter regions have been identified to be closely associated with CRC development and progression, suggesting their potential as diagnostic biomarkers for early detection. In this study, we evaluated the performance of methylated CLIP4 in stool specimens as a potential biomarker for CRC detection. METHODS: A total of 321 subjects out of 365 enrolled participants were included in the final analysis, including 154 CRC patients, 23 advanced adenoma (AA) patients, 49 small polyp (SP) patients, and 95 healthy controls. CLIP4 methylation level was examined by qPCR with bisulfite converted DNA purified from approximately 5 g stool specimen. RESULTS: Methylated CLIP4 test showed high sensitivities of 78.3% (95% CI: 55.8%-91.7%) and 90.3% (95% CI: 84.2%-94.3%) for detecting AA and CRC, respectively, with a specificity of 88.4% (95% CI: 79.8%-93.8%). CLIP4 methylation level discriminated AA and CRC patients from control subjects with area under the curve values of 0.892 (95% CI: 0.795-0.988) and 0.961 (95% CI: 0.938-0.983). Further analysis indicated no significant difference in sensitivities among different ages, genders, stages, locations, sides, tumor sizes and differentiation statuses. CONCLUSIONS: Methylated CLIP4 showed a strong potential as a noninvasive biomarker for early CRC detection.

Disruptors, a new class of oligonucleotide reagents, significantly improved PCR performance on templates containing stable intramolecular secondary structures.

Intramolecular secondary structures within templates have been shown to lower PCR performance. Whereas many approaches have been developed to mitigate such impairment on PCR, their effects can vary greatly depending on template sequences. Here we present a novel, universally effective approach to improve PCR performance involving specifically designed oligonucleotides called disruptors. A disruptor contained three functional components, an anchor designed to initiate template binding, an effector to disrupt intramolecular secondary structure, and a 3' blocker to prevent its elongation by DNA polymerase. A functional mechanism for a disruptor to improve PCR efficiency was proposed where anchor first binds to template followed by effector-mediated strand displacement to unwind intramolecular secondary structure. Such a mechanism was consistent with the observation that anchor played a more critical role for disruptor function. As an example of potential disruptor applications, inverted terminal repeat sequences of recombinant adeno-associated virus vectors were successfully amplified in the presence of disruptors despite their well-known reputation as some of the most difficult templates for PCR amplification and Sanger sequencing due to their ultra-stable T-shaped hairpin structures. In stark contrast, both DMSO and betaine, two PCR additives routinely used to facilitate PCR amplification and Sanger sequencing of GC-rich templates, did not demonstrate any improving effect.

Tackling Photonic Inverse Design with Machine Learning.

Machine learning, as a study of algorithms that automate prediction and decision-making based on complex data, has become one of the most effective tools in the study of artificial intelligence. In recent years, scientific communities have been gradually merging data-driven approaches with research, enabling dramatic progress in revealing underlying mechanisms, predicting essential properties, and discovering unconventional phenomena. It is becoming an indispensable tool in the fields of, for instance, quantum physics, organic chemistry, and medical imaging. Very recently, machine learning has been adopted in the research of photonics and optics as an alternative approach to address the inverse design problem. In this report, the fast advances of machine-learning-enabled photonic design strategies in the past few years are summarized. In particular, deep learning methods, a subset of machine learning algorithms, dealing with intractable high degrees-of-freedom structure design are focused upon.

Building Multifunctional Metasystems via Algorithmic Construction.

Flat optics foresees a promising route to ultracompact optical devices, where metasurfaces serve as the foundation. Conventional designs of metasurfaces start with a certain structure as the prototype, followed by extensive parametric sweeps to accommodate the requirements of phase and amplitude of the emerging light. Regardless of how computation consuming the process is, a predefined structure can hardly realize the independent control over polarization, frequency, and spatial channels, which hinders the potential of metasurfaces to be multifunctional. Besides, achieving complicated and multiple functions calls for designing metasystems with multiple cascading layers of metasurfaces, which introduces exponential complexity. In this work, we present a hybrid deep learning framework for designing multilayer metasystems with multifunctional capabilities. We demonstrate examples of a polarization-multiplexed dual-functional beam generator, a second-order differentiator for all-optical computing, and a space-polarization-wavelength multiplexed hologram. These examples are barely achievable by single-layer metasurfaces and unattainable by traditional design processes.

Transient stem-loop structure of nucleic acid template may interfere with polymerase chain reaction through endonuclease activity of Taq DNA polymerase.

As a standard molecular biology technique, PCR uses DNA polymerase to detect, amplify and manipulate DNA targets. Due to its effect of exponential amplification, PCR can achieve high sensitivity required for detecting targets of low abundance. Therefore, it has become the method of choice for the majority of nucleic acid-based tests. In PCR reactions, DNA templates are first unwound into single strands, followed by a quick temperature drop when transient intramolecular secondary structures may form first within the single-stranded templates due to reaction kinetics. In this study, we showed that the adverse effects of stem-loop structures on PCR performance were directly correlated with their thermal stability. Moreover, fractions of intermediate PCR products of templates with stable stem-loop structures were significantly shorter than those without. It was further demonstrated that when encountering the duplex region of such a structure during the PCR extension step, the endonuclease activity of Taq DNA polymerase mediated by its 5'-3' exonuclease activity could digest template strand, resulting in stem-loop structure unwinding and subsequent completion of replication to produce truncated products. This work thus provided some new mechanistic insights into the complex nature of PCR assays, a frequently encountered but neglected aspect of this widely used technique.

Topological encoding method for data-driven photonics inverse design.

Data-driven approaches have been proposed as effective strategies for the inverse design and optimization of photonic structures in recent years. In order to assist data-driven methods for the design of topology of photonic devices, we propose a topological encoding method that transforms photonic structures represented by binary images to a continuous sparse representation. This sparse representation can be utilized for dimensionality reduction and dataset generation, enabling effective analysis and optimization of photonic topologies with data-driven approaches. As a proof of principle, we leverage our encoding method for the design of two dimensional non-paraxial diffractive optical elements with various diffraction intensity distributions. We proved that our encoding method is able to assist machine-learning-based inverse design approaches for accurate and global optimization.

Compounding Meta-Atoms into Metamolecules with Hybrid Artificial Intelligence Techniques.

Molecules composed of atoms exhibit properties not inherent to their constituent atoms. Similarly, metamolecules consisting of multiple meta-atoms possess emerging features that the meta-atoms themselves do not possess. Metasurfaces composed of metamolecules with spatially variant building blocks, such as gradient metasurfaces, are drawing substantial attention due to their unconventional controllability of the amplitude, phase, and frequency of light. However, the intricate mechanisms and the large degrees of freedom of the multielement systems impede an effective strategy for the design and optimization of metamolecules. Here, a hybrid artificial-intelligence-based framework consolidating compositional pattern-producing networks and cooperative coevolution to resolve the inverse design of metamolecules in metasurfaces is proposed. The framework breaks the design of the metamolecules into separate designs of meta-atoms, and independently solves the smaller design tasks of the meta-atoms through deep learning and evolutionary algorithms. The proposed framework is leveraged to design metallic metamolecules for arbitrary manipulation of the polarization and wavefront of light. Moreover, the efficacy and reliability of the design strategy are confirmed through experimental validations. This framework reveals a promising candidate approach to expedite the design of large-scale metasurfaces in a labor-saving, systematic manner.

Generative Model for the Inverse Design of Metasurfaces.

The advent of metasurfaces in recent years has ushered in a revolutionary means to manipulate the behavior of light on the nanoscale. The design of such structures, to date, has relied on the expertise of an optical scientist to guide a progression of electromagnetic simulations that iteratively solve Maxwell's equations until a locally optimized solution can be attained. In this work, we identify a solution to circumvent this conventional design procedure by means of a deep learning architecture. When fed an input set of customer-defined optical spectra, the constructed generative network generates candidate patterns that match the on-demand spectra with high fidelity. This approach reveals an opportunity to expedite the discovery and design of metasurfaces for tailored optical responses in a systematic, inverse-design manner.

Stability, integrity, and recovery rate of cellular nucleic acids preserved in a new liquid-based cytology medium.

BACKGROUND: Liquid-based cytology (LBC) has replaced the conventional Papanicolaou test in cervical cancer screening. The cervical swab specimens collected in LBC media can also be used for additional analyses including high-risk HPV (HR-HPV) test, DNA methylation analysis, and HPV E6/E7 mRNA test. METHODS: The stability, integrity, and recovery rate of cellular DNA and RNA after storage at different conditions were evaluated by a quantitative real-time PCR (qPCR) based HR-HPV test, reverse transcription qPCR (RT-qPCR), and agarose gel electrophoresis. Cervical swab specimens collected in a newly developed LBC medium, VersaMedium, and ThinPrep PreservCyt medium were processed on Hologic ThinPrep 5000 instrument. RESULTS: Cervical exfoliative cells fixed by VersaMedium exhibited good cellular morphology with intact membranes and delineated chromatin structures. Cellular DNA preserved in VersaMedium exhibited high level of stability at both room temperature and 4°C, and remained mostly intact at 4°C for up to 28 days. Cellular RNA preserved in VersaMedium maintained higher level of stability and integrity at 4°C than at room temperature. VersaMedium also showed no apparent adverse effect on the recovery rate of nucleic acids. CONCLUSION: In addition to maintaining cellular morphology, when stored at 4°C, VersaMedium preserves cellular nucleic acids and PreservCyt medium without noticeable adverse effects on the recovery rate during purification. Therefore, VersaMedium is an appropriate LBC medium for the collection and preservation of cervical swab specimens. And VersaMedium preserved cellular nucleic acids are of such high quality that they are suitable for HR-HPV qPCR test and RT-qPCR analyses.

Controllable optical activity with non-chiral plasmonic metasurfaces.

Optical activity is the rotation of the plane of linearly polarized light along the propagation direction as the light travels through optically active materials. In existing methods, the strength of the optical activity is determined by the chirality of the materials, which is difficult to control quantitatively. Here we numerically and experimentally investigated an alternative approach to realize and control the optical activity with non-chiral plasmonic metasurfaces. Through judicious design of the structural units of the metasurfaces, the right and left circular polarization components of the linearly polarized light have different phase retardations after transmitting through the metasurfaces, leading to large optical activity. Moreover, the strength of the optical activity can be easily and accurately tuned by directly adjusting the phase difference. The proposed approach based on non-chiral plasmonic metasurfaces exhibits large optical activity with a high controllable degree of freedom, which may provide more possibilities for applications in photonics.

Emergent Functionality and Controllability in Few-Layer Metasurfaces.

Recent progress in metamaterial research has successfully exceeded the limitations imposed by conventional materials and optical devices, enabling the manipulation of electromagnetic waves as desired. The distinct characteristics and controlling abilities of metamaterials make them ideal candidates for novel photonics devices not only in traditional optics but also for biological detection, medical science, and metrology. However, the controllability and functionality of both single-layer metasurfaces and bulk metamaterials are not sufficient to meet the requirements of emerging technologies; hence, new solutions must be found. As such technologies advance, new functionalities will emerge as different or identical single-layer metasurfaces are combined. Thus, innovation in few-layer metasurfaces will become an increasingly important line of research. Here, these metasurfaces are classified according to their functionalities and the few-layer metasurfaces that have been proposed up to now are presented in a clear sequence. It is expected that, with further development in this area, few-layer metasurfaces will play an important role in the family of optical materials.

Generation of vector beams with arbitrary spatial variation of phase and linear polarization using plasmonic metasurfaces.

A novel method is proposed to generate vector beams with arbitrary spatial variation of phase and linear polarization at the nanoscale using compact plasmonic metasurfaces with rectangular nanoapertures. The physical mechanism underlying the simultaneous control of light polarization and phase is explained. Vector beams with different spiral phasefronts are obtained by manipulating the local orientation and geometric parameters of the metasurfaces. In addition, radially and azimuthally polarized vector beams and double-mode vector beams are achieved through completely compensating for the Berry phase, which provides additional degrees of freedom for beam manipulation.

Fully interferometric controllable anomalous refraction efficiency using cross modulation with plasmonic metasurfaces.

We present a method of fully interferometric, controllable anomalous refraction efficiency by introducing cross-modulated incident light based on plasmonic metasurfaces. Theoretical analyses and numerical simulations indicate that the anomalous and ordinary refracted beams generated from two opposite-helicity incident beams and following the generalized Snell's law will have a superposition for certain incident angles, and the anomalous refraction efficiency can be dynamically controlled by changing the relative phase of the incident sources. As the incident wavelength nears the resonant wavelength of the plasmonic metasurfaces, two equal-amplitude incident beams with opposite helicity can be used to control the anomalous refraction efficiency. Otherwise, two unequal-amplitude incident beams with opposite helicity can be used to fully control the anomalous refraction efficiency. This Letter may offer a further step in the development of controllable anomalous refraction.