Photon counting Raman spectroscopy: a benchmarking study vs surface plasmon enhancement.

We demonstrate a single-photon counting Raman spectroscope and benchmark it against conventional and surface-enhanced Raman spectroscopy. For direct comparison without ambiguity, we use the same solutions of Rhodamine 6G and a common optical setup with either a spectrometer or an acousto-optic tunable filter, whereas the surface enhancement is realized with immobilized Ag nanoparticles. Our results find that the single photon counting significantly elevates the detection sensitivity by up to eight orders of magnitude, arriving at a comparable level of surface-enhanced Raman spectroscopy. Another significant advantage is with the time-resolving measurement, where we demonstrate time-gated and time-correlated single-photon counting with sub-nanosecond resolution. It offers insights into the samples' transient responses and enables the isolation of Raman scattering from fluorescence signals.

Invertible all-optical logic gate on chip.

We demonstrate an invertible all-optical gate on chip, with the roles of control and signal switchable by slightly adjusting their relative arrival time at the gate. It is based on the quantum Zeno blockade (QZB) driven by sum-frequency generation (SFG) in a periodically poled lithium niobate microring resonator. For two nearly identical nanosecond pulses, the later arriving pulse is modulated by the earlier arriving one, resulting in 2.4 and 3.9 power extinction between the two, respectively, when their peak powers are 1 mW and 2 mW, respectively. Our results, while to be improved and enriched, herald a new, to the best of our knowledge, paradigm of logical gates and circuits for exotic applications.

Broadband frequency comb generation through cascaded quadratic nonlinearity in thin-film lithium niobate microresonators.

Broadband frequency comb generation through cascaded quadratic nonlinearity remains experimentally untapped in free-space cavities with bulk χ(2) materials mainly due to the high threshold power and restricted ability of dispersion engineering. Thin-film lithium niobate (LN) is a good platform for nonlinear optics due to the tight mode confinement in a nano-dimensional waveguide, the ease of dispersion engineering, large quadratic nonlinearities, and flexible phase matching via periodic poling. Here we demonstrate broadband frequency comb generation through dispersion engineering in a thin-film LN microresonator. Bandwidths of 150 nm (80 nm) and 25 nm (12 nm) for center wavelengths at 1560 and 780 nm are achieved, respectively, in a cavity-enhanced second-harmonic generation (doubly resonant optical parametric oscillator). Our demonstration paves the way for pure quadratic soliton generation, which is a great complement to dissipative Kerr soliton frequency combs for extended interesting nonlinear applications.

How do probiotics alleviate constipation? A narrative review of mechanisms.

Constipation is a common gastrointestinal condition, which may occur at any age and affects countless people. The search for new treatments for constipation is ongoing as current drug treatments fail to provide fully satisfactory results. In recent years, probiotics have attracted much attention because of their demonstrated therapeutic efficacy and fewer side effects than pharmaceutical products. Many studies attempted to answer the question of how probiotics can alleviate constipation. It has been shown that different probiotic strains can alleviate constipation by different mechanisms. The mechanisms on probiotics in relieving constipation were associated with various aspects, including regulation of the gut microbiota composition, the level of short-chain fatty acids, aquaporin expression levels, neurotransmitters and hormone levels, inflammation, the intestinal environmental metabolic status, neurotrophic factor levels and the body's antioxidant levels. This paper summarizes the perception of the mechanisms on probiotics in relieving constipation and provides some suggestions on new research directions.

A humanized trivalent Nectin-4-targeting nanobody drug conjugate displays potent antitumor activity in gastric cancer.

BACKGROUND: Gastric cancer represents a highly lethal malignancy with an elevated mortality rate among cancer patients, coupled with a suboptimal postoperative survival prognosis. Nectin-4, an overexpressed oncological target for various cancers, has been exploited to create antibody-drug conjugates (ADCs) to treat solid tumors. However, there is limited research on Nectin-4 ADCs specifically for gastric cancer, and conventional immunoglobulin G (IgG)-based ADCs frequently encounter binding site barriers. Based on the excellent tumor penetration capabilities inherent in nanobodies (Nbs), we developed Nectin-4-targeting Nb drug conjugates (NDCs) for the treatment of gastric cancer. RESULTS: An immunized phage display library was established and employed for the selection of Nectin-4-specific Nbs using phage display technology. Subsequently, these Nbs were engineered into homodimers to enhance Nb affinity. To prolong in vivo half-life and reduce immunogenicity, we fused an Nb targeting human serum albumin (HSA), resulting in the development of trivalent humanized Nbs. Further, we site-specifically conjugated a monomethyl auristatin E (MMAE) at the C-terminus of the trivalent Nbs, creating Nectin-4 NDC (huNb26/Nb26-Nbh-MMAE) with a drug-to-antibody ratio (DAR) of 1. Nectin-4 NDC demonstrated excellent in vitro cell-binding activities and cytotoxic efficacy against cells with high Nectin-4 expression. Subsequent administration of Nectin-4 NDC to mice bearing NCI-N87 human gastric cancer xenografts demonstrated rapid tissue penetration and high tumor uptake through in vivo imaging. Moreover, Nectin-4 NDC exhibited noteworthy dose-dependent anti-tumor efficacy in in vivo studies. CONCLUSION: We have engineered a Nectin-4 NDC with elevated affinity and effective tumor uptake, further establishing its potential as a therapeutic agent for gastric cancer.

A platform utilizing Drosophila ovulation for nonhormonal contraceptive screening.

A significant unmet need for new contraceptive options for both women and men remains due to side-effect profiles, medical concerns, and the inconvenience of many currently available contraceptive products. Unfortunately, the development of novel nonsteroidal female contraceptive medicine has been stalled in the last couple of decades due to the lack of effective screening platforms. Drosophila utilizes conserved signaling pathways for follicle rupture, a final step in ovulation that is essential for female reproduction. Therefore, we explored the potential to use Drosophila as a model to screen compounds that could inhibit follicle rupture and be nonsteroidal contraceptive candidates. Using our ex vivo follicle rupture assay, we screened 1,172 Food and Drug Administration (FDA)-approved drugs and identified six drugs that could inhibit Drosophila follicle rupture in a dose-dependent manner. In addition, we characterized the molecular actions of these drugs in the inhibition of adrenergic signaling and follicle rupture. Furthermore, we validated that three of the four drugs consistently inhibited mouse follicle rupture in vitro and that two of them did not affect progesterone production. Finally, we showed that chlorpromazine, one of the candidate drugs, can significantly inhibit mouse follicle rupture in vivo. Our work suggests that Drosophila ovulation is a valuable platform for identifying lead compounds for nonsteroidal contraceptive development and highlights the potential of these FDA-approved drugs as novel nonsteroidal contraceptive agents.

Insisting on help, facing challenges, and maintaining balance: The lived experiences of caregivers raising a child with developmental delay in the remote islands of Kinmen.

PURPOSE: To explore the lived experiences of the caregivers of children with developmental delay (DD) on the remote island of Kinmen, Taiwan. DESIGN AND METHODS: This descriptive phenomenological study included 14 caregivers of 16 children with DD recruited from Kinmen, Taiwan. Data were collected from September 2020 to February 2021 with face-to-face semi-structured interviews, which were transcribed verbatim and analyzed using thematic analysis. RESULTS: Twelve caregivers were mothers; there was one father and one grandmother. Their mean age was 37.93 ± 5.17 years. The mean age of the children was 3.90 ± 1.49 years; 11 were male (69%). As we began our study, the COVID-19 pandemic occurred, which influenced two of the three themes: (1) focusing on their child's delayed development, which involved seeking a diagnosis and blaming themselves; (2) facing barriers to caring a child with DD on a remote island, which included ostracization of their child and limited off-island medical resources, especially during COVID-19; and (3) maintaining a healthy life balance, which involved protecting their child from physical or spiritual harm, including exposure to COVID-19, and reflecting on their strengths. CONCLUSIONS: Our findings highlight the challenges of caring for a child with DD in the Kinmen islands of Taiwan, and the impact of the COVID-19 pandemic. PRACTICAL IMPLICATIONS: Healthcare professionals are encouraged to provide caregivers of children with DD living in remote, island communities an opportunity to share their caregiving experiences and provide strategies for obtaining medical care, which could help reduce caregiver burden.

MEDL-Net: A model-based neural network for MRI reconstruction with enhanced deep learned regularizers.

PURPOSE: To improve the MRI reconstruction performance of model-based networks and to alleviate their large demand for GPU memory. METHODS: A model-based neural network with enhanced deep learned regularizers (MEDL-Net) was proposed. The MEDL-Net is separated into several submodules, each of which consists of several cascades to mimic the optimization steps in conventional MRI reconstruction algorithms. Information from shallow cascades is densely connected to latter ones to enrich their inputs in each submodule, and additional revising blocks (RB) are stacked at the end of the submodules to bring more flexibility. Moreover, a composition loss function was designed to explicitly supervise RBs. RESULTS: Network performance was evaluated on a publicly available dataset. The MEDL-Net quantitatively outperforms the state-of-the-art methods on different MR image sequences with different acceleration rates (four-fold and six-fold). Moreover, the reconstructed images showed that the detailed textures are better preserved. In addition, fewer cascades are required when achieving the same reconstruction results compared with other model-based networks. CONCLUSION: In this study, a more efficient model-based deep network was proposed to reconstruct MR images. The experimental results indicate that the proposed method improves reconstruction performance with fewer cascades, which alleviates the large demand for GPU memory.

Single-pixel image reconstruction using coherent nonlinear optics.

We propose and experimentally demonstrate a novel, to the best of our knowledge, hybrid optoelectronic system that utilizes mode-selective frequency upconversion, single-pixel detection, and a deep neural network to achieve the reliable reconstruction of two-dimensional (2D) images from a noise-contaminated database of handwritten digits. Our system is designed to maximize the multi-scale structural similarity index measure (MS-SSIM) and minimize the mean absolute error (MAE) during the training process. Through extensive evaluation, we have observed that the reconstructed images exhibit high-quality results, with a peak signal-to-noise ratio (PSNR) reaching approximately 20 dB and a structural similarity index measure (SSIM) of around 0.85. These impressive metrics demonstrate the effectiveness and fidelity of our image reconstruction technique. The versatility of our approach allows its application in various fields, including Lidar, compressive imaging, volumetric reconstruction, and so on.

Applications of optical property measurement for quality evaluation of agri-food products: a review.

Spectroscopic techniques coupled with chemometric approaches have been widely used for quality evaluation of agricultural and food (agri-food) products due to the nondestructive, simple, fast, and easy characters. However, these techniques face the issues or challenges of relatively weak robustness, generalizability, and applicability in modeling and prediction because they measure the aggregate amount of light interaction with tissues, resulting in the combined effect of absorption and scattering of photons. Optical property measurement could separate absorption from scattering, providing new insights into more reliable prediction performance in quality evaluation, which is attracting increasing attention. In this review, a brief overview of the currently popular measurement techniques, in terms of light transfer principles and data analysis algorithms, is first presented. Then, the emphases are put on the recent advances of these techniques for measuring optical properties of agri-food products since 2000. Corresponding applications on qualitative and quantitative analyses of quality evaluation, as well as light transfer simulations within tissues, were reviewed. Furthermore, the leading groups working on optical property measurement worldwide are highlighted, which is the first summary to the best of our knowledge. Finally, challenges for optical property measurement are discussed, and some viewpoints on future research directions are also given.

HighlightsEmerging techniques for measuring optical properties are briefly introducedQualitative analyses of maturity evaluation and defect detection are reviewedQuantitative analyses of attribute prediction and microstructure estimation are presentedLight transfer simulations based on optical properties are comprehensively discussedLeading groups are summarized for the first time, to the best of our knowledgeChallenges and prospects for optical property measurement are given.

Enhanced formaldehyde oxidation over MnO2 and doped manganese-based catalysts: Experimental and theoretical Insights into mechanism and performance.

Thermal catalytic degradation of formaldehyde (HCHO) over manganese-based catalysts is garnering significant attention. In this study, both theoretical simulations and experimental methods were employed to elucidate the primary reaction pathways of HCHO on the MnO2(110) surface. Specifically, the effects of doping MnO2 with elements such as Fe, Ce, Ni, Co, and Cu on the HCHO oxidation properties were evaluated. Advanced characterization techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET), and X-ray photoelectron spectroscopy (XPS), were employed to discern the physical properties and chemical states of the active components on the catalyst surface. The comprehensive oxidation pathway of HCHO on the MnO2(110) surface includes O2 adsorption and dissociation, HCHO adsorption and dehydrogenation, CO2 desorption, H2O formation and desorption, oxygen vacancy supplementation, and other elementary reactions. The pivotal rate-determining step was identified as the hydrogen migration process, characterized by an energy barrier of 234.19 kJ mol-1. Notably, HCHOO and *CHOO emerged as crucial intermediates during the reaction. Among the doped catalysts, Fe-doped MnO2 outperformed its counterparts doped with Ce, Ni, Co, and Cu. The optimal degradation rate and selectivity were achieved at a molar ratio of Fe: Mn = 0.1. The superior performance of the Fe-doped MnO2 can be ascribed to its large specific surface area, conducive pore structure for HCHO molecular transport, rich surface-adsorbed oxygen species, and a significant presence of oxygen vacancies.

TROP2-directed nanobody-drug conjugate elicited potent antitumor effect in pancreatic cancer.

BACKGROUND: Pancreatic cancer is a highly aggressive malignancy with limited treatment options and a poor prognosis. Trophoblast cell surface antigen 2 (TROP2), a cell surface antigen overexpressed in the tumors of more than half of pancreatic cancer patients, has been identified as a potential target for antibody-drug conjugates (ADCs). Almost all reported TROP2-targeted ADCs are of the IgG type and have been poorly studied in pancreatic cancer. Here, we aimed to develop a novel nanobody-drug conjugate (NDC) targeting TROP2 for the treatment of pancreatic cancer. RESULTS: In this study, we developed a novel TROP2-targeted NDC, HuNbTROP2-HSA-MMAE, for the treatment of TROP2-positive pancreatic cancer. HuNbTROP2-HSA-MMAE is characterized by the use of nanobodies against TROP2 and human serum albumin (HSA) and has a drug-antibody ratio of 1. HuNbTROP2-HSA-MMAE exhibited specific binding to TROP2 and was internalized into tumor cells with high endocytosis efficiency within 5 h, followed by intracellular translocation to lysosomes and release of MMAE to induce cell apoptosis in TROP2-positive pancreatic cancer cells through the caspase-3/9 pathway. In a xenograft model of pancreatic cancer, doses of 0.2 mg/kg and 1 mg/kg HuNbTROP2-HSA-MMAE demonstrated significant antitumor effects, and a dose of 5 mg/kg even eradicated the tumor. CONCLUSION: HuNbTROP2-HSA-MMAE has desirable affinity, internalization efficiency and antitumor activity. It holds significant promise as a potential therapeutic option for the treatment of TROP2-positive pancreatic cancer.

Gene regulatory network from cranial neural crest cells to osteoblast differentiation and calvarial bone development.

Calvarial bone is one of the most complex sequences of developmental events in embryology, featuring a uniquely transient, pluripotent stem cell-like population known as the cranial neural crest (CNC). The skull is formed through intramembranous ossification with distinct tissue lineages (e.g. neural crest derived frontal bone and mesoderm derived parietal bone). Due to CNC's vast cell fate potential, in response to a series of inductive secreted cues including BMP/TGF-ß, Wnt, FGF, Notch, Hedgehog, Hippo and PDGF signaling, CNC enables generations of a diverse spectrum of differentiated cell types in vivo such as osteoblasts and chondrocytes at the craniofacial level. In recent years, since the studies from a genetic mouse model and single-cell sequencing, new discoveries are uncovered upon CNC patterning, differentiation, and the contribution to the development of cranial bones. In this review, we summarized the differences upon the potential gene regulatory network to regulate CNC derived osteogenic potential in mouse and human, and highlighted specific functions of genetic molecules from multiple signaling pathways and the crosstalk, transcription factors and epigenetic factors in orchestrating CNC commitment and differentiation into osteogenic mesenchyme and bone formation. Disorders in gene regulatory network in CNC patterning indicate highly close relevance to clinical birth defects and diseases, providing valuable transgenic mouse models for subsequent discoveries in delineating the underlying molecular mechanisms. We also emphasized the potential regenerative alternative through scientific discoveries from CNC patterning and genetic molecules in interfering with or alleviating clinical disorders or diseases, which will be beneficial for the molecular targets to be integrated for novel therapeutic strategies in the clinic.

Subchronic exposure to PM2.5 induced renal function damage and intestinal microflora changes in rats.

BACKGROUND: Exposure to inhalable environmental particulate matter with a diameter of 2.5 µm or smaller (PM2.5) is associated with decreased or impaired kidney function, but the underlying biological mechanisms are not fully understood. Gut microbiota is an emerging key player in the homeostasis regulation of the gut-kidney axis. Few studies have investigated its role in PM2.5 exposure-induced gut-kidney axis homeostasis abnormalities. METHODS: In this study, a versatile aerosol concentration enrichment system for medium- to long-term whole-body exposure was used to expose Sprague-Dawley rats to filtered air (FA) or concentrated ambient PM2.5 for 12 weeks. A correlation analysis of renal impairment and the intestinal microbiome was performed. RESULTS: The urine flow rate calculation and renal function analysis showed that PM2.5 exposure significantly impaired renal function and increased the urine flow rate. The fecal microbiota analysis showed that renal impairment and increased urine flow rates were consistent with the reduced estimates of the fecal bacteria Chao1, observed-species, Shannon, and Simpson (richness and diversity indices). Pearson's correlation analysis showed that the estimated bacterial richness and diversity were correlated with the urine flow rate and renal function. The linear discriminant analysis effect size (LEfSe) analysis revealed differences between animals exposed to PM2.5 and FA in 25 bacterial groups. Further correlation of a single bacterial taxon with the urine flow rate and renal function showed that the relative abundances of 30, 29, 21, and 50 distinct bacterial groups were significantly correlated with the urine flow rate, estimated glomerular filtration rate (eGFR), serum cystatin C (CysC), and beta-2 microglobulin (ß2-MG), respectively. CONCLUSION: Subchronic exposure to PM2.5 can cause intestinal ecological disorders, which may, in turn, lead to decreased kidney function or the development of impaired kidney function.

Characterization and Genomic Analysis of ɸSHP3, a New Transposable Bacteriophage Infecting Stenotrophomonas maltophilia.

This study describes a novel transposable bacteriophage, ɸSHP3, continuously released by Stenotrophomonas maltophilia strain c31. Morphological observation and genomic analysis revealed that ɸSHP3 is a siphovirus with a 37,611-bp genome that encodes 51 putative proteins. Genomic comparisons indicated that ɸSHP3 is a B3-like transposable phage. Its genome configuration is similar to that of Pseudomonas phage B3, except for the DNA modification module. Similar to B3-like phages, the putative transposase B of ɸSHP3 is a homolog of the type two secretion component ExeA, which is proposed to serve as a potential virulence factor. Moreover, most proteins of ɸSHP3 have homologs in transposable phages, but only ɸSHP3 carries an RdgC-like protein encoded by gene 3, which exhibits exonuclease activity in vitro Two genes and their promoters coding for ɸSHP3 regulatory proteins were identified and appear to control the lytic-lysogenic switch. One of the proteins represses one promoter activity and confers immunity to ɸSHP3 superinfection in vivo The short regulatory region, in addition to the canonical bacterial promoter sequences, displays one LexA and two CpxR recognition sequences. This suggests that LexA and the CpxR/CpxA two-component system might be involved in the control of the ɸSHP3 genetic switch.IMPORTANCES. maltophilia is an emerging global pathogenic bacterium that displays genetic diversity in both environmental and clinical strains. Transposable phages have long been known to improve the genetic diversity of bacterial strains by transposition. More than a dozen phages of S. maltophilia have been characterized. However, no transposable phage infecting S. maltophilia has been reported to date. Characterization of the first transposable phage, ɸSHP3, from S. maltophilia will contribute to our understanding of host-phage interactions and genetic diversity, especially the interchange of genetic materials among S. maltophilia.

Resistance to Bacillus thuringiensis Cry1Ac toxin requires mutations in two Plutella xylostella ATP-binding cassette transporter paralogs.

The diamondback moth, Plutella xylostella, is a cosmopolitan pest and the first species to develop field resistance to toxins from the gram-positive bacterium Bacillus thuringiensis (Bt). Although previous work has suggested that mutations of ATP-binding cassette transporter subfamily C2 (ABCC2) or C3 (ABCC3) genes can confer Cry1Ac resistance, here we reveal that P. xylostella requires combined mutations in both PxABCC2 and PxABCC3 to achieve high-level Cry1Ac resistance, rather than simply a mutation of either gene. We identified natural mutations of PxABCC2 and PxABCC3 that concurrently occurred in a Cry1Ac-resistant strain (Cry1S1000) of P. xylostella, with a mutation (RA2) causing the mis-splicing of PxABCC2 and another mutation (RA3) leading to the premature termination of PxABCC3. Genetic linkage analysis showed that RA2 and RA3 were tightly linked to Cry1Ac resistance. Introgression of RA2 and RA3 enabled a susceptible strain (G88) of P. xylostella to obtain high resistance to Cry1Ac, confirming that these genes confer resistance. To further support the role of PxABCC2 and PxABCC3 in Cry1Ac resistance, frameshift mutations were introduced into PxABCC2 and PxABCC3 singly and in combination in the G88 strain with CRISPR/Cas9 mediated mutagenesis. Bioassays of CRISPR-based mutant strains, plus genetic complementation tests, demonstrated that the deletion of PxABCC2 or PxABCC3 alone provided < 4-fold tolerance to Cry1Ac, while disruption of both genes together conferred >8,000-fold resistance to Cry1Ac, suggesting the redundant/complementary roles of PxABCC2 and PxABCC3. This work advances our understanding of Bt resistance in P. xylostella by demonstrating mutations within both PxABCC2 and PxABCC3 genes are required for high-level Cry1Ac resistance.

Efficient optical reservoir computing for parallel data processing.

We propose and experimentally demonstrate an optical reservoir computing system in free space, using second-harmonic generation for nonlinear kernel functions and a scattering medium to enhance reservoir nodes interconnection. We test it for one-step and multi-step predication of Mackey-Glass time series with different input-mapping methods on a spatial light modulator. For one-step prediction, we achieve 1.8 × 10-3 normalized mean squared error (NMSE). For the multi-step prediction, we explore two different mapping methods: linear-combination and concatenation, achieving 16-step prediction with NMSE as low as 3.5 × 10-4. Robust and superior for multi-step prediction, our approach and design have potential for parallel data processing tasks such as video prediction, speech translation, and so on.

Non-invasive single photon imaging through strongly scattering media.

Non-invasive optical imaging through opaque and multi-scattering media remains highly desirable across many application domains. The random scattering and diffusion of light in such media inflict exponential decay and aberration, prohibiting diffraction-limited imaging. By non-interferometric few picoseconds optical gating of backscattered photons, we demonstrate single photon sensitive non-invasive 3D imaging of targets occluded by strongly scattering media with optical thicknesses reaching 9.5ls (19ls round trip). It achieves diffraction-limited imaging of a target placed 130 cm away through the opaque media, with millimeter lateral and depth resolution while requiring only one photon detection out of 50,000 probe pulses. Our single photon sensitive imaging technique does not require wavefront shaping nor computationally-intensive image reconstruction algorithms, promising practical solutions for diffraction-limited imaging through highly opaque and diffusive media with low illumination power.

Dual-band switched unidirectional Ho:YLF ring laser with wavelength tunability.

Tunable single-longitudinal-mode (SLM) ring Ho:YLF laser with intra-cavity isolator is investigated for 2.05 µm and 2.06 µm band based on single resonator, which is realized dual-band SLM laser conversion by a polarizer. Up to 548 mW SLM power with beam quality factor M2 of 1.1 is achieved at wavelength of 2064.63 nm, and the corresponding slope efficiency is 26.7%. Wavelength tuning ranges from 2063.91 nm to 2065.71 nm and 2050.65nm to 2053.15nm can be demonstrated. The highest SLM power around P12 and R30 CO2 absorption peak of 2064.41 nm and 2050.96 nm are 540 mW and 500 mW, respectively. The power instability within 30 minutes is around 0.14%. As we know, dual-band switched Ho:YLF laser operation at SLM with wavelength tunability is reported for the first time for the potential application of CO2 differential absorption lidar.

Robust and efficient single-pixel image classification with nonlinear optics.

We present a hybrid image classifier by feature-sensitive image upconversion, single pixel photodetection, and deep learning, aiming at fast processing of high-resolution images. It uses partial Fourier transform to extract the images' signature features in both the original and Fourier domains, thereby significantly increasing the classification accuracy and robustness. Tested on the Modified National Institute of Standards and Technology handwritten digit images and verified by simulation, it boosts accuracy from 81.25% (by Fourier-domain processing) to 99.23%, and achieves 83% accuracy for highly contaminated images whose signal-to-noise ratio is only -17dB. Our approach could prove useful for fast lidar data processing, high-resolution image recognition, occluded target identification, and atmosphere monitoring.