Robust single-shot 3D fluorescence imaging in scattering media with a simulator-trained neural network.

Imaging through scattering is a pervasive and difficult problem in many biological applications. The high background and the exponentially attenuated target signals due to scattering fundamentally limits the imaging depth of fluorescence microscopy. Light-field systems are favorable for high-speed volumetric imaging, but the 2D-to-3D reconstruction is fundamentally ill-posed, and scattering exacerbates the condition of the inverse problem. Here, we develop a scattering simulator that models low-contrast target signals buried in heterogeneous strong background. We then train a deep neural network solely on synthetic data to descatter and reconstruct a 3D volume from a single-shot light-field measurement with low signal-to-background ratio (SBR). We apply this network to our previously developed computational miniature mesoscope and demonstrate the robustness of our deep learning algorithm on scattering phantoms with different scattering conditions. The network can robustly reconstruct emitters in 3D with a 2D measurement of SBR as low as 1.05 and as deep as a scattering length. We analyze fundamental tradeoffs based on network design factors and out-of-distribution data that affect the deep learning model's generalizability to real experimental data. Broadly, we believe that our simulator-based deep learning approach can be applied to a wide range of imaging through scattering techniques where experimental paired training data is lacking.

Predicting the Dynamic Interaction of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) participate in various biological processes. Interactions involving IDPs are usually dynamic and are affected by their inherent conformation fluctuations. Comprehensive characterization of these interactions based on current techniques is challenging. Here, we present GSALIDP, a GraphSAGE-embedded LSTM network, to capture the dynamic nature of IDP-involved interactions and predict their behaviors. This framework models multiple conformations of IDP as a dynamic graph, which can effectively describe the fluctuation of its flexible conformation. The dynamic interaction between IDPs is studied, and the data sets of IDP conformations and their interactions are obtained through atomistic molecular dynamic (MD) simulations. Residues of IDP are encoded through a series of features including their frustration. GSALIDP can effectively predict the interaction sites of IDP and the contact residue pairs between IDPs. Its performance in predicting IDP interactions is on par with or even better than the conventional models in predicting the interaction of structural proteins. To the best of our knowledge, this is the first model to extend the protein interaction prediction to IDP-involved interactions.

Fourier ptychographic topography.

Topography measurement is essential for surface characterization, semiconductor metrology, and inspection applications. To date, performing high-throughput and accurate topography remains challenging due to the trade-off between field-of-view (FOV) and spatial resolution. Here we demonstrate a novel topography technique based on the reflection-mode Fourier ptychographic microscopy, termed Fourier ptychograhpic topography (FPT). We show that FPT provides both a wide FOV and high resolution, and achieves nanoscale height reconstruction accuracy. Our FPT prototype is based on a custom-built computational microscope consisting of programmable brightfield and darkfield LED arrays. The topography reconstruction is performed by a sequential Gauss-Newton-based Fourier ptychographic phase retrieval algorithm augmented with total variation regularization. We achieve a synthetic numerical aperture (NA) of 0.84 and a diffraction-limited resolution of 750 nm, increasing the native objective NA (0.28) by 3×, across a 1.2 × 1.2 mm2 FOV. We experimentally demonstrate the FPT on a variety of reflective samples with different patterned structures. The reconstructed resolution is validated on both amplitude and phase resolution test features. The accuracy of the reconstructed surface profile is benchmarked against high-resolution optical profilometry measurements. In addition, we show that the FPT provides robust surface profile reconstructions even on complex patterns with fine features that cannot be reliably measured by the standard optical profilometer. The spatial and temporal noise of our FPT system is characterized to be 0.529 nm and 0.027 nm, respectively.

Assessing Long-Term Cycling Stability of Single-Crystal Versus Polycrystalline Nickel-Rich NCM in Pouch Cells with 6 mAh cm-2 Electrodes.

Lithium-ion batteries based on single-crystal LiNi1- x - y Cox Mny O2 (NCM, 1-x-y ≥ 0.6) cathode materials are gaining increasing attention due to their improved structural stability resulting in superior cycle life compared to batteries based on polycrystalline NCM. However, an in-depth understanding of the less pronounced degradation mechanism of single-crystal NCM is still lacking. Here, a detailed postmortem study is presented, comparing pouch cells with single-crystal versus polycrystalline LiNi0.60 Co0.20 Mn0.20 O2 (NCM622) cathodes after 1375 dis-/charge cycles against graphite anodes. The thickness of the cation-disordered layer forming in the near-surface region of the cathode particles does not differ significantly between single-crystal and polycrystalline particles, while cracking is pronounced for polycrystalline particles, but practically absent for single-crystal particles. Transition metal dissolution as quantified by time-of-flight mass spectrometry on the surface of the cycled graphite anode is much reduced for single-crystal NCM622. Similarly, CO2 gas evolution during the first two cycles as quantified by electrochemical mass spectrometry is much reduced for single-crystal NCM622. Benefitting from these advantages, graphite/single-crystal NMC622 pouch cells are demonstrated with a cathode areal capacity of 6 mAh cm-2 with an excellent capacity retention of 83% after 3000 cycles to 4.2 V, emphasizing the potential of single-crystalline NCM622 as cathode material for next-generation lithium-ion batteries.

Modeling and Evaluation of the Joint Prevention and Control Mechanism for Curbing COVID-19 in Wuhan.

The spread of COVID-19 in Wuhan was successfully curbed under the strategy of "Joint Prevention and Control Mechanism." To understand how this measure stopped the epidemics in Wuhan, we establish a compartmental model with time-varying parameters over different stages. In the early stage of the epidemic, due to resource limitations, the number of daily reported cases may lower than the actual number. We employ a dynamic-based approach to calibrate the accumulated clinically diagnosed data with a sudden jump on February 12 and 13. The model simulation shows reasonably good match with the adjusted data which allows the prediction of the cumulative confirmed cases. Numerical results reveal that the "Joint Prevention and Control Mechanism" played a significant role on the containment of COVID-19. The spread of COVID-19 cannot be inhibited if any of the measures was not effectively implemented. Our analysis also illustrates that the Fangcang Shelter Hospitals are very helpful when the beds in the designated hospitals are insufficient. Comprised with Fangcang Shelter Hospitals, the designated hospitals can contain the transmission of COVID-19 more effectively. Our findings suggest that the combined multiple measures are essential to curb an ongoing epidemic if the prevention and control measures can be fully implemented.

Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a public health emergency of global concern. We aimed to explore the risk factors of 14-day and 28-day mortality and develop a model for predicting 14-day and 28-day survival probability among adult hospitalized patients with COVID-19. METHODS: In this multicenter, retrospective, cohort study, we examined 828 hospitalized patients with confirmed COVID-19 hospitalized in Wuhan Union Hospital and Central Hospital of Wuhan between January 12 and February 9, 2020. Among the 828 patients, 516 and 186 consecutive patients admitted in Wuhan Union Hospital were enrolled in the training cohort and the validation cohort, respectively. A total of 126 patients hospitalized in Central Hospital of Wuhan were enrolled in a second external validation cohort. Demographic, clinical, radiographic, and laboratory measures; treatment; proximate causes of death; and 14-day and 28-day mortality are described. Patients' data were collected by reviewing the medical records, and their 14-day and 28-day outcomes were followed up. RESULTS: Of the 828 patients, 146 deaths were recorded until May 18, 2020. In the training set, multivariate Cox regression indicated that older age, lactate dehydrogenase level over 360 U/L, neutrophil-to-lymphocyte ratio higher than 8.0, and direct bilirubin higher than 5.0 µmol/L were independent predictors of 28-day mortality. Nomogram scoring systems for predicting the 14-day and 28-day survival probability of patients with COVID-19 were developed and exhibited strong discrimination and calibration power in the two external validation cohorts (C-index, 0.878 and 0.839). CONCLUSION: Older age, high lactate dehydrogenase level, evaluated neutrophil-to-lymphocyte ratio, and high direct bilirubin level were independent predictors of 28-day mortality in adult hospitalized patients with confirmed COVID-19. The nomogram system based on the four factors revealed good discrimination and calibration, suggesting good clinical utility.

Dynamic behaviors of interfacial water on the self-assembly monolayer (SAM) heterogeneous surface.

Dynamic behaviors of water molecules near the surface with mixed hydrophobic and hydrophilic areas are studied by molecular dynamics simulation. More specifically, the diffusion coefficient and hydrogen bond lifetime of interfacial water on the self-assembly monolayer composed of hydrophobic and hydrophilic groups and their dependence on the mixing ratio are studied. The diffusion dramatically slows down, and the hydrogen bond lifetime considerably increases when a few hydrophilic groups are added to the hydrophobic surface. When the percentage of hydrophilic groups increases to 25%, the behavior of interfacial water is similar to the case of the pure hydrophilic surface. The sensitivity to the hydrophilic group can be attributed to the fact that the grafted hydrophilic groups can not only retard the directly bound water molecules but also affect indirectly bound water by stabilizing hydrogen bonds among interfacial water molecules.

The Role of Interleukin-17 in Lung Cancer.

Tumour-associated inflammation is a hallmark of malignant carcinomas, and lung cancer is a typical inflammation-associated carcinoma. Interleukin-17 (IL-17) is an important inflammatory cytokine that plays an important role in chronic inflammatory and autoimmune diseases and in inflammation-associated tumours. Numerous studies have shown that IL-17 directly or indirectly promotes tumour angiogenesis and cell proliferation and that it inhibits apoptosis via the activation of inflammatory signalling pathways. Therefore, IL-17 contributes to the metastasis and progression of lung cancer. Research advances with respect to the role of IL-17 in lung cancer will be presented as a review in this paper.

Wet Conformation of Prion-Like Domain and Intimate Correlation of Hydration and Conformational Fluctuations.

Proteins with prion-like domains (PLDs) are involved in neurodegeneration-associated aggregation and are prevalent in liquid-like membrane-less organelles. These PLDs contain amyloidogenic stretches but can maintain dynamic disordered conformations, even in the condensed phase. However, the molecular mechanism underlying such intricate conformational properties of PLDs remains elusive. Here we employed molecular dynamics simulations to investigate the conformational properties of a prototypical PLD system (i.e., FUS PLD). According to our simulation results, PLD adopts a wet collapsed conformation, wherein most residues maintain sufficient hydration with the abundance of internal water. These internal water molecules can rapidly exchange between the protein interior and the bulk, enabling intensive coupling of the entire protein with its hydration environment. The dynamic exchange of water molecules is intimately correlated to the overall conformational fluctuations of PLD. Furthermore, the abundance of dynamic internal water suppresses the formation of aggregation-prone ordered structures. These results collectively elucidate the crucial role of internal water in sustaining the dynamic disordered conformation of the PLD and inhibiting its aggregation propensity.

HiLo microscopy with caustic illumination.

HiLo microscopy is an optical sectioning structured illumination microscopy technique based on computationally combining two images: one with uniform illumination and the other with structured illumination. The most widely used structured illumination in HiLo microscopy is random speckle patterns, due to their simplicity and resilience to tissue scattering. Here, we present a novel HiLo microscopy strategy based on random caustic patterns. Building on an off-the-shelf diffuser and a low-coherence LED source, we demonstrate that caustic HiLo can achieve 4.5 µm optical sectioning capability with a 20× 0.75 NA objective. In addition, with the distinct intensity statistical properties of caustic patterns, we show that our caustic HiLo outperforms speckle HiLo, achieving enhanced optical sectioning capability and preservation of fine features by imaging scattering fixed brain sections of 100 µm, 300 µm, and 500 µm thicknesses. We anticipate that this new structured illumination technique may find various biomedical imaging applications.

EventLFM: event camera integrated Fourier light field microscopy for ultrafast 3D imaging.

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product (SBP). Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems, thus restricting data throughput to maintain high SBP at limited frame rates. To address this, we introduce EventLFM, a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy (LFM), a state-of-the-art single-shot 3D wide-field imaging technique. The event camera operates on a novel asynchronous readout architecture, thereby bypassing the frame rate limitations inherent to conventional CMOS systems. We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM. Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates. Furthermore, we highlight EventLFM's capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C. elegans. We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

Oxides Induced Preferential Growth of {110} Planes for Superior Performance Single-Crystal LiMn2O4 through Solid-State Process.

Polycrystalline lithium manganese oxide (LMO) is known to suffer from severe surface structure degradation and electrochemical polarization due to its mixed crystal plane orientations. A hexagonal prism single-crystal LMO (LMOS-HP), engineered through the SrO-induced preferential growth effect, features the most stable {111} top surfaces and the fastest Li+ diffusion {110} side surfaces, effectively addressing these challenges. Consequently, LMOS-HP exhibits superior electrochemical capability, with only 0.021% capacity fading per cycle after 500 cycles and achieves a discharge capacity of 81.9 mAh g-1 at 20C. This innovative design offers a promising approach for tuning surface crystal orientation to improve performance.

Syntheses of LiMn2O4 nanoparticles with nano-size precursor and its electrochemistry performance.

LiMn2O4 nanoparticles were prepared by solid state reaction with nano-size Mn3O4 precursor. Mn3O4 nanoparticles with the size of about 200 nm were prepared via controlled crystallization method, which were used as the precursor to prepare LiMn2O4 in nanometer size. The size of LiMn2O4 synthesized by the route is about 300 nm. Cyclic voltammetry shows two pairs of clearly-separated oxidation peaks, located at 4.07 and 4.19 V, and reduction peaks, located at 3.91 and 4.07 V. The as-synthesized LiMn2O4 nanoparticles exhibit good electrochemical performance with an initial discharge capacity of 125.9 mAh x g(-1) at a current density of 14.8 mA x g(-1). The LiMn2O4 nanoparticles show wonderful cycle ability and the capacity retention ratio is 92.1% after 650 cycles at the current density of 296 mA x g(-1).

Pupil engineering for extended depth-of-field imaging in a fluorescence miniscope.

Significance: Fluorescence head-mounted microscopes, i.e., miniscopes, have emerged as powerful tools to analyze in-vivo neural populations but exhibit a limited depth-of-field (DoF) due to the use of high numerical aperture (NA) gradient refractive index (GRIN) objective lenses. Aim: We present extended depth-of-field (EDoF) miniscope, which integrates an optimized thin and lightweight binary diffractive optical element (DOE) onto the GRIN lens of a miniscope to extend the DoF by 2.8× between twin foci in fixed scattering samples. Approach: We use a genetic algorithm that considers the GRIN lens' aberration and intensity loss from scattering in a Fourier optics-forward model to optimize a DOE and manufacture the DOE through single-step photolithography. We integrate the DOE into EDoF-Miniscope with a lateral accuracy of 70 µm to produce high-contrast signals without compromising the speed, spatial resolution, size, or weight. Results: We characterize the performance of EDoF-Miniscope across 5- and 10-µm fluorescent beads embedded in scattering phantoms and demonstrate that EDoF-Miniscope facilitates deeper interrogations of neuronal populations in a 100-µm-thick mouse brain sample and vessels in a whole mouse brain sample. Conclusions: Built from off-the-shelf components and augmented by a customizable DOE, we expect that this low-cost EDoF-Miniscope may find utility in a wide range of neural recording applications.

Robust single-shot 3D fluorescence imaging in scattering media with a simulator-trained neural network.

Imaging through scattering is a pervasive and difficult problem in many biological applications. The high background and the exponentially attenuated target signals due to scattering fundamentally limits the imaging depth of fluorescence microscopy. Light-field systems are favorable for high-speed volumetric imaging, but the 2D-to-3D reconstruction is fundamentally ill-posed, and scattering exacerbates the condition of the inverse problem. Here, we develop a scattering simulator that models low-contrast target signals buried in heterogeneous strong background. We then train a deep neural network solely on synthetic data to descatter and reconstruct a 3D volume from a single-shot light-field measurement with low signal-to-background ratio (SBR). We apply this network to our previously developed Computational Miniature Mesoscope and demonstrate the robustness of our deep learning algorithm on scattering phantoms with different scattering conditions. The network can robustly reconstruct emitters in 3D with a 2D measurement of SBR as low as 1.05 and as deep as a scattering length. We analyze fundamental tradeoffs based on network design factors and out-of-distribution data that affect the deep learning model's generalizability to real experimental data. Broadly, we believe that our simulator-based deep learning approach can be applied to a wide range of imaging through scattering techniques where experimental paired training data is lacking.

Mechanistic Insight on General Protein-Binding Ability of ATP and the Impacts of Arginine Residues.

Recent experiments suggested that adenosine triphosphate (ATP) can regulate liquid-liquid phase separation (LLPS) of various proteins and inhibit protein aggregations at its physiological concentration, which is highly correlated with the nonspecific interactions of ATP to a wide variety of proteins. However, the mechanism underlying the general binding capability of ATP largely remains unclear. In this work, we used molecular dynamics simulation to study the binding of ATPs to three proteins with distinct net charges: TDP-43 NTD (-7 e), TAF15-RRM (0 e), HWEL (+8 e). Negatively charged ATP exhibits a strong trend to accumulate around all of these proteins. While only a fraction of the accumulated ATPs directly binds to the limited regions of the protein surface, additional ATPs indirectly bind to proteins by aggregating into ATP clusters. Hence, the proportion of the directly bound ATPs in the clusters as well as their binding regions can be adjusted in response to different proteins, which makes ATP well adapted to a variety of proteins. Moreover, our results suggest that ATP tightly binds to Arg with high affinity, and Arg dominates the direct binding of ATP. Meanwhile, Arg also affects the self-association of accumulated ATPs. The size of the ATP cluster is effectively regulated by the distribution of Arg. Considering the ubiquity of Arg in proteins, our findings are helpful to understand the general binding capability of ATP.

Deep-learning-augmented computational miniature mesoscope.

Fluorescence microscopy is essential to study biological structures and dynamics. However, existing systems suffer from a trade-off between field of view (FOV), resolution, and system complexity, and thus cannot fulfill the emerging need for miniaturized platforms providing micron-scale resolution across centimeter-scale FOVs. To overcome this challenge, we developed a computational miniature mesoscope (CM2) that exploits a computational imaging strategy to enable single-shot, 3D high-resolution imaging across a wide FOV in a miniaturized platform. Here, we present CM2 V2, which significantly advances both the hardware and computation. We complement the 3 × 3 microlens array with a hybrid emission filter that improves the imaging contrast by 5×, and design a 3D-printed free-form collimator for the LED illuminator that improves the excitation efficiency by 3×. To enable high-resolution reconstruction across a large volume, we develop an accurate and efficient 3D linear shift-variant (LSV) model to characterize spatially varying aberrations. We then train a multimodule deep learning model called CM2Net, using only the 3D-LSV simulator. We quantify the detection performance and localization accuracy of CM2Net to reconstruct fluorescent emitters under different conditions in simulation. We then show that CM2Net generalizes well to experiments and achieves accurate 3D reconstruction across a ~7-mm FOV and 800-µm depth, and provides ~6-µm lateral and ~25-µm axial resolution. This provides an ~8× better axial resolution and ~1400× faster speed compared to the previous model-based algorithm. We anticipate this simple, low-cost computational miniature imaging system will be useful for many large-scale 3D fluorescence imaging applications.

Prototype endoscopic photoacoustic-ultrasound balloon catheter for characterizing intestinal obstruction.

In our previous studies, we have demonstrated the feasibility of characterizing intestinal inflammation and fibrosis using endoscopic photoacoustic imaging. Purposed at te clinical translation of the imaging technology, we developed a photoacoustic/ultrasound imaging probe by integrating a miniaturized ultrasound array and an angle-tipped optical fiber in a hydrostatic balloon catheter. When collapsed, the catheter probe may potentially be compatible with a clinical ileo-colonoscope. In addition, the flexible surface of the hydrostatic balloon allows for acoustic coupling at the uneven surfaces of the gas-filled intestine. Tissue phantom studies show that the catheter probe possesses an imaging penetration of at least 12 mm. Experiments with a rabbit model in vivo validated the probe in differentiating normal, acute and chronic conditions in intestinal obstruction.

Enabling high energy lithium metal batteries via single-crystal Ni-rich cathode material co-doping strategy.

High-capacity Ni-rich layered oxides are promising cathode materials for secondary lithium-based battery systems. However, their structural instability detrimentally affects the battery performance during cell cycling. Here, we report an Al/Zr co-doped single-crystalline LiNi0.88Co0.09Mn0.03O2 (SNCM) cathode material to circumvent the instability issue. We found that soluble Al ions are adequately incorporated in the SNCM lattice while the less soluble Zr ions are prone to aggregate in the outer SNCM surface layer. The synergistic effect of Al/Zr co-doping in SNCM lattice improve the Li-ion mobility, relief the internal strain, and suppress the Li/Ni cation mixing upon cycling at high cut-off voltage. These features improve the cathode rate capability and structural stabilization during prolonged cell cycling. In particular, the Zr-rich surface enables the formation of stable cathode-electrolyte interphase, which prevent SNCM from unwanted reactions with the non-aqueous fluorinated liquid electrolyte solution and avoid Ni dissolution. To prove the practical application of the Al/Zr co-doped SNCM, we assembled a 10.8 Ah pouch cell (using a 100 µm thick Li metal anode) capable of delivering initial specific energy of 504.5 Wh kg-1 at 0.1 C and 25 °C.

Enhancing Surface Chemical Stability of LiMn2 O4 Cathode by Strontium Enrichment at Grain Boundaries.

LiMn2 O4 (LMO) cathodes suffer from limited cycle life, resulting from Mn dissolution and side reactions between electrode and electrolyte. In this study, Sr-modified LMO is prepared by using a simple strategy. The nature and position of large-radius Sr ions are investigated, alongside their influence on the structural stability of the bulk. SrMnO3 (SMO) is found to be enriched at grain boundaries of LMO, with Mn-O-Sr bonds forming at the SMO/LMO interface. Furthermore, stable SMO alleviates the migration of Mn ions in LMO associated with structural integrity and suppresses side reactions between the electrode and electrolyte. The modified LMO cathodes maintain their structural integrity and display improved rate performance and cycling stability under harsh conditions. Remarkably, the discharge capacity of a Sr-modified LMO||Li half-cell maintains 94.8 % at 25 °C and 79.6 % at 55 °C after 500 cycles. Consequently, enrichment of strontium at grain boundaries presents a promising strategy for developing cathodes for long-term use.