Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network.

The advancement of single-cell sequencing technology has smoothed the ability to do biological studies at the cellular level. Nevertheless, single-cell RNA sequencing (scRNA-seq) data presents several obstacles due to the considerable heterogeneity, sparsity and complexity. Although many machine-learning models have been devised to tackle these difficulties, there is still a need to enhance their efficiency and accuracy. Current deep learning methods often fail to fully exploit the intrinsic interconnections within cells, resulting in unsatisfactory results. Given these obstacles, we propose a unique approach for analyzing scRNA-seq data called scMPN. This methodology integrates multi-layer perceptron and graph neural network, including attention network, to execute gene imputation and cell clustering tasks. In order to evaluate the gene imputation performance of scMPN, several metrics like cosine similarity, median L1 distance and root mean square error are used. These metrics are utilized to compare the efficacy of scMPN with other existing approaches. This research utilizes criteria such as adjusted mutual information, normalized mutual information and integrity score to assess the efficacy of cell clustering across different approaches. The superiority of scMPN over current single-cell data processing techniques in cell clustering and gene imputation investigations is shown by the experimental findings obtained from four datasets with gold-standard cell labels. This observation demonstrates the efficacy of our suggested methodology in using deep learning methodologies to enhance the interpretation of scRNA-seq data.

Amorphization Activated Multimetallic Pd Alloys for Boosting Oxygen Reduction Catalysis.

Amorphous nanomaterials have drawn extensive attention owing to their unique features, while amorphization on noble metal nanomaterials still remains formidably challenging. Herein, we demonstrate a universal strategy to synthesize amorphous Pd-based nanomaterials from unary to quinary metals through the introduction of phosphorus (P). The amorphous Pd-based nanoparticles (NPs) exhibit generally promoted oxygen reduction reaction (ORR) activity and durability compared with their crystalline counterparts. Significantly, the quinary P-PdCuNiInSn NPs, benefiting from the amorphous structure and multimetallic component effect, exhibit mass activities as high as 1.04 A mgPd-1 and negligible activity decays of 1.8% among the stability tests, which are much better than values for original Pd NPs (0.134 A mgPd-1 and 28.4%). Experimental and theoretical analyses collectively reveal that the synergy of P-induced amorphization and the expansion of metallic components can considerably lower the free energy changes in the rate-determined step, thereby explaining the positive correlation with the catalytic activity.

Alleviating OH Blockage on the Catalyst Surface by the Puncture Effect of Single-Atom Sites to Boost Alkaline Water Electrolysis.

Nonprecious transition metal catalysts have emerged as the preferred choice for industrial alkaline water electrolysis due to their cost-effectiveness. However, their overstrong binding energy to adsorbed OH often results in the blockage of active sites, particularly in the cathodic hydrogen evolution reaction. Herein, we found that single-atom sites exhibit a puncture effect to effectively alleviate OH blockades, thereby significantly enhancing the alkaline hydrogen evolution reaction (HER) performance. Typically, after anchoring single Ru atoms onto tungsten carbides, the overpotential at 10 mA·cm-2 is reduced by more than 130 mV (159 vs 21 mV). Also, the mass activity is increased 16-fold over commercial Pt/C (MA100 = 17.3 A·mgRu-1 vs 1.1 A·mgPt-1, Pt/C). More importantly, such electrocatalyst-based alkaline anion-exchange membrane water electrolyzers can exhibit an ultralow potential (1.79 Vcell) and high stability at an industrial current density of 1.0 A·cm-2. Density functional theory (DFT) calculations reveal that the isolated Ru sites could weaken the surrounding local OH binding energy, thus puncturing OH blockage and constructing bifunctional interfaces between Ru atoms and the support to accelerate water dissociation. Our findings exhibit generality to other transition metal catalysts (such as Mo) and contribute to the advancement of industrial-scale alkaline water electrolysis.

CRISPR/Cas genome editing in plants: mechanisms, applications, and overcoming bottlenecks.

The CRISPR/Cas systems have emerged as transformative tools for precisely manipulating plant genomes and enhancement. It has provided unparalleled applications from modifying the plant genomes to resistant enhancement. This review manuscript summarises the mechanism, application, and current challenges in the CRISPR/Cas genome editing technology. It addresses the molecular mechanisms of different Cas genes, elucidating their applications in various plants through crop improvement, disease resistance, and trait improvement. The advent of the CRISPR/Cas systems has enabled researchers to precisely modify plant genomes through gene knockouts, knock-ins, and gene expression modulation. Despite these successes, the CRISPR/Cas technology faces challenges, including off-target effects, Cas toxicity, and efficiency. In this manuscript, we also discuss these challenges and outline ongoing strategies employed to overcome these challenges, including the development of novel CRISPR/Cas variants with improved specificity and specific delivery methods for different plant species. The manuscript will conclude by addressing the future perspectives of the CRISPR/Cas technology in plants. Although this review manuscript is not conclusive, it aims to provide immense insights into the current state and future potential of CRISPR/Cas in sustainable and secure plant production.

Unlocking the Effect of Chain Length and Terminal Group on Ethylene Glycol Ether Family Toward Advanced Aqueous Electrolytes.

Constructing high-performance hybrid electrolyte is important to advanced aqueous electrochemical energy storage devices. However, due to the lack of in-depth understanding of how the molecule structures of cosolvent additives influence the properties of electrolytes significantly impeded the development of hybrid electrolytes. Herein, a series of hybrid electrolytes are prepared by using ethylene glycol ether with different chain lengths and terminal groups as additives. The optimized 2 m LiTFSI-90%DDm hybrid electrolyte prepared from diethylene glycol dimethyl ether (DDm) molecule showcases excellent comprehensive performance and significantly enhances the operating voltage of supercapacitors (SCs) to 2.5 V by suppressing the activity of water. Moreover, the SC with 2 m LiTFSI-90%DDm hybrid electrolyte supplies a long-term cycling life of 50 000 cycles at 1 A g-1 with 92.3% capacitance retention as well as excellent low temperature (-40 ºC) cycling performance (10 000 times at 0.2 A g-1). Universally, Zn//polyaniline full cell with 2 m Zn(OTf)2-90%DDm electrolyte manifests outstanding cycling performance in terms of 77.9% capacity retention after 2,000 cycles and a dendrite-free Zn anode. This work inspires new thinking of developing advanced hybrid electrolytes by cosolvent molecule design toward high-performance energy storage devices.

A close-up of regulatory networks and signaling pathways of MKK5 in biotic and abiotic stresses.

Mitogen-activated protein Kinase Kinase 5 (MKK5) is a central hub in the complex phosphorylation chain reaction of the Mitogen-activated protein kinases (MAPK) cascade, regulating plant responses to biotic and abiotic stresses. This review manuscript aims to provide a comprehensive analysis of the regulatory mechanism of the MKK5 involved in stress adaptation. This review will delve into the intricate post-transcriptional and post-translational modifications of the MKK5, discussing how they affect its expression, activity, and subcellular localization in response to stress signals. We also discuss the integration of the MKK5 into complex signaling pathways, orchestrating plant immunity against pathogens and its modulating role in regulating abiotic stresses, such as: drought, cold, heat, and salinity, through the phytohormonal signaling pathways. Furthermore, we highlight potential applications of the MKK5 for engineering stress-resilient crops and provide future perspectives that may pave the way for future studies. This review manuscript aims to provide valuable insights into the mechanisms underlying MKK5 regulation, bridge the gap from numerous previous findings, and offer a firm base in the knowledge of MKK5, its regulating roles, and its involvement in environmental stress regulation.

Bidirectional Enhancement of Nitrogen Removal by Indigenous Synergetic Microalgal-Bacterial Consortia in Harsh Low-C/N Wastewater.

Conventional microalgal-bacterial consortia have limited capacity to treat low-C/N wastewater due to carbon limitation and single nitrogen (N) removal mode. In this work, indigenous synergetic microalgal-bacterial consortia with high N removal performance and bidirectional interaction were successful in treating rare earth tailing wastewaters with low-C/N. Ammonia removal reached 0.89 mg N L-1 h-1, 1.84-fold more efficient than a common microalgal-bacterial system. Metagenomics-based metabolic reconstruction revealed bidirectional microalgal-bacterial interactions. The presence of microalgae increased the abundance of bacterial N-related genes by 1.5- to 57-fold. Similarly, the presence of bacteria increased the abundance of microalgal N assimilation by 2.5- to 15.8-fold. Furthermore, nine bacterial species were isolated, and the bidirectional promotion of N removal by the microalgal-bacterial system was verified. The mechanism of microalgal N assimilation enhanced by indole-3-acetic acid was revealed. In addition, the bidirectional mode of the system ensured the scavenging of toxic byproducts from nitrate metabolism to maintain the stability of the system. Collectively, the bidirectional enhancement system of synergetic microalgae-bacteria was established as an effective N removal strategy to broaden the stable application of this system for the effective treatment of low C/N ratio wastewater.

Newly graphene/polypyrrole (rGO/PPy) modified carbon felt as bio-cathode in bio-electrochemical systems (BESs) achieving complete denitrification.

Nitrate reduction in bio-electrochemical systems (BESs) has attracted wide attention due to its low sludge yields and cost-efficiency advantages. However, the high resistance of traditional electrodes is considered to limit the denitrification performance of BESs. Herein, a new graphene/polypyrrole (rGO/PPy) modified electrode is fabricated via one-step electrodeposition and used as cathode in BES for improving nitrate removal from wastewater. The formation and morphological results support the successful formation of rGO/PPy nanohybrids and confirm the part covalent bonding of Py into GO honeycomb lattices to form a three-dimensional cross-linked spatial structure. The electrochemical tests indicate that the rGO/PPy electrode outperforms the unmodified electrode due to the 3.9-fold increase in electrochemical active surface area and 6.9-fold decrease in the charge transfer resistance (Rct). Batch denitrification activity tests demonstrate that the BES equipped with modified rGO/PPy biocathode could not only achieve the full denitrification efficiency of 100% with energy recovery (15.9 × 10-2 ± 0.14 A/m2), but also favor microbial attach and growth with improved biocompatible surface. This work provides a feasible electrochemical route to fabricate and design a high-performance bioelectrode to enhance denitrification in BESs.

Resourceful application and mechanism of oyster shell-microalgae synergistic system：Sustainable treatment of harsh low carbon nitrogen ratio actual wastewater.

Microalgal technology holds great promise for both low C/N wastewater treatment and resource recovery simultaneously. Nevertheless, the advancement of microalgal technology is hindered by its reduced nitrogen removal efficiency in low C/N ratio wastewater. In this work, microalgae and waste oyster shells were combined to achieve a total inorganic nitrogen removal efficiency of 93.85% at a rate of 2.05 mg L-1 h-1 in low C/N wastewater. Notably, over four cycles of oyster shell reuse, the reactor achieved an average 85% ammonia nitrogen removal extent, with a wastewater treatment cost of only $0.092/ton. Moreover, microbial community analysis during the reuse of oyster shells revealed the critical importance of timely replacement in inhibiting the growth of non-functional bacteria (Poterioochromonas_malhamensi). The work demonstrated that the oyster shell - microalgae system provides a time- and cost-saving, environmental approach for the resourceful treatment of harsh low C/N wastewater.

Risk factors of different mortality periods in older patients with end-stage renal disease undergoing urgent-start peritoneal dialysis: a retrospective observational study.

BACKGROUND: The first six months of therapy represents a high-risk period for peritoneal dialysis (PD) failure. The risk of death in the first six months is higher for older patients treated with urgent-start PD (USPD). However, there are still gaps in research on mortality and risk factors for death in this particular group of patients. We aimed to investigate mortality rates and risk factors for death in older patients with end-stage renal disease (ESRD) receiving USPD within and after six months of therapy. METHODS: We retrospectively studied the clinical information of older adults aged ≥ 65 years with ESRD who received USPD between 2013 and 2019 in five Chinese hospitals. Patients were followed up to June 30, 2020. The mortality and risk factors for death in the first six months of USPD treatment and beyond were analyzed. RESULTS: Of the 379 elderly patients in the study, 130 died over the study period. During the follow-up period, the highest number (45, 34.6%) of deaths occurred within the first six months. Cardiovascular disease was the most common cause of death. The baseline New York Heart Association (NYHA) class III-IV cardiac function [hazard ratio (HR) = 2.457, 95% confidence interval (CI): 1.200-5.030, p = 0.014] and higher white blood cell (WBC) count (HR = 1.082, 95% CI: 1.021-1.147, p = 0.008) increased the mortality risk within six months of USPD. The baseline NYHA class III-IV cardiac function (HR = 1.945, 95% CI: 1.149-3.294, p = 0.013), lower WBC count (HR = 0.917, 95% CI: 0.845-0.996, p = 0.040), lower potassium levels (HR = 0.584, 95% CI: 0.429-0.796, p = 0.001), and higher calcium levels (HR = 2.160, 95% CI: 1.025-4.554, p = 0.043) increased the mortality risk after six months of USPD. CONCLUSION: Different risk factors correlated with mortality in older adults with ESRD within and after six months of undergoing USPD, including baseline NYHA class III-IV cardiac function, WBC count, potassium, and calcium levels.

Selective recycling of lithium from spent LiNixCoyMn1-x-yO2 cathode via constructing a synergistic leaching environment.

The global response to lithium scarcity is overstretched, and it is imperative to explore a green process to sustainably and selectively recover lithium from spent lithium-ion battery (LIB) cathodes. This work investigates the distinct leaching behaviors between lithium and transition metals in pure formic acid and the auxiliary effect of acetic acid as a solvent in the leaching reaction. A formic acid-acetic acid (FA-AA) synergistic system was constructed to selectively recycle 96.81% of lithium from spent LIB cathodes by regulating the conditions of the reaction environment to inhibit the leaching of non-target metals. Meanwhile, the transition metals generate carboxylate precipitates enriched in the leaching residue. The inhibition mechanism of manganese leaching by acetic acid and the leaching behavior of nickel or cobalt being precipitated after release was revealed by characterizations such as XPS, SEM, and FTIR. After the reaction, 90.50% of the acid can be recycled by distillation, and small amounts of the residual Li-containing concentrated solution are converted to battery-grade lithium carbonate by roasting and washing (91.62% recovery rate). This recycling process possesses four significant advantages: i) no additional chemicals are required, ii) the lithium sinking step is eliminated, iii) no waste liquid is discharged, and iv) there is the potential for profitability. Overall, this study provides a novel approach to the waste management technology of lithium batteries and sustainable recycling of lithium resources.

Tandem Electro-Thermo-Catalysis for the Oxidative Aminocarbonylation of Arylboronic Acids to Amides from CO2 and Water.

Direct CO2 electroreduction to valuable chemicals is critical for carbon neutrality, while its main products are limited to simple C1 /C2 compounds, and traditionally, the anodic O2 byproduct is not utilized. We herein report a tandem electrothermo-catalytic system that fully utilizes both cathodic (i.e., CO) and anodic (i.e., O2 ) products during overall CO2 electrolysis to produce valuable organic amides from arylboronic acids and amines in a separate chemical reactor, following the Pd(II)-catalyzed oxidative aminocarbonylation mechanism. Hexamethylenetetramine (HMT)-incorporated silver and nickel hydroxide carbonate electrocatalysts were prepared for efficient coproduction of CO and O2 with Faradaic efficiencies of 99.3 % and 100 %, respectively. Systematic experiments, operando attenuated total reflection surface-enhanced Fourier transform infrared spectroscopy characterizations and theoretical studies reveal that HMT promotes *CO2 hydrogenation/*CO desorption for accelerated CO2 -to-CO conversion, and O2 inhibits reductive deactivation of the Pd(II) catalyst for enhanced oxidative aminocarbonylation, collectively leading to efficient synthesis of 10 organic amides with high yields of above 81 %. This work demonstrates the effectiveness of a tandem electrothermo-catalytic strategy for economically attractive CO2 conversion and amide synthesis, representing a new avenue to explore the full potential of CO2 utilization.

Metal-Free Catalytic Formation of a Donor-Acceptor-Donor Molecule and Its Lewis Acid-Adduct Singlet Diradical with High-Efficient NIR-II Photothermal Conversion.

We have synthesized a quinone-incorporated bistriarylamine donor-acceptor-donor (D-A-D) semiconductor 1 by B(C6F5)3 (BCF) catalyzed C-H/C-H cross coupling via radical ion pair intermediates. Coordination of Lewis acids BCF and Al(ORF)3 (RF=C(CF3)3) to the semiconductor 1 afforded diradical zwitterions 2 and 3 by integer electron transfer. Upon binding to Lewis acids, the LUMO energy of 1 is significantly lowered and the band gap of the semiconductor is significantly narrowed from 1.93 eV (1) to 1.01 eV (2) and 1.06 eV (3). 2 and 3 are rare near-infrared (NIR) diradical dyes with broad absorption both centered around 1500 nm. By introducing a photo BCF generator, 2 can be generated by light-dependent control. Furthermore, the integer electron transfer process can also be reversibly regulated via the addition of CH3CN. In addition, the temperature of 2 sharply increased and reached as high as 110 °C in 10 s upon the irradiation of near-infrared-II (NIR-II) laser (1064 nm, 0.7 W cm-2), exhibiting a fast response to laser. It displays excellent photothermal stability with a photothermal (PT) conversion efficiency of 62.26 % and high-quality PT imaging.

Low-Electronegativity Mn-Contraction of PtMn Nanodendrites Boosts Oxygen Reduction Durability.

Platinum metal (PtM, M=Ni, Fe, Co) alloys catalysts show high oxygen reduction reaction (ORR) activity due to their well-known strain and ligand effects. However, these PtM alloys usually suffer from a deficient ORR durability in acidic environment as the alloyed metal is prone to be dissolved due to its high electronegativity. Herein, we report a new class of PtMn alloy nanodendrite catalyst with low-electronegativity Mn-contraction for boosting the oxygen reduction durability of fuel cells. The moderate strain in PtMn, induced by Mn contraction, yields optimal oxygen reduction activity at 0.53 A mg-1 at 0.9 V versus reversible hydrogen electrode (RHE). Most importantly, we show that relative to well-known high-electronegativity Ni-based Pt alloy counterpart, the PtMn nanodendrite catalyst experiences less transition metals' dissolution in acidic solution and achieves an outstanding mass activity retention of 96 % after 10,000 degradation cycles. Density functional theory calculation reveals that PtMn alloys are thermodynamically more stable than PtNi alloys in terms of formation enthalpy and cohesive energy. The PtMn nanodendrite-based membrane electrode assembly delivers an outstanding peak power density of 1.36 W cm-2 at a low Pt loading and high-performance retention over 50 h operations at 0.6 V in H2 -O2 hydrogen fuel cells.

Detection of diabetic patients in people with normal fasting glucose using machine learning.

BACKGROUND: Diabetes mellitus (DM) is a chronic metabolic disease that could produce severe complications threatening life. Its early detection is thus quite important for the timely prevention and treatment. Normally, fasting blood glucose (FBG) by physical examination is used for large-scale screening of DM; however, some people with normal fasting glucose (NFG) actually have suffered from diabetes but are missed by the examination. This study aimed to investigate whether common physical examination indexes for diabetes can be used to identify the diabetes individuals from the populations with NFG. METHODS: The physical examination data from over 60,000 individuals with NFG in three Chinese cohorts were used. The diabetes patients were defined by HbA1c ≥ 48 mmol/mol (6.5%). We constructed the models using multiple machine learning methods, including logistic regression, random forest, deep neural network, and support vector machine, and selected the optimal one on the validation set. A framework using permutation feature importance algorithm was devised to discover the personalized risk factors. RESULTS: The prediction model constructed by logistic regression achieved the best performance with an AUC, sensitivity, and specificity of 0.899, 85.0%, and 81.1% on the validation set and 0.872, 77.9%, and 81.0% on the test set, respectively. Following feature selection, the final classifier only requiring 13 features, named as DRING (diabetes risk of individuals with normal fasting glucose), exhibited reliable performance on two newly recruited independent datasets, with the AUC of 0.964 and 0.899, the balanced accuracy of 84.2% and 81.1%, the sensitivity of 100% and 76.2%, and the specificity of 68.3% and 86.0%, respectively. The feature importance ranking analysis revealed that BMI, age, sex, absolute lymphocyte count, and mean corpuscular volume are important factors for the risk stratification of diabetes. With a case, the framework for identifying personalized risk factors revealed FBG, age, and BMI as significant hazard factors that contribute to an increased incidence of diabetes. DRING webserver is available for ease of application ( http://www.cuilab.cn/dring ). CONCLUSIONS: DRING was demonstrated to perform well on identifying the diabetes individuals among populations with NFG, which could aid in early diagnosis and interventions for those individuals who are most likely missed.

Vascular Electrical Stimulation with Wireless, Battery-Free, and Fully Implantable Features Reduces Atherosclerotic Plaque Formation Through Sirt1-Mediated Autophagy.

Electrical stimulation (ES) is a safe and effective procedure in clinical rehabilitation with few adverse effects. However, studies on ES for atherosclerosis (AS) are scarce because ES does not provide a long-term intervention for chronic disease processes. Battery-free implants and surgically mounted them in the abdominal aorta of high-fat-fed Apolipoprotein E (ApoE-/- ) mice are used, which are electrically stimulated for four weeks using a wireless ES device to observe changes in atherosclerotic plaques. Results showed that there is almost no growth of atherosclerotic plaque at the stimulated site in AopE-/- mice after ES. RNA-sequencing (RNA-seq) analysis of Thp-1 macrophages reveal that the transcriptional activity of autophagy-related genes increase substantially after ES. Additionally, ES reduces lipid accumulation in macrophages by restoring ABCA1- and ABCG1-mediated cholesterol efflux. Mechanistically, it is demonstrated that ES reduced lipid accumulation through Sirtuin 1 (Sirt1)/Autophagy related 5 (Atg5) pathway-mediated autophagy. Furthermore, ES reverse autophagic dysfunction in macrophages of AopE-/- mouse plaques by restoring Sirt1, blunting P62 accumulation, and inhibiting the secretion of interleukin (IL)-6, resulting in the alleviation of atherosclerotic lesion formation. Here, a novel approach is shown in which ES can be used as a promising therapeutic strategy for AS treatment through Sirt1/Atg5 pathway-mediated autophagy.

Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design.

The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide. Despite many efforts, the development of effective drugs and vaccines for this novel virus will take considerable time. Artificial intelligence (AI) and machine learning (ML) offer promising solutions that could accelerate the discovery and optimization of new antivirals. Motivated by this, in this paper, we present an extensive survey on the application of AI and ML for combating COVID-19 based on the rapidly emerging literature. Particularly, we point out the challenges and future directions associated with state-of-the-art solutions to effectively control the COVID-19 pandemic. We hope that this review provides researchers with new insights into the ways AI and ML fight and have fought the COVID-19 outbreak.

Hepatocellular cystathionine γ lyase/hydrogen sulfide attenuates nonalcoholic fatty liver disease by activating farnesoid X receptor.

BACKGROUND AND AIMS: Hydrogen sulfide (H2 S) plays a protective role in NAFLD. However, whether cystathionine γ lyase (CSE), a dominant H2 S generating enzyme in hepatocytes, has a role in the pathogenesis of NAFLD is currently unclear. APPROACH AND RESULTS: We showed that CSE protein expression is dramatically downregulated, especially in fibrotic areas, in livers from patients with NAFLD. In high-fat diet (HFD)-induced NAFLD mice or an oleic acid-induced hepatocyte model, the CSE/H2 S pathway is also downregulated. To illustrate a regulatory role for CSE in NAFLD, we generated a hepatocyte-specific CSE knockout mouse (CSELKO ). Feeding an HFD to CSELKO mice, they showed more hepatic lipid deposition with increased activity of the fatty acid de novo synthesis pathway, increased hepatic insulin resistance, and higher hepatic gluconeogenic ability compared to CSELoxp control mice. By contrast, H2 S donor treatment attenuated these phenotypes. Furthermore, the protection conferred by H2 S was blocked by farnesoid X receptor (FXR) knockdown. Consistently, serum deoxycholic acid and lithocholic acid (FXR antagonists) were increased, and tauro-ß-muricholic acid (FXR activation elevated) was reduced in CSELKO . CSE/H2 S promoted a post-translation modification (sulfhydration) of FXR at Cys138/141 sites, thereby enhancing its activity to modulate expression of target genes related to lipid and glucose metabolism, inflammation, and fibrosis. Sulfhydration proteomics in patients' livers supported the CSE/H2 S modulation noted in the CSELKO mice. CONCLUSIONS: FXR sulfhydration is a post-translational modification affected by hepatic endogenous CSE/H2 S that may promote FXR activity and attenuate NAFLD. Hepatic CSE deficiency promotes development of nonalcoholic steatohepatitis. The interaction between H2 S and FXR may be amenable to therapeutic drug treatment in NAFLD.

Structured modulation multi-height microscopy for high-resolution imaging.

Conventional multi-height microscopy techniques introduce different object-to-detector distances to obtain multiple measurements for phase retrieval. However, surpassing the diffraction limit imposed by the numerical aperture (NA) of the objective lens remains a challenging task. Here, we report a novel structured modulation multi-height microscopy technique for quantitative high-resolution imaging. In our platform, a thin diffuser is placed in between the sample and the objective lens. By translating the diffuser to different axial positions, a sequence of modulated intensity images is captured for reconstruction. The otherwise inaccessible high-resolution object information can thus be encoded into the optical system for detection. In the construction process, we report a ptychographic phase retrieval algorithm to recover the existing wavefront of the complex object. We validate our approach using a resolution target, a phase target, and various biological samples. We demonstrate a ∼4-fold resolution gain over the diffraction limit. We also demonstrate our approach to achieve a 6.5 mm by 4.3 mm field of view and a half-pitch resolution of 1.2 µm. The reported methodology provides a portable, turnkey solution for quantitative high-resolution imaging with potential applications in disease diagnosis, sample screening, and other fields.

Remote referencing strategy for high-resolution coded ptychographic imaging.

The applications of conventional ptychography are limited by its relatively low resolution and throughput in the visible light regime. The new development of coded ptychography (CP) has addressed these issues and achieved the highest numerical aperture for large-area optical imaging in a lensless configuration. A high-quality reconstruction of CP relies on precise tracking of the coded sensor's positional shifts. The coded layer on the sensor, however, prevents the use of cross correlation analysis for motion tracking. Here we derive and analyze the motion tracking model of CP. A novel, to the best of our knowledge, remote referencing scheme and its subsequent refinement pipeline are developed for blind image acquisition. By using this approach, we can suppress the correlation peak caused by the coded surface and recover the positional shifts with deep sub-pixel accuracy. In contrast with common positional refinement methods, the reported approach can be disentangled from the iterative phase retrieval process and is computationally efficient. It allows blind image acquisition without motion feedback from the scanning process. It also provides a robust and reliable solution for implementing ptychography with high imaging throughput. We validate this approach by performing high-resolution whole slide imaging of bio-specimens.