Hyperuricemia is associated with heart failure readmission in patients with heart failure and preserved ejection fraction-an observational study in Chinese.

BACKGROUND AND AIMS: This study aimed to explore the association between hyperuricemia and heart failure (HF) readmission in HF patients with preserved ejection fraction (HFpEF) because the impact of hyperuricemia on the prognosis of these patients has not been fully understood. METHODS AND RESULTS: This retrospective observational study included 538 hospitalized patients diagnosed with HFpEF. A total of 57.6 % of patients with HFpEF suffered from hyperuricemia (serum uric acid (SUA) was >7 mg/dL in men and >6 mg/dL in women). Compared to those without hyperuricemia, patients with hyperuricemia were more likely to be female (62.6 % vs. 53.9 %, p = 0.044) and older (78.0 ± 8.4 vs. 75.9 ± 9.0 years, p = 0.008). Our Cox analysis revealed that SUA level (hazard ratio (HR) = 1.158, 95 % confidence interval (CI): 1.087-1.234, p<0.001) and hyperuricemia (HR = 1.846, 95 % CI: 1.308-2.606, p<0.001) were associated with HF readmission in patients with HFpEF, respectively. Kaplan-Meier analysis showed that patients with hyperuricemia had a significantly worse prognosis (p<0.001). The receiver operating characteristic analysis revealed that the area under the ROC curve of SUA for predicting HF readmission was 0.6276 (95 % CI: 0.5763-0.6790) and a designated cut-off value of 7.53 mg/dL. CONCLUSIONS: Hyperuricemia is a common comorbidity among patients with HFpEF. Moreover, SUA level and hyperuricemia have been shown to be associated with HF readmission. Therefore, it is meaningful to monitor SUA levels in patients with HFpEF during the whole treatment period of HF. Whereas, whether intervention of hyperuricemia could benefit patients with HFpEF needs further studies.

Cystatin C and sarcopenia index are associated with cardiovascular and all-cause death among adults in the United States.

OBJECTIVES: This study aimed to investigate the association of cystatin C, serum creatinine and sarcopenia index with cardiovascular and all-cause death in general population. METHODS: Data of participants from the National Health and Nutrition Examination Surveys (NHANES) from 1999 to 2004 were used and all participants were followed up regularly until December 31, 2019. Multivariable Cox analysis was used to investigate the association of cystatin C, serum creatinine and sarcopenia index with cardiovascular and all-cause death. Restricted cubic spline was conducted to evaluate the nonlinear association. RESULTS: A total of 9894 participants with a mean age of 45.64 years were enrolled and followed up for a mean duration of 15.62 ± 4.68 years. Approximately 50.3% were male and there were a total of 2681 all-cause deaths and 691 cardiovascular deaths recorded during the follow-up period. In final adjusted model, compared with the first quartile of cystatin C (< 0.659 mg/L), the risk of cardiovascular and all-cause death increased 2.36-fold and 1.71-fold for participants in the fourth quartile (≥ 0.877 mg/L) (HR: 3.36, 95% CI: 2.06-5.46, P < 0.001; HR: 2.71, 95% CI: 2.17-3.38, P < 0.001; respectively). Furthermore, a higher sarcopenia index (< 88.41 vs. ≥125.52) was associated with the reduced risk of cardiovascular death (HR: 0.41, 95% CI: 0.31-0.53, P < 0.001) as well as all-cause death (HR: 0.41, 95% CI: 0.35-0.49, P < 0.001). Additionally, restricted cubic splines showed that there was a nonlinear relationship between sarcopenia index levels and all-cause death while there was a linear relationship between sarcopenia index levels and cardiovascular death. CONCLUSIONS: Higher sarcopenia index was associated with the decreased risk of cardiovascular and all-cause death in general population in the United States. Elevated cystatin C was positively associated with cardiovascular and all-cause death.

[Study on direct ventricular assist loading mode based on a finite element method].

To investigate the biomechanical effects of direct ventricular assistance and explore the optimal loading mode, this study established a left ventricular model of heart failure patients based on the finite element method. It proposed a loading mode that maintains peak pressure compression, and compared it with the traditional sinusoidal loading mode from both hemodynamic and biomechanical perspectives. The results showed that both modes significantly improved hemodynamic parameters, with ejection fraction increased from a baseline of 29.33% to 37.32% and 37.77%, respectively, while peak pressure, stroke volume, and stroke work parameters also increased. Additionally, both modes showed improvements in stress concentration and excessive fiber strain. Moreover, considering the phase error of the assist device's working cycle, the proposed assist mode in this study was less affected. Therefore, this research may provide theoretical support for the design and optimization of direct ventricular assist devices.

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.

Air-laser-based coherent Raman spectroscopy of atmospheric molecules in a filamentary plasma grating.

Coherent Raman spectroscopy (CRS) with air-laser-based hybrid femtosecond/picosecond (fs/ps) pulses has shown promising potential for remote detection and surveillance of atmospheric species with high temporal and frequency resolution. Here, to enhance the sensitivity and extend the detection distance, we generate the CRS spectra of air molecules in situ in a filamentary plasma grating, and show that the grating can efficiently enhance the intensities of the coherent vibrational Raman lines of N2, O2, and N2 + by 2-3 orders of magnitude at an extended distance. By examining the intensities of the Raman lines, fs-pulsed supercontinuum, and ps-pulsed air laser produced under different grating conditions, we reveal that the optimization of the Raman lines is achieved by the dynamic balance between the supercontinuum-induced vibrational coherence and air-laser-induced polarization of the air species.

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.

FedDroidMeter: A Privacy Risk Evaluator for FL-Based Android Malware Classification Systems.

In traditional centralized Android malware classifiers based on machine learning, the training sample uploaded by users contains sensitive personal information, such as app usage and device security status, which will undermine personal privacy if used directly by the server. Federated-learning-based Android malware classifiers have attracted much attention due to their privacy-preserving and multi-party joint modeling. However, research shows that indirect privacy inferences from curious central servers threaten this framework. We propose a privacy risk evaluation framework, FedDroidMeter, based on normalized mutual information in response to user privacy requirements to measure the privacy risk in FL-based malware classifiers. It captures the essential cause of the disclosure of sensitive information in classifiers, independent of the attack model and capability. We performed numerical assessments using the Androzoo dataset, the baseline FL-based classifiers, the privacy-inferred attack model, and the baseline methodology of privacy evaluation. The experimental results show that FedDroidMeter can measure the privacy risks of the classifiers more effectively. Meanwhile, by comparing different models, FL, and privacy parameter settings, we proved that FedDroidMeter could compare the privacy risk between different use cases equally. Finally, we preliminarily study the law of privacy risk in classifiers. The experimental results emphasize the importance of providing a systematic privacy risk evaluation framework for FL-based malware classifiers and provide experience and a theoretical basis for studying targeted defense methods.

Effect of co-toxicity of lead and nanoplastics on the flavonoid biosynthetic pathway in dandelion (Taraxacum asiaticum Dahlst).

MAIN CONCLUSION: Negatively charged carboxy-polystyrene (CPS) and positively charged amino-polystyrene (NPS) could significantly inhibit the biomass and flavonoid content of dandelion roots and leaves, and the inhibitory effect of NPS was stronger than that of CPS. The increasingly serious pollution of microplastics and heavy metals is likely to affect the efficacy of flavonoids synthesized by dandelion in natural medicine fields. Therefore, we combined hydroponic experiments with computational chemistry (Gaussian and autodock analysis) to explore the mechanism by which amino-polystyrene (NPS), carboxy-polystyrene (CPS), and lead affect the flavonoid biosynthetic pathway in dandelion (Taraxacum asiaticum Dahlst). Our results show that CPS and NPS could significantly inhibit the biomass and flavonoid content of dandelion roots and leaves, and the inhibitory effect of NPS was stronger than that of CPS. Mechanistic studies showed that CPS and NPS increased the content of O2- and H2O2 in dandelion roots and leaves, causing membrane lipid peroxidation, resulting in cell damage and decreased biomass. CPS and NPS inhibited related enzymatic activities by affecting their tertiary structures, resulting in a decrease in phenolic acid, coumaroyl-CoA, and flavonoid content. Dandelion preferred to absorb positively charged NPS compared to negatively charged CPS, but CPS inhibited the uptake of Pb by dandelion more strongly than NPS. Pb promoted CPS agglomeration and increased the surface positive charge of CPS through coordination bonds and hydrogen bonds, so more CPS entered dandelion under CPS + Pb treatment than under CPS alone. Although NPS and CPS reduced the uptake of Pb by dandelion, the biomass and flavonoid contents of dandelion were lower than those of single Pb treatment because of the higher toxicity of NPS and CPS than Pb. Pb significantly increased the effect of CPS on the root biomass of dandelion compared with CPS alone by increasing the positive charge of CPS. We suggest that microplastics with different charges and lead composite pollution inhibit dandelion flavonoid biosynthesis and provide a reference for the loss of dandelion medicinal components and economic value.

Deep learning-enabled whole slide imaging (DeepWSI): oil-immersion quality using dry objectives, longer depth of field, higher system throughput, and better functionality.

Whole slide imaging (WSI) has moved the traditional manual slide inspection process to the era of digital pathology. A typical WSI system translates the sample to different positions and captures images using a high numerical aperture (NA) objective lens. Performing oil-immersion microscopy is a major obstacle for WSI as it requires careful liquid handling during the scanning process. Switching between dry objective and oil-immersion lens is often impossible as it disrupts the acquisition process. For a high-NA objective lens, the sub-micron depth of field also poses a challenge to acquiring in-focus images of samples with uneven topography. Additionally, it implies a small field of view for each tile, thus limiting the system throughput and resulting in a long acquisition time. Here we report a deep learning-enabled WSI platform, termed DeepWSI, to substantially improve the system performance and imaging throughput. With this platform, we show that images captured with a regular dry objective lens can be transformed into images comparable to that of a 1.4-NA oil immersion lens. Blurred images with defocus distance from -5 µm to +5 µm can be virtually refocused to the in-focus plane post measurement. We demonstrate an equivalent data throughput of >2 gigapixels per second, the highest among existing WSI systems. Using the same deep neural network, we also report a high-resolution virtual staining strategy and demonstrate it for Fourier ptychographic WSI. The DeepWSI platform may provide a turnkey solution for developing high-performance diagnostic tools for digital pathology.

High-throughput lensless whole slide imaging via continuous height-varying modulation of a tilted sensor.

We report a new, to the best of our knowledge, lensless microscopy configuration by integrating the concepts of transverse translational ptychography and defocus multi-height phase retrieval. In this approach, we place a tilted image sensor under the specimen for introducing linearly increasing phase modulation along one lateral direction. Similar to the operation of ptychography, we laterally translate the specimen and acquire the diffraction images for reconstruction. Since the axial distance between the specimen and the sensor varies at different lateral positions, laterally translating the specimen effectively introduces defocus multi-height measurements while eliminating axial scanning. Lateral translation further introduces sub-pixel shift for pixel super-resolution imaging and naturally expands the field of view for rapid whole slide imaging. We show that the equivalent height variation can be precisely estimated from the lateral shift of the specimen, thereby addressing the challenge of precise axial positioning in conventional multi-height phase retrieval. Using a sensor with 1.67 µm pixel size, our low-cost and field-portable prototype can resolve the 690 nm linewidth on the resolution target. We show that a whole slide image of a blood smear with a 120mm2 field of view can be acquired in 18 s. We also demonstrate accurate automatic white blood cell counting from the recovered image. The reported approach may provide a turnkey solution for addressing point-of-care and telemedicine-related challenges.

Virtual brightfield and fluorescence staining for Fourier ptychography via unsupervised deep learning.

Fourier ptychographic microscopy (FPM) is a computational approach geared towards creating high-resolution and large field-of-view images without mechanical scanning. Acquiring color images of histology slides often requires sequential acquisitions with red, green, and blue illuminations. The color reconstructions often suffer from coherent artifacts that are not presented in regular incoherent microscopy images. As a result, it remains a challenge to employ FPM for digital pathology applications, where resolution and color accuracy are of critical importance. Here we report a deep learning approach for performing unsupervised image-to-image translation of FPM reconstructions. A cycle-consistent adversarial network with multiscale structure similarity loss is trained to perform virtual brightfield and fluorescence staining of the recovered FPM images. In the training stage, we feed the network with two sets of unpaired images: (1) monochromatic FPM recovery and (2) color or fluorescence images captured using a regular microscope. In the inference stage, the network takes the FPM input and outputs a virtually stained image with reduced coherent artifacts and improved image quality. We test the approach on various samples with different staining protocols. High-quality color and fluorescence reconstructions validate its effectiveness.

Super-resolved multispectral lensless microscopy via angle-tilted, wavelength-multiplexed ptychographic modulation.

We report an angle-tilted, wavelength-multiplexed ptychographic modulation approach for multispectral lensless on-chip microscopy. In this approach, we illuminate the specimen with lights at five wavelengths simultaneously. A prism is added at the illumination path for spectral dispersion. Thus, lightwaves at different wavelengths hit the specimen at slightly different incident angles, breaking the ambiguities in mixed-state ptychographic reconstruction. At the detection path, we place a thin diffuser between the specimen and the monochromatic image sensor for encoding the spectral information into 2D intensity measurements. By scanning the sample to different x-y positions, we acquire a sequence of monochromatic images for reconstructing the five complex object profiles at the five wavelengths. An up-sampling procedure is integrated into the recovery process to bypass the resolution limit imposed by the imager pixel size. We demonstrate a half-pitch resolution of 0.55 µm using an image sensor with 1.85 µm pixel size. We also demonstrate quantitative and high-quality multispectral reconstructions of stained tissue sections for digital pathology applications.

A Cognitive Method for Automatically Retrieving Complex Information on a Large Scale.

Modern retrieval systems tend to deteriorate because of their large output of useless and even misleading information, especially for complex search requests on a large scale. Complex information retrieval (IR) tasks requiring multi-hop reasoning need to fuse multiple scattered text across two or more documents. However, there are two challenges for multi-hop retrieval. To be specific, the first challenge is that since some important supporting facts have little lexical or semantic relationship with the retrieval query, the retriever often omits them; the second challenge is that once a retriever chooses misinformation related to the query as the entities of cognitive graphs, the retriever will fail. In this study, in order to improve the performance of retrievers in complex tasks, an intelligent sensor technique was proposed based on a sub-scope with cognitive reasoning (2SCR-IR), a novel method of retrieving reasoning paths over the cognitive graph to provide users with verified multi-hop reasoning chains. Inspired by the users' process of step-by-step searching online, 2SCR-IR includes a dynamic fusion layer that starts from the entities mentioned in the given query, explores the cognitive graph dynamically built from the query and contexts, gradually finds relevant supporting entities mentioned in the given documents, and verifies the rationality of the retrieval facts. Our experimental results show that 2SCR-IR achieves competitive results on the HotpotQA full wiki and distractor settings, and outperforms the previous state-of-the-art methods by a more than two points absolute gain on the full wiki setting.

On-Chip Rolling Design for Controllable Strain Engineering and Enhanced Photon-Phonon Interaction in Graphene.

On-chip strain engineering is highly demanded in 2D materials as an effective route for tuning their extraordinary properties and integrating consistent functionalities toward various applications. Herein, rolling technique is proposed for strain engineering in monolayer graphene grown on a germanium substrate, where compressive or tensile strain could be acquired, depending on the designed layer stressors. Unusual compressive strains up to 0.30% are achieved in the rolled-up graphene tubular structures. The subsequent phonon hardening under compressive loading is observed through strain-induced Raman G band splitting, while distinct blueshifts of characteristic peaks (G+ , G- , or 2D) can be well regulated on an asymmetric tubular structure with a strain variation. In addition, due to the strong confinement of the local electromagnetic field under 3D tubular geometry, the photon-phonon interaction is highly strengthened, and thus, the Raman scattering of graphene in rolled-up tubes is enhanced. Such an on-chip rolling approach leads to a superior strain tuning method in 2D materials and could improve their light-matter interaction in a tubular configuration, which may hold great capability in 2D materials integration for on-chip applications such as in mechanics, electronics, and photonics.

Deep-ultraviolet Fourier ptychography (DUV-FP) for label-free biochemical imaging via feature-domain optimization.

We present deep-ultraviolet Fourier ptychography (DUV-FP) for high-resolution chemical imaging of biological specimens in their native state without exogenous stains. This approach uses a customized 265-nm DUV LED array for angle-varied illumination, leveraging the unique DUV absorption properties of biomolecules at this wavelength region. We implemented a robust feature-domain optimization framework to overcome common challenges in Fourier ptychographic reconstruction, including vignetting, pupil aberrations, stray light problems, intensity variations, and other systematic errors. By using a 0.12 numerical aperture low-resolution objective lens, our DUV-FP prototype can resolve the 345-nm linewidth on a resolution target, demonstrating at least a four-fold resolution gain compared to the captured raw images. Testing on various biospecimens demonstrates that DUV-FP significantly enhances absorption-based chemical contrast and reveals detailed structural and molecular information. To further address the limitations of conventional FP in quantitative phase imaging, we developed a spatially coded DUV-FP system. This platform enables true quantitative phase imaging of biospecimens with DUV light, overcoming the non-uniform phase response inherent in traditional microscopy techniques. The demonstrated advancements in high-resolution, label-free chemical imaging may accelerate developments in digital pathology, potentially enabling rapid, on-site analysis of biopsy samples in clinical settings.

GRASS: Learning Spatial-Temporal Properties From Chainlike Cascade Data for Microscopic Diffusion Prediction.

Information diffusion prediction captures diffusion dynamics of online messages in social networks. Thus, it is the basis of many essential tasks such as popularity prediction and viral marketing. However, there are two thorny problems caused by the loss of spatial-temporal properties of cascade data: "position-hopping" and "branch-independency." The former means no exact propagation relationship between any two consecutive infected users. The latter indicates that not all previously infected users contribute to the prediction of the next infected user. This article proposes the GRU-like Attention Unit and Structural Spreading (GRASS) model for microscopic cascade prediction to overcome the above two problems. First, we introduce the attention mechanism into the gated recurrent unit (GRU) component to expand the restricted receptive field of the recurrent neural network (RNN)-type module, thus addressing the "position-hopping" problem. Second, the structural spreading (SS) mechanism leverages structural features to filter out related users and controls the generation of cascade hidden states, thereby solving the "branch-independency" problem. Experiments on multiple real-world datasets show that our model significantly outperforms state-of-the-art baseline models on both hits@κ and map@κ metrics. Furthermore, the visualization of latent representations by t-distributed stochastic neighbor embedding (t-SNE) indicates that our model makes different cascades more discriminative during the encoding process.

Optical ptychography for biomedical imaging: recent progress and future directions [Invited].

Ptychography is an enabling microscopy technique for both fundamental and applied sciences. In the past decade, it has become an indispensable imaging tool in most X-ray synchrotrons and national laboratories worldwide. However, ptychography's limited resolution and throughput in the visible light regime have prevented its wide adoption in biomedical research. Recent developments in this technique have resolved these issues and offer turnkey solutions for high-throughput optical imaging with minimum hardware modifications. The demonstrated imaging throughput is now greater than that of a high-end whole slide scanner. In this review, we discuss the basic principle of ptychography and summarize the main milestones of its development. Different ptychographic implementations are categorized into four groups based on their lensless/lens-based configurations and coded-illumination/coded-detection operations. We also highlight the related biomedical applications, including digital pathology, drug screening, urinalysis, blood analysis, cytometric analysis, rare cell screening, cell culture monitoring, cell and tissue imaging in 2D and 3D, polarimetric analysis, among others. Ptychography for high-throughput optical imaging, currently in its early stages, will continue to improve in performance and expand in its applications. We conclude this review article by pointing out several directions for its future development.

Antithrombotic strategy in cancer patients comorbid with acute coronary syndrome and atrial fibrillation.

It has been shown that patients with cancer have a longer expected life duration, benefiting from advanced medical therapy. Meanwhile, the risk of suffering from cardiovascular disease (CVD) has been increasing with ageing. A growing number of studies have elucidated the association between cancer and CVD. Cancer, atrial fibrillation (AF) and coronary artery disease share some common factors and interact with each other, such as obesity, aging, diabetes, and inflammation, but the potential specific mechanism is still unclear. In addition, cancer-specific and therapy-related factors may increase the risk of embolism and bleeding in patients with cancer than in general population. However, current available embolic and bleeding risk scores applied in patients with CVD may not be applicable for risk assessment in cancer patients, which would be difficult for clinicians to select an appropriate antithrombotic regimen and ensure the balance between bleeding and embolism. Moreover, different types of cancer have distinct risks, which may increase the complexity of antithrombotic therapy. In this review, we review the literature related to cancer, AF, and acute coronary syndrome, focusing on the epidemiological status, physiological mechanism, embolism and bleeding risks, and strategies of antithrombotic therapy.

Depth-multiplexed ptychographic microscopy for high-throughput imaging of stacked bio-specimens on a chip.

Imaging a large number of bio-specimens at high speed is essential for many biomedical applications. The common strategy is to place specimens at different lateral positions and image them sequentially. Here we report a new on-chip imaging strategy, termed depth-multiplexed ptychographic microscopy (DPM), for parallel imaging and sensing at high speed. Different from the common strategy, DPM stacks multiple specimens in the axial direction and images the entire z-stack all at once. In our prototype platform, we modify a low-cost car mirror for programmable steering of the incident laser beam. A blood-coated image sensor is then placed underneath the stacked sample for acquiring the resulting diffraction patterns. With the captured images, we perform blind recovery of the incident beam angle and model different layers of the stacked sample as different coded surfaces for object reconstruction. For in vitro experiment, we demonstrate time-lapse cell culture monitoring by imaging 3 stacked microfluidic channels on the coded sensor. For high-throughput cytometric analysis, we image 5 stacked brain sections with a 205-mm2 field of view in ∼50 s. Cytometric analysis is also performed to quantify the cellular proliferation biomarkers on the slides. The DPM approach adds a new degree of freedom for data multiplexing in microscopy, enabling parallel imaging of multiple specimens using a single detector. The demonstrated 6-mm depth of field is among the longest ones in microscopy imaging. The novel depth-multiplexed configuration also complements the miniaturization provided by microfluidics devices, offering a solution for on-chip sensing and imaging with efficient sample handling.

Spatial- and Fourier-domain ptychography for high-throughput bio-imaging.

First envisioned for determining crystalline structures, ptychography has become a useful imaging tool for microscopists. However, ptychography remains underused by biomedical researchers due to its limited resolution and throughput in the visible light regime. Recent developments of spatial- and Fourier-domain ptychography have successfully addressed these issues and now offer the potential for high-resolution, high-throughput optical imaging with minimal hardware modifications to existing microscopy setups, often providing an excellent trade-off between resolution and field of view inherent to conventional imaging systems, giving biomedical researchers the best of both worlds. Here, we provide extensive information to enable the implementation of ptychography by biomedical researchers in the visible light regime. We first discuss the intrinsic connections between spatial-domain coded ptychography and Fourier ptychography. A step-by-step guide then provides the user instructions for developing both systems with practical examples. In the spatial-domain implementation, we explain how a large-scale, high-performance blood-cell lens can be made at negligible expense. In the Fourier-domain implementation, we explain how adding a low-cost light source to a regular microscope can improve the resolution beyond the limit of the objective lens. The turnkey operation of these setups is suitable for use by professional research laboratories, as well as citizen scientists. Users with basic experience in optics and programming can build the setups within a week. The do-it-yourself nature of the setups also allows these procedures to be implemented in laboratory courses related to Fourier optics, biomedical instrumentation, digital image processing, robotics and capstone projects.