Optimization of lipid nanoparticles for gene editing of the liver via intraduodenal delivery.

Lipid nanoparticles (LNPs) have recently emerged as successful gene delivery platforms for a diverse array of disease treatments. Efforts to optimize their design for common administration methods such as intravenous injection, intramuscular injection, or inhalation, revolve primarily around the addition of targeting ligands or the choice of ionizable lipid. Here, we employed a multi-step screening method to optimize the type of helper lipid and component ratios in a plasmid DNA (pDNA) LNP library to efficiently deliver pDNA through intraduodenal delivery as an indicative route for oral administration. By addressing different physiological barriers in a stepwise manner, we down-selected effective LNP candidates from a library of over 1000 formulations. Beyond reporter protein expression, we assessed the efficiency in non-viral gene editing in mouse liver mediated by LNPs to knockdown PCSK9 and ANGPTL3 expression, thereby lowering low-density lipoprotein (LDL) cholesterol levels. Utilizing an all-in-one pDNA construct with Strep. pyogenes Cas9 and gRNAs, our results showcased that intraduodenal administration of selected LNPs facilitated targeted gene knockdown in the liver, resulting in a 27% reduction in the serum LDL cholesterol level. This LNP-based all-in-one pDNA-mediated gene editing strategy highlights its potential as an oral therapeutic approach for hypercholesterolemia, opening up new possibilities for DNA-based gene medicine applications.

A low-cost machine learning framework for predicting drug-drug interactions based on fusion of multiple features and a parameter self-tuning strategy.

Poly-drug therapy is now recognized as a crucial treatment, and the analysis of drug-drug interactions (DDIs) offers substantial theoretical support and guidance for its implementation. Predicting potential DDIs using intelligent algorithms is an emerging approach in pharmacological research. However, the existing supervised models and deep learning-based techniques still have several limitations. This paper proposes a novel DDI analysis and prediction framework called the Multi-View Semi-supervised Graph-based (MVSG) framework, which provides a comprehensive judgment by integrating multiple DDI features and functions without any time-consuming training process. Unlike conventional approaches, MVSG can search for the most suitable similarity (or distance) measurement among DDI data and construct graph structures for each feature. By employing a parameter self-tuning strategy, MVSG fuses multiple graphs according to the contributions of features' information. The actual anticancer drug data are extracted from the authoritative public database for evaluating the effectiveness of our framework, including 904 drugs, 7730 DDI records and 19 types of drug interactions. Validation results indicate that the prediction is more accurate when multiple features are adopted by our framework. In comparison to conventional machine learning techniques, MVSG can achieve higher performance even with less labeled data and without a training process. Finally, MVSG is employed to narrow down the search for potential valuable combinations.

A novel approach for diabetic foot diagnosis: Deep learning-based detection of lower extremity arterial stenosis.

PURPOSE OF THE STUDY: Assessing the lower extremity arterial stenosis scores (LEASS) in patients with diabetic foot ulcer (DFU) is a challenging task that requires considerable time and efforts from physicians, and it may yield varying results. The presence of vascular wall calcification and other irrelevant tissue information surrounding the vessel can further compound the difficulties of this evaluation. Automatic detection of lower extremity arterial stenosis (LEAS) is expected to help doctors develop treatment plans for patients faster. METHODS: In this paper, we first reconstructed the 3D model of blood vessels by medical digital image processing and then utilized it as the training data for deep learning (DL) in conjunction with the non-calcified part of blood vessels in the original data. We proposed an improved model of vascular stenosis small target detection based on YOLOv5. We added Convolutional Block Attention Module (CBAM) in backbone, replaced Path Aggregation Network (PANET) with Bidirectional Feature Pyramid Network (BiFPN) and replaced C3 with GhostC3 in neck to improve the recognition of three types of stenosis targets (I: <50 %, II: 51 % - 99 %, III: completely occluded). Additionally, we utilized K-Means++ instead of K-Means for better algorithm convergence performance, and enhanced the Complete-IoU (CIoU) loss function to Alpha-Scylla-IoU (ASIoU) loss for faster reasoning and convergence. Lastly, we conducted comparisons between our approach and five other prominent models. RESULT: Our method had the best average ability to detect three types of stenosis with 85.40% mean Average Precision (mAP) and 74.60 Frames Per Second (FPS) and explored the possibility of applying DL to the detection of LEAS in diabetic foot. The code is available at github.com/wuchongxin/yolov5_LEAS.git.

Piezoresistivity modeling of soft tissue electrical-mechanical properties: A validation study.

In general, the electrical property of soft tissues is sensitive to the force applied to their surface. To further study the relationship between the force and the electrical property of soft tissues, this paper attempts to investigate the effect of static and higher-order stresses on electrical properties. Overall, a practical experimental platform is designed to acquire the force information and the electrical property of soft tissues during a contact procedure, which is featured different compression stimuli, such as constant pressing force, constant pressing speed, and step-force compression, etc. Furthermore, the piezoresistive characteristic is innovatively introduced to model the mechanical-electrical properties of soft tissue. Finite Element Modeling (FEM) is adopted to fit the static piezoresistivity of the soft tissue. Finally, experimental studies were performed to demonstrate the effect of stress on the electrical properties and the feasibility of the proposed piezoresistive model to describe soft tissues' mechanical and electrical properties.

Effects of low-dose furosemide combined with aminophylline on the renal function in septic shock patients.

BACKGROUND: To investigate the effects of low-dose furosemide and aminophylline on the renal function in patients with septic shock. METHODS AND RESULTS: A total of 109 eligible septic shock patients in the intensive care unit were randomly divided into a control group (n = 55) and an intervention group (n = 54). The control group received normal saline, and the intervention group received low-dose furosemide (0.048 mg/kg.h-1) with aminophylline (0.3 mg/kg.h-1). The primary outcomes included the levels of serum creatinine (Scr), creatinine clearance rate (Ccr), blood urea nitrogen (BUN), glomerular filtration rate (GFR), and urine output on admission and on days 3, 7 and 14. The secondary outcomes were the sequential organ failure assessment (SOFA) scores, continuous renal replacement therapy (CRRT) time and intensive care unit (ICU) mortality, hospital mortality and 28-day mortality. There were no significant differences in the levels of Scr, Ccr, BUN, or GFR between the two groups, while the urine output was higher in the intervention group on days 3, 7, and 14. Compared with the control group, the SOFA scores, ICU mortality, hospital mortality and 28-day mortality were significantly lower in the intervention group on days 3, 7, and 14, the CRRT time was shorter, and the cumulative fluid balance was lower on days 3 and 7 in the intervention group. CONCLUSIONS: Although low-dose furosemide and aminophylline have fewer protective effects on the renal function in septic shock patients, they could reduce the CRRT time and improve the prognosis.

TREM-1 induces pyroptosis in cardiomyocytes by activating NLRP3 inflammasome through the SMC4/NEMO pathway.

Sepsis often causes cell death via pyroptosis and hence results in septic cardiomyopathy. Triggering receptors expressed in myeloid cells-1 (TREM-1) may initiate cellular cascade pathways and, in turn, induce cell death and vital organ dysfunction in sepsis, but the evidence is limited. We set to investigate the role of TREM-1 on nucleotide-binding oligomerization domain-like receptors with pyrin domain-3 (NLRP3) inflammasome activation and cardiomyocyte pyroptosis in sepsis models using cardiac cell line (HL-1) and mice. In this study, TREM-1 was found to be significantly increased in HL-1 cells challenged with lipopolysaccharide (LPS). Pyroptosis was also significantly increased in the HL-1 cells challenged with lipopolysaccharide and an NLRP3 inflammasome activator, nigericin. The close interaction between TREM-1 and structural maintenance of chromosome 4 (SMC4) was also identified. Furthermore, inhibition of TREM-1 or SMC4 prevented the upregulation of NLRP3 and decreased Gasdermin-D, IL-1ß and caspase-1 cleavage. In mice subjected to caecal ligation and puncture, the TREM-1 inhibitor LR12 decreased the expression of NLRP3 and attenuated cardiomyocyte pyroptosis, leading to improved cardiac function and prolonged survival of septic mice. Our work demonstrates that, under septic conditions, TREM-1 plays a critical role in cardiomyocyte pyroptosis. Targeting TREM-1 and its associated molecules may therefore lead to novel therapeutic treatments for septic cardiomyopathy.

A Novel and Fast Encryption System Based on Improved Josephus Scrambling and Chaotic Mapping.

To address the shortcomings of weak confusion and high time complexity of the existing permutation algorithms, including the traditional Josephus ring permutation (TJRP), an improved Josephus ring-based permutation (IJRBP) algorithm is developed. The proposed IJRBP replaces the remove operation used in TJRP with the position exchange operation and employs random permutation steps instead of fixed steps, which can offer a better scrambling effect and a higher permutation efficiency, compared with various scrambling methods. Then, a new encryption algorithm based on the IJRBP and chaotic system is developed. In our scheme, the plaintext feature parameter, which is related to the plaintext and a random sequence generated by a chaotic system, is used as the shift step of the circular shift operation to generate the diffusion matrix, which means that a minor change in the source image will generate a totally different encrypted image. Such a strategy strikes a balance between plaintext sensitivity and ciphertext sensitivity to obtain the ability to resist chosen-plaintext attacks (CPAs) and the high robustness of resisting noise attacks and data loss. Simulation results demonstrate that the proposed image cryptosystem has the advantages of great encryption efficiency and the ability to resist various common attacks.

Smart handheld device with flexible wrist and electrical bioimpedance sensor for tissue inspection.

With the evolving demands of surgical intervention, there is a strong need for smaller and functionally augmented instruments to improve surgical outcomes, operational convenience, and diagnostic safety. Owing to the narrow and complicated anatomy, the probe head of the medical instrument is required to possess both good maneuverability and compact size. In addition, the development of medical instrument is moving toward patient-specialized, of which the articulation positions can be customized to reach the target position. To fulfill these requirements, this study presents the design of a smart handheld device which equips with a low cost, easy control, disposable flexible wrist, and an electrical bioimpedance sensor for medical diagnosis. Prototype of the device is made and tested. The experimental results demonstrate that the proposed device can provide accurate manipulation and effective tissue detection, showing a great potential in various medical applications.

Design and ARM-Based Implementation of Bitstream-Oriented Chaotic Encryption Scheme for H.264/AVC Video.

In actual application scenarios of the real-time video confidential communication, encrypted videos must meet three performance indicators: security, real-time, and format compatibility. To satisfy these requirements, an improved bitstream-oriented encryption (BOE) method based chaotic encryption for H.264/AVC video is proposed. Meanwhile, an ARM-embedded remote real-time video confidential communication system is built for experimental verification in this paper. Firstly, a 4-D self-synchronous chaotic stream cipher algorithm with cosine anti-controllers (4-D SCSCA-CAC) is designed to enhance the security. The algorithm solves the security loopholes of existing self-synchronous chaotic stream cipher algorithms applied to the actual video confidential communication, which can effectively resist the combinational effect of the chosen-ciphertext attack and the divide-and-conquer attack. Secondly, syntax elements of the H.264 bitstream are analyzed in real-time. Motion vector difference (MVD) coefficients and direct-current (DC) components in Residual syntax element are extracted through the Exponential-Golomb decoding operation and entropy decoding operation based on the context-based adaptive variable length coding (CAVLC) mode, respectively. Thirdly, the DC components and MVD coefficients are encrypted by the 4-D SCSCA-CAC, and the encrypted syntax elements are re-encoded to replace the syntax elements of the original H.264 bitstream, keeping the format compatibility. Besides, hardware codecs and multi-core multi-threading technology are employed to improve the real-time performance of the hardware system. Finally, experimental results show that the proposed scheme, with the advantage of high efficiency and flexibility, can fulfill the requirement of security, real-time, and format compatibility simultaneously.

Drug delivery carriers with therapeutic functions.

Design of micro- or nanocarriers for drug delivery has primarily been focused on properties such as hydrophobicity, biodegradability, size, shape, surface charge, and toxicity, so that they can achieve optimal delivery with respect to drug loading, release kinetics, biodistribution, cellular uptake, and biocompatibility. Incorporation of stimulus-sensitive moieties into the carriers would lead to "smart" delivery systems. A further evolution would be to endow the carrier with a therapeutic function such that it no longer serves as a mere passive entity to release the drug at the target tissue but can be viewed as a therapeutic agent in itself. In this review, we will discuss recent and ongoing efforts over the past decade to design therapeutic drug carriers that confer a biological benefit, including ROS scavenging or generating, pro- or anti-inflammatory, and immuno-evasive properties, to enhance the overall therapeutic efficacy of the delivery systems.

Acute fatty liver of pregnancy causes severe acute pancreatitis and stillborn fetus: A case report.

RATIONALE: Acutefatty liver of pregnancy (AFLP) is a potentially fatal obstetric emergency characterized by acute hepatic failure secondary to fatty infiltration. The resultant effects include coagulopathy, electrolyte abnormalities, and multisystem organ dysfunction. Pancreatitis typically develops after the onset of renal and hepatic dysfunction. Pancreatitis has been suggested as a poor prognostic indicator because it is associated with more adverse outcomes. PATIENT CONCERNS: A 29-year-old Chinese woman at 34.7 weeks pregnancy was admitted to hospital due to paroxysmal hypogastric pain and massive colporrhagia for 1 day. DIAGNOSIS: Laboratory tests revealed hepatic and renal impairment, coagulopathy. Thoracoabdominal computed tomography (CT) scanning showed pleural and peritoneal effusion, fatty liver, and pancreatitis. She was diagnosed with AFLP, severe acute pancreatitis (SAP), multiple organ dysfunction syndrome (MODS), and intrauterine fetal death. INTERVENTIONS: The patient was treated with blood component transfusions, plasma exchange combined with renal replacement therapy, antibiotic de-escalation, gastric and pancreatic secretion inhibitor, and enteral nutrition. OUTCOMES: After successful management, the patient was discharged without any complications on day 35 of admission. At 10 months follow-up, thoracoabdominal enhanced CT revealed was normal and laboratory tests revealed normal liver and kidney function. LESSONS: Once AFLP is highly suspected or confirmed, the pregnancy should be terminated in time and active symptomatic management should be given.

Circulating Neutrophil-Derived Microparticles Associated with the Prognosis of Patients with Sepsis.

INTRODUCTION: Because of its high morbidity and mortality, sepsis remains the leading cause of death in the ICU. Microparticles (MP) have been largely studied as potential diagnostic or prognostic markers in various diseases including sepsis. OBJECTIVE: The biological and clinical relevance of neutrophil-derived microparticles (NDMPs) within the MP population remains unclear. The objective of this study was to elucidate the relationship between plasma NDMPs and the prognosis of patients with sepsis and/or septic shock. METHODS: The study was designed as an observational, noninterventional clinical study. The cohort for this study included 40 sepsis and 40 septic shock patients together with 10 healthy controls admitted to the Intensive Care Unit (ICU) and the Health Surveillance Center in the Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China, from January to November 2018, respectively. The degree of critical disease for sepsis and septic shock was evaluated, with data analyses conducted from 2018 to 2019. RESULTS: On days 1, 3 and 5 post-admission a series of data including plasma NDMP levels, patient demographics, TNF-α levels, IL-6 levels, sTREM-1 levels, and the sepsis severity score measurements were collected. A survival curve was plotted against levels of plasma NDMPs. Levels of NDMPs were observed to be higher in the septic shock patients than in the sepsis patients on days 1, 3, and 5 post-ICU admission (p < 0.05). NDMP levels were significantly increased in sepsis and septic shock patients with a parallel increase in pro-inflammatory mediators and sepsis severity score (p < 0.05) as well as mortality. CONCLUSION: Our data suggest that NDMPs may be a biomarker of sepsis severity and mortality although its implications on sepsis prognosis warrant further study.

Combined fluorescence-guided surgery and photodynamic therapy for glioblastoma multiforme using cyanine and chlorin nanocluster.

INTRODUCTION: Glioblastoma multiforme (GBM) is the most common primary intracranial malignancy; survival can be improved by maximizing the extent-of-resection. METHODS: A near-infrared fluorophore (Indocyanine-Green, ICG) was combined with a photosensitizer (Chlorin-e6, Ce6) on the surface of superparamagnetic-iron-oxide-nanoparticles (SPIONs), all FDA-approved for clinical use, yielding a nanocluster (ICS) using a microemulsion. The physical-chemical properties of the ICS were systematically evaluated. Efficacy of photodynamic therapy (PDT) was evaluated in vitro with GL261 cells and in vivo in a subtotal resection trial using a syngeneic flank tumor model. NIR imaging properties of ICS were evaluated in both a flank and an intracranial GBM model. RESULTS: ICS demonstrated high ICG and Ce6 encapsulation efficiency, high payload capacity, and chemical stability in physiologic conditions. In vitro cell studies demonstrated significant PDT-induced cytotoxicity using ICS. Preclinical animal studies demonstrated that the nanoclusters can be detected through NIR imaging in both flank and intracranial GBM tumors (ex: 745 nm, em: 800 nm; mean signal-to-background 8.5 ± 0.6). In the flank residual tumor PDT trial, subjects treated with PDT demonstrated significantly enhanced local control of recurrent neoplasm starting on postoperative day 8 (23.1 mm3 vs 150.5 mm3, p = 0.045), and the treatment effect amplified to final mean volumes of 220.4 mm3 vs 806.1 mm3 on day 23 (p = 0.0055). CONCLUSION: A multimodal theragnostic agent comprised solely of FDA-approved components was developed to couple optical imaging and PDT. The findings demonstrated evidence for the potential theragnostic benefit of ICS in surgical oncology that is conducive to clinical integration.

Broad-Spectrum Activity of Volatile Organic Compounds from Three Yeast-like Fungi of the Galactomyces Genus Against Diverse Plant Pathogens.

The application of antagonistic fungi for plant protection has attracted considerable interest because they may potentially replace the use of chemical pesticides. Antipathogenic activities confirmed in volatile organic compounds (VOCs) from microorganisms have potential to serve as biocontrol agents against pre- and post-harvest diseases. In the present study, we investigated Galactomyces fungi isolated from rotten leaves and the rhizosphere of cherry tomato (Lycopersicon esculentum var. cerasiforme). VOCs produced by Galactomyces fungi negatively affected the growth of phytopathogenic fungi and the survival of nematodes. Mycelial growths of all nine examined phytopathogenic fungi were inhibited on agar plate, although the inhibition was more intense in Athelia rolfsii JYC2163 and Cladosporium cladosporioides JYC2144 and relatively moderate in Fusarium sp. JYC2145. VOCs also efficiently suppressed the spore germination and mycelial growth of A. rolfsii JYC2163 on tomatoes. The soil nematode Caenorhabditis elegans exhibited higher mortality in 24 h in the presence of VOCs. These results suggest the broad-spectrum activity of Galactomyces fungi against various plant pathogens and the potential to use VOCs from Galactomyces as biocontrol agents.

Design of a Drop-in EBI Sensor Probe for Abnormal Tissue Detection in Minimally Invasive Surgery.

It is a common challenge for the surgeon to detect pathological tissues and determine the resection margin during a minimally invasive surgery. In this study, we present a drop-in sensor probe based on the electrical bioimpedance spectroscopic technology, which can be grasped by a laparoscopic forceps and controlled by the surgeon to inspect suspicious tissue area conveniently. The probe is designed with an optimized electrode and a suitable shape specifically for Minimally Invasive Surgery (MIS). Subsequently, a series of ex vivo experiments are carried out with porcine liver tissue for feasibility validation. During the experiments, impedance measured at frequencies from 1 kHz to 2 MHz are collected on both normal tissues and water soaked tissue. In addition, classifiers based on discriminant analysis are developed. The result of the experiment indicate that the sensor probe can be used to measure the impedance of the tissue easily and the developed tissue classifier achieved accuracy of 80% and 100% respectively.

Clonal Vγ6+Vδ4+ T cells promote IL-17-mediated immunity against Staphylococcus aureus skin infection.

T cell cytokines contribute to immunity against Staphylococcus aureus, but the predominant T cell subsets involved are unclear. In an S. aureus skin infection mouse model, we found that the IL-17 response was mediated by γδ T cells, which trafficked from lymph nodes to the infected skin to induce neutrophil recruitment, proinflammatory cytokines IL-1α, IL-1ß, and TNF, and host defense peptides. RNA-seq for TRG and TRD sequences in lymph nodes and skin revealed a single clonotypic expansion of the encoded complementarity-determining region 3 amino acid sequence, which could be generated by canonical nucleotide sequences of TRGV5 or TRGV6 and TRDV4 However, only TRGV6 and TRDV4 but not TRGV5 sequences expanded. Finally, Vγ6+ T cells were a predominant γδ T cell subset that produced IL-17A as well as IL-22, TNF, and IFNγ, indicating a broad and substantial role for clonal Vγ6+Vδ4+ T cells in immunity against S. aureus skin infections.

Directing GDNF-mediated neuronal signaling with proactively programmable cell-surface saccharide-free glycosaminoglycan mimetics.

A significant barrier to harnessing the power of cell-surface glycosaminoglycans (GAGs) to modulate glial cell-line-derived neurotrophic factor (GDNF) signaling is the difficulty in accessing key GAG structures involved. Here, we report tailored GDNF signaling using synthetic polyproline-based GAG mimetics (PGMs). PGMs deliver the much needed proactive programmability for GDNF recognition and effectively modulate GDNF-mediated neuronal processes in a cellular context.

Injury, dysbiosis, and filaggrin deficiency drive skin inflammation through keratinocyte IL-1α release.

BACKGROUND: Atopic dermatitis (AD) is associated with epidermal barrier defects, dysbiosis, and skin injury caused by scratching. In particular, the barrier-defective epidermis in patients with AD with loss-of-function filaggrin mutations has increased IL-1α and IL-1ß levels, but the mechanisms by which IL-1α, IL-1ß, or both are induced and whether they contribute to the aberrant skin inflammation in patients with AD is unknown. OBJECTIVE: We sought to determine the mechanisms through which skin injury, dysbiosis, and increased epidermal IL-1α and IL-1ß levels contribute to development of skin inflammation in a mouse model of injury-induced skin inflammation in filaggrin-deficient mice without the matted mutation (ft/ft mice). METHODS: Skin injury of wild-type, ft/ft, and myeloid differentiation primary response gene-88-deficient ft/ft mice was performed, and ensuing skin inflammation was evaluated by using digital photography, histologic analysis, and flow cytometry. IL-1α and IL-1ß protein expression was measured by means of ELISA and visualized by using immunofluorescence and immunoelectron microscopy. Composition of the skin microbiome was determined by using 16S rDNA sequencing. RESULTS: Skin injury of ft/ft mice induced chronic skin inflammation involving dysbiosis-driven intracellular IL-1α release from keratinocytes. IL-1α was necessary and sufficient for skin inflammation in vivo and secreted from keratinocytes by various stimuli in vitro. Topical antibiotics or cohousing of ft/ft mice with unaffected wild-type mice to alter or intermix skin microbiota, respectively, resolved the skin inflammation and restored keratinocyte intracellular IL-1α localization. CONCLUSIONS: Taken together, skin injury, dysbiosis, and filaggrin deficiency triggered keratinocyte intracellular IL-1α release that was sufficient to drive chronic skin inflammation, which has implications for AD pathogenesis and potential therapeutic targets.

A new development of non-local image denoising using fixed-point iteration for non-convex ℓp sparse optimization.

We proposed a new efficient image denoising scheme, which mainly leads to four important contributions whose approaches are different from existing ones. The first is to show the equivalence between the group-based sparse representation and the Schatten-p norm minimization problem, so that the sparsity of the coefficients for each group can be measured by estimating the underlying singular values. The second is that we construct the proximal operator for sparse optimization in ℓp space with p ∈ (0, 1] by using fixed-point iteration and obtained a new solution of Schatten-p norm minimization problem, which is more rigorous and accurate than current available results. The third is that we analyze the suitable setting of power p for each noise level σ = 20, 30, 50, 60, 75, 100, respectively. We find that the optimal value of p is inversely proportional to the noise level except for high level of noise, where the best values of p are 1 and 0.95, when the noise levels are respectively 75 and 100. Last we measure the structural similarity between two image patches and extends previous deterministic annealing-based solution to sparsity optimization problem through incorporating the idea of dictionary learning. Experimental results demonstrate that for every given noise level, the proposed Spatially Adaptive Fixed Point Iteration (SAFPI) algorithm attains the best denoising performance on the value of Peak Signal-to-Noise Ratio (PSNR) and structure similarity (SSIM), being able to retain the image structure information, which outperforms many state-of-the-art denoising methods such as Block-matching and 3D filtering (BM3D), Weighted Nuclear Norm Minimization (WNNM) and Weighted Schatten p-Norm Minimization (WSNM).

Facile saccharide-free mimetics that recapitulate key features of glycosaminoglycan sulfation patterns.

Controlling glycosaminoglycan (GAG) activity to exploit its immense potential in biology ultimately requires facile manipulation of sulfation patterns associated with GAGs. However, satisfying this requirement in full remains challenging, given that synthesis of GAGs is technically arduous while convenient GAG mimetics often produce sulfation patterns that are uncharacteristic of GAGs. To overcome this, we develop saccharide-free polyproline-based GAG mimetics (PGMs) that can be facilely assembled via amide coupling chemistry. Molecular dynamics simulations show that PGMs recapitulate key GAG structural features (i.e. ∼9 Å-sized repeating units, periodicity and helicity) and as with GAGs, can be tuned to introduce systematic variations in sulfate clustering and spacing. Functionally, a variety of PGMs control various GAG activities (concerning P-selectin, neurotrophic factors and heparinase) and exhibit GAG-like characteristics such as progressive modulation, comparable effectiveness with heparins, need for different sequences to suit different activities and the presence of a "minimal bioactive length". Furthermore, PGMs produce consistent effects in vivo and successfully provide therapeutic benefits over cancer metastasis. Taken together with their high level of biosafety, PGMs answer the long-standing need for an effective and practicable strategy to manipulate GAG-appropriate sulfation patterns and exploit GAG activity in medicine and biotechnology.