Molecular mechanisms of diabetic nephropathy: A narrative review.

Diabetic nephropathy (DN) is the predominant secondary nephropathy resulting in global end-stage renal disease. It is attracting significant attention in both domestic and international research due to its widespread occurrence, fast advancement, and limited choices for prevention and treatment. The pathophysiology of this condition is intricate and involves multiple molecular and cellular pathways at various levels. This article provides a concise overview of the molecular processes involved in the development of DN. It discusses various factors, such as signaling pathways, cytokines, inflammatory responses, oxidative stress, cellular damage, autophagy, and epigenetics. The aim is to offer clinicians a valuable reference for DN's diagnosis, treatment, and intervention.

OFIDA: Object-focused image data augmentation with attention-driven graph convolutional networks.

Image data augmentation plays a crucial role in data augmentation (DA) by increasing the quantity and diversity of labeled training data. However, existing methods have limitations. Notably, techniques like image manipulation, erasing, and mixing can distort images, compromising data quality. Accurate representation of objects without confusion is a challenge in methods like auto augment and feature augmentation. Preserving fine details and spatial relationships also proves difficult in certain techniques, as seen in deep generative models. To address these limitations, we propose OFIDA, an object-focused image data augmentation algorithm. OFIDA implements one-to-many enhancements that not only preserve essential target regions but also elevate the authenticity of simulating real-world settings and data distributions. Specifically, OFIDA utilizes a graph-based structure and object detection to streamline augmentation. Specifically, by leveraging graph properties like connectivity and hierarchy, it captures object essence and context for improved comprehension in real-world scenarios. Then, we introduce DynamicFocusNet, a novel object detection algorithm built on the graph framework. DynamicFocusNet merges dynamic graph convolutions and attention mechanisms to flexibly adjust receptive fields. Finally, the detected target images are extracted to facilitate one-to-many data augmentation. Experimental results validate the superiority of our OFIDA method over state-of-the-art methods across six benchmark datasets.

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer.

PURPOSE: This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis. METHODS: SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses. RESULTS: Our analysis revealed that 48 DEPCDGs are significantly correlated with apoptotic signaling and oxidative stress pathways and identified seven key DEPCDGs (CASP3, GADD45B, GNA15, GZMB, IL1B, ISG20, and RHOB) through survival analysis. Furthermore, eight distinct cell subtypes were characterized using scRNA-seq. It was found that G protein subunit alpha 15 (GNA15) exhibited low expression across these subtypes and a strong association with immune cells. Based on the DEGs identified by the GNA15 high- and low-expression groups, a prognostic model comprising eight genes with significant prognostic value was constructed, effectively predicting patient overall survival. Additionally, a nomogram incorporating the RS signature, age, grade, and stage was developed and validated using two large SOC datasets. CONCLUSION: GNA15 emerged as an independent and excellent prognostic marker for SOC patients. This study provides valuable insights into the prognostic potential of DEPCDGs in SOC, presenting new avenues for personalized treatment strategies.

Three-Direction Fusion for Accurate Volumetric Liver and Tumor Segmentation.

Biomedical image segmentation of organs, tissues and lesions has gained increasing attention in clinical treatment planning and navigation, which involves the exploration of two-dimensional (2D) and three-dimensional (3D) contexts in the biomedical image. Compared to 2D methods, 3D methods pay more attention to inter-slice correlations, which offer additional spatial information for image segmentation. An organ or tumor has a 3D structure that can be observed from three directions. Previous studies focus only on the vertical axis, limiting the understanding of the relationship between a tumor and its surrounding tissues. Important information can also be obtained from sagittal and coronal axes. Therefore, spatial information of organs and tumors can be obtained from three directions, i.e. the sagittal, coronal and vertical axes, to understand better the invasion depth of tumor and its relationship with the surrounding tissues. Moreover, the edges of organs and tumors in biomedical image may be blurred. To address these problems, we propose a three-direction fusion volumetric segmentation (TFVS) model for segmenting 3D biomedical images from three perspectives in sagittal, coronal and transverse planes, respectively. We use the dataset of the liver task provided by the Medical Segmentation Decathlon challenge to train our model. The TFVS method demonstrates a competitive performance on the 3D-IRCADB dataset. In addition, the t-test and Wilcoxon signed-rank test are also performed to show the statistical significance of the improvement by the proposed method as compared with the baseline methods. The proposed method is expected to be beneficial in guiding and facilitating clinical diagnosis and treatment.

Exploration of Postharvest Conditions for Codonopsis pilosula Nannf. var. modesta (Nannf.) L. T. Shen Roots Based on Sensory Quality, Active Components, Antioxidant Capacity and Physiological Changes at Different Storage Temperatures.

The promotion of industrial-mode production of Codonopsis pilosula Nannf. var. modesta (Nannf.) L. T. Shen (C. pilosula) has expanded the demand for the postharvest storage of fresh roots. Further research is needed to establish comprehensive methods to evaluate the impact of storage conditions. This study simulated the storage process of roots at near-freezing temperature [NFT (-1 °C)] and traditional low temperatures (-6 °C, 4 °C and 9 °C) for 40 days. At different storage stages, correlation analysis was conducted using quantitative data on 20 parameters, including sensory quality, active components, antioxidant capacity and physiological changes. Appearance and principal component analysis could distinguish between fresh and stored samples, while NFT samples on the 40th day of storage were similar to fresh ones. Correlation analysis indicated that NFT storage could maintain the sensory quality by increasing the antioxidant enzyme activity and active components, reducing the accumulation of reactive oxygen species and malondialdehyde and reducing the activity of browning-related enzymes and cell-wall-degrading enzymes. These findings highlight the importance of the overall quality evaluation of fresh roots and emphasize the potential to improve fresh root and dried medicinal material quality by regulating storage conditions such as temperature.

Study on environmental factors affecting the quality of codonopsis radix based on MaxEnt model and all-in-one functional factor.

Owing to the increasing market demand of Codonopsis Radix, the cropper blindly cultivates to expand planting area for economic benefits, which seriously affects the quality of Codonopsis Radix. Therefore, this study synthesized 207 batches of Codonopsis Radix and 115 ecological factors, and analyzed the suitable planting areas of Codonopsis pilosula under current and future climate change based on Geographic Information System (GIS) and MaxEnt model. Secondly, we evaluated the quality of Codonopsis Radix based on the all-in-one functional factor including chromatographic fingerprint, the index components, the effective compounds groups, the nutritional components, and the nutritional elements, and the quality regionalization of Codonopsis Radix was analyzed. Finally, the ecological factors affecting the accumulation of effective components of Codonopsis Radix were analyzed. This study found for the first time that the highly suitable area of Codonopsis pilosula was mainly distributed in the Weihe River system and the Bailongjiang River system in Gansu Province. There were differences in the quality of Codonopsis Radix from different ecologically suitable areas based on the all-in-one functional factors, and the comprehensive high-quality area of Codonopsis Radix was mainly distributed in Longnan and Longxi district of Gansu Province. The precipitation, temperature and altitude play a key role in the accumulation of chemical components in the 10 ecological factors affecting the distribution of Codonopsis pilosula. Under future climatic conditions, the highly suitable area of Codonopsis pilosula is decreased.

A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer.

We developed and validated a multimodal radiomic machine learning approach to noninvasively predict the expression of lymphocyte cell-specific protein-tyrosine kinase (LCK) expression and clinical prognosis of patients with high-grade serous ovarian cancer (HGSOC). We analyzed gene enrichment using 343 HGSOC cases extracted from The Cancer Genome Atlas. The corresponding biomedical computed tomography images accessed from The Cancer Imaging Archive were used to construct the radiomic signature (Radscore). A radiomic nomogram was built by combining the Radscore and clinical and genetic information based on multimodal analysis. We compared the model performances and clinical practicability via area under the curve (AUC), Kaplan-Meier survival, and decision curve analyses. LCK mRNA expression was associated with the prognosis of HGSOC patients, serving as a significant prognostic marker of the immune response and immune cells infiltration. Six radiomic characteristics were chosen to predict the expression of LCK and overall survival (OS) in HGSOC patients. The logistic regression (LR) radiomic model exhibited slightly better predictive abilities than the support vector machine model, as assessed by comparing combined results. The performance of the LR radiomic model for predicting the level of LCK expression with five-fold cross-validation achieved AUCs of 0.879 and 0.834, respectively, in the training and validation sets. Decision curve analysis at 60 months demonstrated the high clinical utility of our model within thresholds of 0.25 and 0.7. The radiomic nomograms were robust and displayed effective calibration. Abnormally high expression of LCK in HGSOC patients is significantly correlated with the tumor immune microenvironment and can be used as an essential indicator for predicting the prognosis of HGSOC. The multimodal radiomic machine learning approach can capture the heterogeneity of HGSOC, noninvasively predict the expression of LCK, and replace LCK for predictive analysis, providing a new idea for predicting the clinical prognosis of HGSOC and formulating a personalized treatment plan.

An Efficient Differential Privacy-Based Method for Location Privacy Protection in Location-Based Services.

Location-based services (LBS) are widely used due to the rapid development of mobile devices and location technology. Users usually provide precise location information to LBS to access the corresponding services. However, this convenience comes with the risk of location privacy disclosure, which can infringe upon personal privacy and security. In this paper, a location privacy protection method based on differential privacy is proposed, which efficiently protects users' locations, without degrading the performance of LBS. First, a location-clustering (L-clustering) algorithm is proposed to divide the continuous locations into different clusters based on the distance and density relationships among multiple groups. Then, a differential privacy-based location privacy protection algorithm (DPLPA) is proposed to protect users' location privacy, where Laplace noise is added to the resident points and centroids within the cluster. The experimental results show that the DPLPA achieves a high level of data utility, with minimal time consumption, while effectively protecting the privacy of location information.

Analysis of 14 terpenoids and sterols and variety discrimination of Codonopsis Radix using ultra-high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry.

Recently, we confirmed that the 95% ethanol-extracted fraction of Codonopsis Radix, which contains several triterpenoids and sterols, possesses pharmacological activities. However, due to the low content and diverse types of triterpenoids and sterols, their similar structures, lack of ultraviolet absorption, and difficulty in obtaining controls, few studies have so far assessed their contents in Codonopsis Radix. We accordingly constructed an ultra-high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry technique for the simultaneous quantitative determination of 14 terpenoids and sterols. Separation was performed on the Waters Acquity UPLC HSS T3 C18 column (100 × 2.1 mm, 1.8 µm) with 0.1% formic acid (A) and 0.1% formic acid in methanol (B) as mobile phase under gradient elution. The determination coefficients for each of the matrix calibration curves were ≥0.9925. The average recovery ranged from 81.25% to 118.05%, with relative standard deviations of <4%. The contents of 14 components in 23 batches were quantified and further analyzed through chemometrics. Linear discriminant analysis can distinguish sample varieties. The quantitative analysis method can accurately determine the contents of 14 components and thereby provide the chemical basis for the quality control of Codonopsis Radix. It also could be a valuable approach for the classification of different Codonopsis Radix varieties.

In vitro analysis of a physiological strain sensor formulated from a PEDOT:PSS functionalized carbon nanotube-poly(glycerol sebacate urethane) composite.

Biodegradable strain sensors able to undergo controlled degradation following implantation have recently received significant interest as novel approaches to detect pathological tissue swelling or non-physiological stresses. In this study, the physicomechanical, electrochemical and active pressure sensing behavior of an electrically conductive and biodegradable poly(glycerol sebacate urethane) (PGSU) composite, reinforced with poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) functionalized carbon nanotubes (CNTs), was evaluated in vitro. Analysis of these PGSU-CNTs composites demonstrated that the incorporation of functionalized CNTs into a biodegradable elastomer resulted in enhanced mechanical strength, conductivity and tailored matrix biodegradation. PGSU-CNT composites were subsequently formulated into flexible and active pressure sensors which demonstrated optimal sensitivity to applied 1% uniaxial tensile strains. Finally, cytocompatibility analysis a with primary neural culture confirmed that PGSU-CNT composites exhibited low cytotoxicity, and supported neuron adhesion, viability, and proliferation in vitro.

A randomized, double-blind, placebo-controlled, multicenter clinical trial for efficacy and safety of traditional Chinese medicine combined with antibiotics in the treatment of bacterial pneumonia in children.

BACKGROUND: Pneumonia is the second leading cause of death in children worldwide after preterm birth and certification. Bacteria, viruses, mycoplasma, and other microorganisms are known to be the main causes of pneumonia, of which bacterial pathogenic factors account for 12.5% of cases. The invention and application of antibiotics have improved the prognosis of children with community-acquired bacterial pneumonia (CABP) to a certain extent, but with the emergence of antibiotic resistance worldwide, the mortality of children with CABP is still high. "Maxing Shigan Decoction" and "Qingfei Decoction" have significant efficacy in the treatment of CABP in children, but there is no standardized randomized controlled trial to systematically evaluate the outcomes. METHODS: This study is a randomized, double-blind, placebo-controlled, multicenter clinical trial that will randomize 240 patients with CABP to group of Oral Maxing Shigan Decoction, group of Qingfei Decoction or group of placebos administered 3 times a day for 7 days. This study will observe a wide range of clinically relevant endpoints that have been used in clinical trials of pneumonia, including but not limited to clinical cure rate, antibiotic application days, complete antipyretic rate, complete antipyretic days, disease efficacy, traditional Chinese medicine syndrome effect, and antibiotic upgrade treatment rates. Safety will be assessed by monitoring for the incidence of adverse events during the study. DISCUSSION: This clinical trial is the first to evaluate the efficacy and safety of "Maxing Shigan Decoction" and "Qingfei Decoction" in the treatment of children with CABP. The research results will provide a reference for future research design. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1900025354. Registered on 14th October 2019-Retrospectively registered, http://www.chictr.org.cn/.

Impact of Protein Corona on Noncovalent Molecule-Gold Nanoparticle-Based Sensing.

Gold nanoparticle (AuNP)-based sensors have been extensively applied for sensing or imaging. It is known that a protein shell named protein corona (PC) formed around the nanomaterials could not only block the desired function of nanomaterials but also affect their behavior, which is a hot and important issue needing consideration. Therefore, we hypothesize that the formation of PC around AuNPs could inevitably affect the AuNP-based target assay. In this work, the effects of PC on the detection results in sensors based on AuNPs were studied. Three types of noncovalent molecule-AuNP sensors including AuNP-dichlorofluorescein, AuNP-aptamer, and AuNP-antibody-DNA were constructed, and several typical proteins (bovine serum albumin, fibrinogen, hemoglobin, and ß-lactoglobulin), milk, and fetal bovine serum were selected as models for the formation of PCs. This study shows that the PC could cause the loss of detection signals (up to 80%) and result in positive deviation of the measuring value compared with the true value. Moreover, the loss of detection signals could also increase the limits of detection (almost 10 times), decreasing the sensitivity of the three types of sensors, as proposed in this work compared to that without PC. Moreover, the polyethylene glycol backfilling strategy could not resolve the negative effects of PC on noncovalent molecule-AuNP sensors. The impacts of PC on detection results from noncovalent molecule-AuNP sensors would cause misdiagnosis or wasted production, which needs careful reconsideration of the AuNP-based detection in application fields like clinic diagnosis, food safety control, and so forth.

Joint Raindrop and Haze Removal from a Single Image.

In a recent study, it was shown that, with adversarial training of an attentive generative network, it is possible to convert a raindrop degraded image into a relatively clean one. However, in real world, raindrop appearance is not only formed by individual raindrops, but also by the distant raindrops accumulation and the atmospheric veiling, namely haze. Current methods are limited in extracting accurate features from a raindrop degraded image with background scene, the blurred raindrop regions, and the haze. In this paper, we propose a new model for an image corrupted by the raindrops and the haze, and introduce an integrated multi-task algorithm to address the joint raindrop and haze removal (JRHR) problem by combining an improved estimate of the atmospheric light, a modified transmission map, a generative adversarial network (GAN) and an optimized visual attention network. The proposed algorithm can extract more accurate features for both sky and non-sky regions. Experimental evaluation has been conducted to show that the proposed algorithm significantly outperforms state-of-the-art algorithms on both synthetic and real-world images in terms of both qualitative and quantitative measures.

Shaping Waves of Bone Morphogenetic Protein Inhibition During Vascular Growth.

RATIONALE: The BMPs (bone morphogenetic proteins) are essential morphogens in angiogenesis and vascular development. Disruption of BMP signaling can trigger cardiovascular diseases, such as arteriovenous malformations. OBJECTIVE: A computational model predicted that BMP4 and BMP9 and their inhibitors MGP (matrix gamma-carboxyglutamic acid [Gla] protein) and CV2 (crossveinless-2) would form a regulatory system consisting of negative feedback loops with time delays and that BMP9 would trigger oscillatory expression of the 2 inhibitors. The goal was to investigate this regulatory system in endothelial differentiation and vascular growth. METHODS AND RESULTS: Oscillations in the expression of MGP and CV2 were detected in endothelial cells in vitro, using quantitative real-time polymerase chain reaction and immunoblotting. These organized temporally downstream BMP-related activities, including expression of stalk-cell markers and cell proliferation, consistent with an integral role of BMP9 in vessel maturation. In vivo, the inhibitors were located in distinct zones in relation to the front of the expanding retinal network, as determined by immunofluorescence. Time-dependent changes of the CV2 location in the retina and the existence of an endothelial population with signs of oscillatory MGP expression in developing vasculature supported the in vitro findings. Loss of MGP or its BMP4-binding capacity disrupted the retinal vasculature, resulting in poorly formed networks, especially in the venous drainage areas, and arteriovenous malformations as determined by increased cell coverage and functional testing. CONCLUSIONS: Our results suggest a previously unknown mechanism of temporal orchestration of BMP4 and BMP9 activities that utilize the tandem actions of the extracellular antagonists MGP and CV2. Disruption of this mechanism may contribute to vascular malformations and disease.

Do job stress, health, and presenteeism differ between Chinese healthcare workers in public and private hospitals: a cross sectional study.

To determine if job stress, health, and presenteeism differ between healthcare workers at Chinese public and private hospitals. This cross-sectional study analyzed the records of 1080 healthcare workers in eastern, central, and western China for the period from January2015 through November2015. Data on challenge stress, hindrance stress, health, and presenteeism were collected. Using univariate and multivariate regression and SPSS, we investigated differences between Chinese public and private hospitals in China. Challenge stress, hindrance stress, and presenteeism, but not health status, significantly differed between healthcare workers at public and private hospitals in China. Challenge stress and hindrance stress were significantly higher in public hospitals, while presenteeism was significantly lower in private hospitals. The significant differences between public and private hospitals are attributable to differences in the business practices and management of public and private hospitals. To achieve successful long-term medical reform in China, the adverse effects of psychosocial factors should be considered in future research plans and policies. Chinese hospitals urgently require improvements in management and leadership. Reform efforts should encompass fields such as management science, psychology, and the behavioral sciences.

Noggin depletion in adipocytes promotes obesity in mice.

OBJECTIVE: Obesity has increased to pandemic levels and enhanced understanding of adipose regulation is required for new treatment strategies. Although bone morphogenetic proteins (BMPs) influence adipogenesis, the effect of BMP antagonists such as Noggin is largely unknown. The aim of the study was to define the role of Noggin, an extracellular BMP inhibitor, in adipogenesis. METHODS: We generated adipose-derived progenitor cells and a mouse model with adipocyte-specific Noggin deletion using the AdiponectinCre transgenic mouse, and determined the adipose phenotype of Noggin-deficiency. RESULTS: Our studies showed that Noggin is expressed in progenitor cells but declines in adipocytes, possibly allowing for lipid accumulation. Correspondingly, adipocyte-specific Noggin deletion in vivo promoted age-related obesity in both genders with no change in food intake. Although the loss of Noggin caused white adipose tissue hypertrophy, and whitening and impaired function in brown adipose tissue in both genders, there were clear gender differences with the females being most affected. The females had suppressed expression of brown adipose markers and thermogenic genes including peroxisome proliferator activated receptor gamma coactivator 1 alpha (PGC1alpha) and uncoupling protein 1 (UCP1) as well as genes associated with adipogenesis and lipid metabolism. The males, on the other hand, had early changes in a few BAT markers and thermogenic genes, but the main changes were in the genes associated with adipogenesis and lipid metabolism. Further characterization revealed that both genders had reductions in VO2, VCO2, and RER, whereas females also had reduced heat production. Noggin was also reduced in diet-induced obesity in inbred mice consistent with the obesity phenotype of the Noggin-deficient mice. CONCLUSIONS: BMP signaling regulates female and male adipogenesis through different metabolic pathways. Modulation of adipose tissue metabolism by select BMP antagonists may be a strategy for long-term regulation of age-related weight gain and obesity.

Job Stress and Presenteeism among Chinese Healthcare Workers: The Mediating Effects of Affective Commitment.

BACKGROUND: Presenteeism affects the performance of healthcare workers. This study examined associations between job stress, affective commitment, and presenteeism among healthcare workers. METHODS: To investigate the relationship between job stress, affective commitment, and presenteeism, structural equation modeling was used to analyze a sample of 1392 healthcare workers from 11 Class A tertiary hospitals in eastern, central, and western China. The mediating effect of affective commitment on the association between job stress and presenteeism was examined with the Sobel test. RESULTS: Job stress was high and the level of presenteeism was moderate among healthcare workers. Challenge stress and hindrance stress were strongly correlated (ß = 0.62; p < 0.05). Affective commitment was significantly and directly inversely correlated with presenteeism (ß = -0.27; p < 0.001). Challenge stress was significantly positively correlated with affective commitment (ß = 0.15; p < 0.001) but not with presenteeism. Hindrance stress was significantly inversely correlated with affective commitment (ß = -0.40; p < 0.001) but was significantly positively correlated with presenteeism (ß = 0.26; p < 0.001). CONCLUSIONS: This study provides important empirical data on presenteeism among healthcare workers. Presenteeism can be addressed by increasing affective commitment and challenge stress and by limiting hindrance stress among healthcare workers in China.

Assembling Ordered Nanorod Superstructures and Their Application as Microcavity Lasers.

Herein we report the formation of multi-layered arrays of vertically aligned and close packed semiconductor nanorods in perfect registry at a substrate using electric field assisted assembly. The collective properties of these CdSexS1-x nanorod emitters are harnessed by demonstrating a relatively low amplified spontaneous emission (ASE) threshold and a high net optical gain at medium pump intensity. The importance of order in the system is highlighted where a lower ASE threshold is observed compared to disordered samples.

Factors Influencing the Performance of Pd/C Catalysts in the Green Production of Hydrogen from Formic Acid.

Formic acid derived from biomass is known to be used for hydrogen production over Pd catalysts. The effects of preparation variables, structure of the carbon support, surface functional composition on the state of Pd, and catalytic properties of the samples in the vapor-phase decomposition of formic acid were studied. In all catalysts derived from Pd acetate, metal particles visible by conventional TEM had similar sizes, but the adsorption capacity towards CO responded strongly to N-doping of the carbon surface. Moreover, a decrease in the CO/Pd values was accompanied by a significant increase in the reaction rate. Taking account of X-ray photoelectron spectroscopy (XPS) and atomic resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF/STEM) data, the trends observed were assigned to a larger fraction of single electron-deficient Pd atoms in the N-doped samples, which do not adsorb CO but interact with formic acid to produce hydrogen. This was confirmed by extended DFT studies. The obtained results are valuable for the development of Pd catalysts on carbon supports for different processes.

Fungal surface protein mediated one-pot synthesis of stable and hemocompatible gold nanoparticles.

Despite their large secretome and wide applications in bioprocesses, fungi remain underexplored in metal nanoparticles (MNP) biosynthesis. Previous studies have shown that cell surface proteins of Rhizopus oryzae play a crucial role in biomineralization of Au(III) to produce gold nanoparticles (AuNPs). Therefore, it is hypothesized that purified cell surface protein may produce in vitro AuNPs with narrow size distribution for biomedical and biocatalytic applications. However, different protein extraction methods might affect protein stability and the AuNP biosynthesis process. Herein, we have explored the extraction of cell surface proteins from R. oryzae using common detergents and reducing agent (sodium dodecyl sulfate (SDS) Triton X-100, and 1,4-dithiothreitol (DTT)) and their effect on the size and shape of the biosynthetic AuNPs. The surface proteins extracted with reducing agent (DTT) and non-ionic detergent (Triton X-100) produce spherical AuNPs with a mean particle size of 16±7nm, and 19±4nm, respectively, while the AuNPs produced by the surface protein extracted by ionic detergent (SDS) are flower-like AuNPs with broader size distribution of 43±19nm. This synthetic approach does not require use of any harsh chemicals, multistep preparation and separation process, favouring environmental sustainability. The biosynthetic AuNPs thus formed, are stable in different physiological buffers and hemocompatible, making them suitable for biomedical applications.