Graphene Nanocomposite Ink Coated Laser Transformed Flexible Electrodes for Selective Dopamine Detection and Immunosensing.

Novel and flexible disposable laser-induced graphene (LIG) sensors modified with graphene conductive inks have been developed for dopamine and interleukin-6 (IL-6) detection. The LIG sensors exhibit high reproducibility (relative standard deviation, RSD = 0.76%, N = 5) and stability (RSD = 4.39%, N = 15) after multiple bendings, making the sensors ideal for wearable and stretchable bioelectronics applications. We have developed electrode coatings based on graphene conductive inks, poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (G-PEDOT:PSS) and polyaniline (G-PANI), for working electrode modification to improve the sensitivity and limit of detection (LOD). The selectivity of LIG sensors modified with the G-PANI ink is 41.47 times higher than that of the screen-printed electrode with the G-PANI ink modification. We have compared our fabricated bare laser-engraved Kapton sensor (LIG) with the LIG sensors modified with G-PEDOT (LIG/G-PEDOT) and G-PANI (LIG/G-PANI) conductive inks. We have further compared the performance of the fabricated electrodes with commercially available screen-printed electrodes (SPEs) and screen-printed electrodes modified with G-PEDOT:PSS (SPE/G-PEDOT:PSS) and G-PANI (SPE/G-PANI). SPE/G-PANI has a lower LOD of 0.632 µM compared to SPE/G-PEDOT:PSS (0.867 µM) and SPE/G-PANI (1.974 µM). The lowest LOD of the LIG/G-PANI sensor (0.4084 µM, S/N = 3) suggests that it can be a great alternative to measure dopamine levels in a physiological medium. Additionally, the LIG/G-PANI electrode has excellent LOD (2.6234 pg/mL) to detect IL-6. Also, the sensor is successfully able to detect ascorbic acid (AA), dopamine (DA), and uric acid (UA) in their ternary mixture. The differential pulse voltammetry (DPV) result shows peak potential separation of 229, 294, and 523 mV for AA-DA, DA-UA, and UA-AA, respectively.

Association of biosecurity and hygiene practices with avian influenza A/H5 and A/H9 virus infections in turkey farms.

High pathogenicity avian influenza (HPAI) H5N1 outbreaks pose a significant threat to the health of livestock, wildlife, and humans. Avian influenza viruses (AIVs) are enzootic in poultry in many countries, including Bangladesh, necessitating improved farm biosecurity measures. However, the comprehension of biosecurity and hygiene practices, as well as the infection of AIV in turkey farms, are poorly understood in Bangladesh. Therefore, we conducted this study to determine the prevalence of AIV subtypes and their association with biosecurity and hygiene practices in turkey farms. We collected oropharyngeal and cloacal swabs from individual turkeys from 197 farms across 9 districts in Bangladesh from March to August 2019. We tested the swab samples for the AIV matrix gene (M gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We found 24.68% (95% CI:21.54-28.04) of turkey samples were AIV positive, followed by 5.95% (95% CI: 4.33-7.97) for H5, 6.81% (95% CI: 5.06-8.93) for H9 subtype and no A/H7 was found. Using a generalized linear mixed model, we determined 10 significant risk factors associated with AIV circulation in turkey farms. We found that the absence of sick turkeys, the presence of footbaths, the absence of nearby poultry farms, concrete flooring, and the avoidance of mixing newly purchased turkeys with existing stock can substantially reduce the risk of AIV circulation in turkey farms (odds ratio ranging from 0.02 to 0.08). Furthermore, the absence of nearby live bird markets, limiting wild bird access, no visitor access, improved floor cleaning frequency, and equipment disinfection practices also had a substantial impact on lowering the AIV risk in the farms (odds ratio ranging from 0.10 to 0.13). The results of our study underscore the importance of implementing feasible and cost-effective biosecurity measures aimed at reducing AIV transmission in turkey farms. Particularly in resource-constrained environments such as Bangladesh, such findings might assist governmental entities in enhancing biosecurity protocols within their poultry sector, hence mitigating and potentially averting the transmission of AIV and spillover to humans.

Synthesis and optical properties of WS2 nanotubes with relatively small diameters.

Tungsten disulfide (WS2) nanotubes exhibit various unique properties depending on their structures, such as their diameter and wall number. The development of techniques to prepare WS2 nanotubes with the desired structure is crucial for understanding their basic properties. Notably, the synthesis and characterization of multi-walled WS2 nanotubes with small diameters are challenging. This study reports the synthesis and characterization of small-diameter WS2 nanotubes with an average inner diameter of 6 nm. The optical absorption and photoluminescence (PL) spectra of the as-prepared nanotubes indicate that a decrease in the nanotube diameter induces a red-shift in the PL, suggesting that the band gap narrowed due to a curvature effect, as suggested by theoretical calculations.

A Facile Graphene Conductive Polymer Paper Based Biosensor for Dopamine, TNF-α, and IL-6 Detection.

Paper-based biosensors are a potential paradigm of sensitivity achieved via microporous spreading/microfluidics, simplicity, and affordability. In this paper, we develop decorated paper with graphene and conductive polymer (herein referred to as graphene conductive polymer paper-based sensor or GCPPS) for sensitive detection of biomolecules. Planetary mixing resulted in uniformly dispersed graphene and conductive polymer ink, which was applied to laser-cut Whatman filter paper substrates. Scanning electron microscopy and Raman spectroscopy showed strong attachment of conductive polymer-functionalized graphene to cellulose fibers. The GCPPS detected dopamine and cytokines, such as tumor necrosis factor-alpha (TNF-α), and interleukin 6 (IL-6) in the ranges of 12.5-400 µM, 0.005-50 ng/mL, and 2 pg/mL-2 µg/mL, respectively, using a minute sample volume of 2 µL. The electrodes showed lower detection limits (LODs) of 3.4 µM, 5.97 pg/mL, and 9.55 pg/mL for dopamine, TNF-α, and IL-6 respectively, which are promising for rapid and easy analysis for biomarkers detection. Additionally, these paper-based biosensors were highly selective (no serpin A1 detection with IL-6 antibody) and were able to detect IL-6 antigen in human serum with high sensitivity and hence, the portable, adaptable, point-of-care, quick, minute sample requirement offered by our fabricated biosensor is advantageous to healthcare applications.

Semiconducting Transition Metal Dichalcogenide Heteronanotubes with Controlled Outer-Wall Structures.

Transition metal dichalcogenide (TMDC) nanotubes exhibit unique physical properties due to their nanotube structures. The development of techniques for synthesizing TMDC nanotubes with controlled structures is very important for their science and applications. However, structural control efforts have been made only for the homostructures of TMDC nanotubes and not for their heterostructures that provide an important platform for their two-dimensional counterparts. In this study, we synthesized heterostructures of TMDC nanotubes, MoS2/WS2 heteronanotubes, and demonstrated a technique for controlling features of their structures, such as diameters, layer numbers, and crystallinity. The diameter of the heteronanotubes could be tuned with inner nanotube templates and was reduced by using small-diameter WS2 nanotubes. The layer number and crystallinity of the MoS2 outer wall could be controlled by controlling their precursors and synthesis temperatures, resulting in the formation of high-crystallinity TMDC heteronanotubes with specific chirality. This study can expand the research of van der Waals heterostructures.

FracAtlas: A Dataset for Fracture Classification, Localization and Segmentation of Musculoskeletal Radiographs.

Digital radiography is one of the most common and cost-effective standards for the diagnosis of bone fractures. For such diagnoses expert intervention is required which is time-consuming and demands rigorous training. With the recent growth of computer vision algorithms, there is a surge of interest in computer-aided diagnosis. The development of algorithms demands large datasets with proper annotations. Existing X-Ray datasets are either small or lack proper annotation, which hinders the development of machine-learning algorithms and evaluation of the relative performance of algorithms for classification, localization, and segmentation. We present FracAtlas, a new dataset of X-Ray scans curated from the images collected from 3 major hospitals in Bangladesh. Our dataset includes 4,083 images that have been manually annotated for bone fracture classification, localization, and segmentation with the help of 2 expert radiologists and an orthopedist using the open-source labeling platform, makesense.ai. There are 717 images with 922 instances of fractures. Each of the fracture instances has its own mask and bounding box, whereas the scans also have global labels for classification tasks. We believe the dataset will be a valuable resource for researchers interested in developing and evaluating machine learning algorithms for bone fracture diagnosis.

Comparison and assessment of methods for cellulose crystallinity determination.

The degree of crystallinity in cellulose significantly affects the physical, mechanical, and chemical properties of cellulosic materials, their processing, and their final application. Measuring the crystalline structures of cellulose is a challenging task due to inadequate consistency among the variety of analytical techniques available and the lack of absolute crystalline and amorphous standards. Our article reviews the primary methods for estimating the crystallinity of cellulose, namely, X-ray diffraction (XRD), nuclear magnetic resonance (NMR), Raman and Fourier-transform infrared (FTIR) spectroscopy, sum-frequency generation vibrational spectroscopy (SFG), as well as differential scanning calorimetry (DSC), and evolving biochemical methods using cellulose binding molecules (CBMs). The techniques are compared to better interrogate not only the requirements of each method, but also their differences, synergies, and limitations. The article highlights fundamental principles to guide the general community to initiate studies of the crystallinity of cellulosic materials.

BEENE: deep learning-based nonlinear embedding improves batch effect estimation.

MOTIVATION: Analyzing large-scale single-cell transcriptomic datasets generated using different technologies is challenging due to the presence of batch-specific systematic variations known as batch effects. Since biological and technological differences are often interspersed, detecting and accounting for batch effects in RNA-seq datasets are critical for effective data integration and interpretation. Low-dimensional embeddings, such as principal component analysis (PCA) are widely used in visual inspection and estimation of batch effects. Linear dimensionality reduction methods like PCA are effective in assessing the presence of batch effects, especially when batch effects exhibit linear patterns. However, batch effects are inherently complex and existing linear dimensionality reduction methods could be inadequate and imprecise in the presence of sophisticated nonlinear batch effects. RESULTS: We present Batch Effect Estimation using Nonlinear Embedding (BEENE), a deep nonlinear auto-encoder network which is specially tailored to generate an alternative lower dimensional embedding suitable for both linear and nonlinear batch effects. BEENE simultaneously learns the batch and biological variables from RNA-seq data, resulting in an embedding that is more robust and sensitive than PCA embedding in terms of detecting and quantifying batch effects. BEENE was assessed on a collection of carefully controlled simulated datasets as well as biological datasets, including two technical replicates of mouse embryogenesis cells, peripheral blood mononuclear cells from three largely different experiments and five studies of pancreatic islet cells. AVAILABILITY AND IMPLEMENTATION: BEENE is freely available as an open source project at https://github.com/ashiq24/BEENE.

Integrated Computational Approaches for Inhibiting Sex Hormone-Binding Globulin in Male Infertility by Screening Potent Phytochemicals.

Male infertility is significantly influenced by the plasma-protein sex hormone-binding globulin (SHBG). Male infertility, erectile dysfunction, prostate cancer, and several other male reproductive system diseases are all caused by reduced testosterone bioavailability due to its binding to SHBG. In this study, we have identified 345 phytochemicals from 200 literature reviews that potentially inhibit severe acute respiratory syndrome coronavirus 2. Only a few studies have been done using the SARS-CoV-2 inhibitors to identify the SHBG inhibitor, which is thought to be the main protein responsible for male infertility. In virtual-screening and molecular-docking experiments, cryptomisrine, dorsilurin E, and isoiguesterin were identified as potential SHBG inhibitors with binding affinities of -9.2, -9.0, and -8.8 kcal/mol, respectively. They were also found to have higher binding affinities than the control drug anastrozole (-7.0 kcal/mol). In addition to favorable pharmacological properties, these top three phytochemicals showed no adverse effects in pharmacokinetic evaluations. Several molecular dynamics simulation profiles' root-mean-square deviation, radius of gyration, root-mean-square fluctuation, hydrogen bonds, and solvent-accessible surface area supported the top three protein-ligand complexes' better firmness and stability than the control drug throughout the 100 ns simulation period. These combinatorial drug-design approaches indicate that these three phytochemicals could be developed as potential drugs to treat male infertility.

Automatic dispersion, defect, curing, and thermal characteristics determination of polymer composites using micro-scale infrared thermography and machine learning algorithm.

Infrared thermography is a non-destructive technique that can be exploited in many fields including polymer composite investigation. Based on emissivity and thermal diffusivity variation; components, defects, and curing state of the composite can be identified. However, manual processing of thermal images that may contain significant artifacts, is prone to erroneous component and property determination. In this study, thermal images of different graphite/graphene-based polymer composites fabricated by hand, planetary, and batch mixing techniques were analyzed through an automatic machine learning model. Filler size, shape, and location can be identified in polymer composites and thus, the dispersion of different samples was quantified with a resolution of ~ 20 µm despite having artifacts in the thermal image. Thermal diffusivity comparison of three mixing techniques was performed for 40% graphite in the elastomer. Batch mixing demonstrated superior dispersion than planetary and hand mixing as the dispersion index (DI) for batch mixing was 0.07 while planetary and hand mixing showed 0.0865 and 0.163 respectively. Curing was investigated for a polymer with different fillers (PDMS took 500 s while PDMS-Graphene and PDMS Graphite Powder took 800 s to cure), and a thermal characteristic curve was generated to compare the composite quality. Therefore, the above-mentioned methods with machine learning algorithms can be a great tool to analyze composite both quantitatively and qualitatively.

Food safety and handling knowledge and practices among university students of Bangladesh: A cross-sectional study.

Our study aimed to examine the practices and knowledge of food handling and safety among 1534 university students in Bangladesh (mean age 22.09 ± 1.78), as well as the relationship between these factors and their academic and demographic backgrounds. Participants in this study were undergraduate and graduate students from four public universities in Bangladesh from different religions, income levels, years and majors of study, residential areas, living alone or not, and whose mothers are working or non-working. The questionnaire included 14 questions on food handling practices and 16 on knowledge. Questions were related to food preparation, hygiene, cross-contamination, and storage. The overall mean score for food handling practices was 34.9% (SD = 13.7), while that of knowledge was 41.8% (SD = 16.5). Female students, those from food-related majors, and those engaged in cooking activities scored significantly higher in the knowledge and practice sections (p < 0.05). Students who lived with their families performed significantly better on the knowledge parts, while those who shared a home with roommates in mess performed significantly better on the practice part (p < 0.05). Students having housewife mothers, personal poisoning experience, and continuous involvement in food purchasing scored significantly higher (p < 0.05) in the practices section but not in the knowledge one. On the other hand, students living in urban areas scored significantly higher (p < 0.05) in the knowledge section but not in the practices one. Our results highlight the importance of educational interventions and initiatives to enhance food safety awareness among Bangladeshi university students.

Epidemiology and molecular characterization of avian influenza virus in backyard poultry of Chattogram, Bangladesh.

Ducks, the natural reservoir of avian influenza virus (AIV), act as reassortment vessels for HPAI and low pathogenic avian influenza (LPAI) virus for domestic and wild bird species. In Bangladesh, earlier research was mainly focused on AIV in commercial poultry and live bird markets, where there is scanty literature reported on AIV in apparently healthy backyard poultry at the household level. The present cross-sectional study was carried out to reveal the genomic epidemiology of AIV of backyard poultry in coastal (Anowara) and plain land (Rangunia) areas of Bangladesh. We randomly selected a total of 292 households' poultry (having both chicken and duck) for sampling. We administered structured pre-tested questionnaires to farmers through direct interviews. We tested cloacal samples from birds for the matrix gene (M gene) followed by H5 and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). All AIV-positive samples were subjected to four-gene segment sequencing (M, PB1, HA, and NA gene). We found that the prevalence of AIV RNA at the household level was 6.2% (n = 18; N = 292), whereas duck and chicken prevalence was 3.6% and 3.2%, respectively. Prevalence varied with season, ranging from 3.1% in the summer to 8.2% in the winter. The prevalence of subtypes H5 and H9 in backyard poultry was 2.7% and 3.3%, respectively. The phylogenetic analysis of M, HA, NA, and PB1 genes revealed intra-genomic similarity, and they are closely related to previously reported AIV strains in Bangladesh and Southeast Asia. The findings indicate that H5 and H9 subtypes of AIV are circulating in the backyard poultry with or without clinical symptoms. Moreover, we revealed the circulation of 2.3.2.1a (new) clade among the chicken and duck population without occurring outbreak which might be due to vaccination. In addition to routine surveillance, molecular epidemiology of AIV will assist to gain a clear understanding of the genomic evolution of the AIV virus in the backyard poultry rearing system, thereby facilitating the implementation of effective preventive measures to control infection and prevent the potential spillover to humans.

Seroprevalence and risk factors of bluetongue virus in sheep of Chattogram, Bangladesh.

Background and Aim: Bluetongue (BT) is a non-contagious, infectious disease of wild and domestic ruminant animals caused by the BT virus (BTV). Bangladesh having a border with a BTV-endemic country, India and a substantial number of susceptible animals. Therefore, this study aimed to estimate BTV seroprevalence and potential risk factors. Materials and Methods: We collected 150 serum samples from indigenous sheep from Chattogram, Bangladesh. We screened the serum samples using a competitive enzyme-linked immunosorbent assay for detecting BTV-specific immunoglobulin. Results: We detected antibodies against BTV in 39.3% (59/150; 95% confidence interval: 31.5-47.6) of all sampled sheep. Factors like sampling site, sheep rearing location, rearing sheep with other farm species, and body condition score had a significant (p < 0.05) influence on the seroprevalence of BTV. Conclusion: The findings show that indigenous sheep have a higher BTV seroprevalence, necessitating sustained surveillance for early diagnosis and a better understanding of virus epidemiology in Bangladesh.

Graphene-Coated PVDF/PAni Fiber Mats and Their Applications in Sensing and Nanogeneration.

Forcespinning is a powerful technique to produce fiber systems with suitable properties for a vast array of applications. This study investigates the sensing and energy generation performance of PVDF/PAni fiber mat systems made by the forcespinning method with and without graphene coating. The developed fiber mats were coated with graphene nanoflakes by drop-casting. The graphene-coated nanocomposites show an average output voltage of 75 mV (peak-to-peak), which is 300% higher compared to bare fiber mats, and an output current of 24 mA (peak-to-peak) by gentle finger pressing. Moreover, graphene-coated PVDF/PAni showed a volume conductivity of 1.2 × 10-7 S/cm and was investigated as a promising system for temperature (5 times better sensitivity than normal fiber mat), vibration (2 times better voltage generation), and airflow sensing. The graphene-coated composite has been further investigated as a water tide energy harvesting piezoelectric nanogenerator, with the system generating ∼40 mV for a synthetic ocean wave with a flow rate of 30 mL/min. In the future, graphene-coated nanofiber mats can be a solution for low-powered sensors and to harvest blue energy and vibration energy.

Modelling the causes of boiler accidents: implications for economic and social sustainability at the workplace.

This study aims to examine the causes of boiler accidents in the context of the ready-made garment (RMG) industry of Bangladesh as an emerging economy. On the basis of a comprehensive review of the existing literature, previous accident reports, and technical discussion with relevant personnel in the industries and regulating authorities, a total of 14 causes of boiler accidents were identified. This study merged neutrosophic (N) theory with the analytic hierarchy process (AHP) for prioritizing the causes of boiler accidents. Finally, to examine the reliability of the results, a robustness analysis was performed. The findings reveal that the lack of standard legislation, non-standard boiler operation, use of expired, non-registered, and non-certified boilers, faulty design of boilers, and the shortage of skilled boiler operators are the top five notable causes of boiler accidents in the RMG industry. The findings provide valuable insights for industrial managers and policymakers to formulate strategies to reduce boiler accidents.

CHAPAO: Likelihood and hierarchical reference-based representation of biomolecular sequences and applications to compressing multiple sequence alignments.

BACKGROUND: High-throughput experimental technologies are generating tremendous amounts of genomic data, offering valuable resources to answer important questions and extract biological insights. Storing this sheer amount of genomic data has become a major concern in bioinformatics. General purpose compression techniques (e.g. gzip, bzip2, 7-zip) are being widely used due to their pervasiveness and relatively good speed. However, they are not customized for genomic data and may fail to leverage special characteristics and redundancy of the biomolecular sequences. RESULTS: We present a new lossless compression method CHAPAO (COmpressing Alignments using Hierarchical and Probabilistic Approach), which is especially designed for multiple sequence alignments (MSAs) of biomolecular data and offers very good compression gain. We have introduced a novel hierarchical referencing technique to represent biomolecular sequences which combines likelihood based analyses of the sequence similarities and graph theoretic algorithms. We performed an extensive evaluation study using a collection of real biological data from the avian phylogenomics project, 1000 plants project (1KP), and 16S and 23S rRNA datasets. We report the performance of CHAPAO in comparison with general purpose compression techniques as well as with MFCompress and Nucleotide Archival Format (NAF)-two of the best known methods especially designed for FASTA files. Experimental results suggest that CHAPAO offers significant improvements in compression gain over most other alternative methods. CHAPAO is freely available as an open source software at https://github.com/ashiq24/CHAPAO. CONCLUSION: CHAPAO advances the state-of-the-art in compression algorithms and represents a potential alternative to the general purpose compression techniques as well as to the existing specialized compression techniques for biomolecular sequences.

Characterizing the Aging Process of the Human Eye: Tear Evaporation, Fluid Dynamics, Blood Flow, and Metabolism-Based Comparative Study.

Eye temperature and intraocular pressure are two measurable parameters that can be monitored as a health index with aging. Deviations from the normal range of intraocular pressure and temperature lead to the formation of many diseases. This study has been carried out to evaluate the relations between the physiological and anatomical changes of the eye with aging using mathematical modeling. 2D computer-aided design of the human eye has been developed for two major groups: 21 to 30 years and 41 to 50 years. The computer simulation has been carried out to determine the effects of physiological changes of tear evaporation, fluid dynamics, blood flow, and metabolism of eye tissues with aging. The simulation has been carried out in the standing and the supine position of a human body. The rate of temperature change is - 0.0075 K per year in the standing position and - 0.007 K per year in the supine position because of the modeled anatomical and physiological effects. All the three simulation parameters of this study, the temperature of the human eye, the intraocular pressure, and the aqueous humor flow velocity, have been compared with the recent practical and simulation-based experiments to validate our results.

Prevalence and risk factors of Avian Influenza Viruses among household ducks in Chattogram, Bangladesh.

Avian influenza viruses (AIV) increase commercial and backyard poultry mortality and morbidity, reduces egg production, and elevates public health risk. Household ducks propagate and transmit HPAI and LPAI viruses between domesticated and wild birds in Southeast Asian countries, including Bangladesh. This study was conducted to identify epidemiological factors associated with AIV infection among household ducks at Chattogram, Bangladesh. We randomly selected and collected blood and oropharyngeal swab samples from 281 households ducks. We evaluated the serum for AIV antibody using cELISA and tested for H5 and H9 subtypes using the HI test. We tested the swabs with real-time reverse transcriptase PCR (rRT-PCR) for M gene, and H5, H9 subtypes. In the duck populations, the household level AIV sero-prevalence was 57.7% (95% CI: 51.6-63.3) and RNA prevalence was 2.4% (95% CI: 1.0-5.0). H5 and H9 subtype sero-prevalence was 31.5% (95% CI: 22.2-42.0) and 23.9% (95% CI: 15.6-33.9). H5 and H9 subtype RNA prevalence were 0% (95% CI: 0.0-1.3) and 2.4% (95% CI: 1.0-5.0). We determined household-level OR (Odds Ratios) for the "combined (mixed materials-mud and concrete or metallic)" category was 2.2 (95% CI: 1.1-4.2) compared with "wooden/bamboo" category (p = 0.02); 2.8 (95% CI: 1.2-6.6) in households with duck plague vaccine coverage compared with no coverage (p = 0.01); and 2.4 (95% CI: 0.6-9.7) in households that threw dead birds in bushes and the roadside compared with households that buried or threw dead birds in garbage pits (p = 0.21). M gene phylogenetic analysis compared M gene sequences to previously reported Bangladeshi H9N2 isolates. The evidence presented here shows AIV circulation in the Chattogram, Bangladesh study areas. AIV reduction can be achieved through farmer education of proper farm management practices.

Progress in surface-modified silicas for Cr(VI) adsorption: A review.

Various toxic chemicals are discharging to the environment due to rapid industrialization and polluting soil, water, and air causing numerous diseases including life-threatening cancer. Among these pollutants, Cr(VI) or hexavalent chromium is one of the most carcinogenic and toxic contaminants hostile to human health and other living things. Therefore, along with other contaminants, the removal of Cr(VI) efficiently is very crucial to keep our environment neat and clean. On the other hand, silica has a lot of room to modify its surfaces as it is available with various sizes, shapes, pore sizes, surface areas etc. and the surface silanol groups are susceptible to design and prepare adsorbents for Cr(VI). This review emphases on the progress in the development of different types of silica-based adsorbents by modifying the surfaces of silica and their application for the removal of Cr(VI) from wastewater. Toxicity of Cr(VI), different silica surface modification processes, and removal techniques are also highlighted. The adsorption capacities of the surface-modified silica materials with other parameters are discussed extensively to understand how to select the best condition, silica and modifiers to achieve optimum removal performance. The adsorption mechanisms of various adsorbents are also discussed. Finally, future prospects are summarized and some suggestions are given to enhance the adsorption capacities of the surface-modified silica materials.