Surface enhanced Raman spectroscopy based analysis of SARS-CoV-2 spike protein binding to ACE2 receptor

The SARS-CoV-2 virus is still a challenge because of its diversity and mutations. The binding interactions of the angiotensin converting enzyme 2 (ACE2) receptor and the spike protein are relevant for the SARS-CoV-2 virus to enter the cell. Consequently, it is important and helpful to analyze binding activities and the changes in the structure of the ACE2 receptor and the spike protein. Surface enhanced Raman spectroscopy is able to analyze small concentrations of the proteins without contact, non-invasively and label-free. In this work, we present a SERS based approach in the visible wavelength range to analyze and study the binding interactions of the ACE2 receptor and the spike protein. SERS measurements of the ACE2 receptor, the spike protein and the ACE2-spike complex were performed. Additionally, an inhibitor was used to prevent the spike protein from binding to ACE2 and to compare the results. The analysis of the measured SERS spectra reveals structural differences and changes due to binding activities. Thus, we show that the performed SERS based approach can help for rapid and non-invasive analysis of binding interactions of the ACE2-spike complex and also of protein binding in general. © 2023 SPIE.

Nanosponges: As a Dynamic Drug Delivery Approach for Targeted Delivery

Recent advancements in nanotechnology have resulted in improved medicine delivery to the target site. Nanosponges are three-dimensional drug delivery systems that are nanoscale in size and created by cross-linking polymers. The introduction of Nanosponges has been a significant step toward overcoming issues such as drug toxicity, low bioavailability, and predictable medication release. Using a new way of nanotechnology, nanosponges, which are porous with small sponges (below one microm) flowing throughout the body, have demonstrated excellent results in delivering drugs. As a result, they reach the target place, attach to the skin's surface, and slowly release the medicine. Nanosponges can be used to encapsulate a wide range of medicines, including both hydrophilic and lipophilic pharmaceuticals. The medication delivery method using nanosponges is one of the most promising fields in pharmacy. It can be used as a biocatalyst carrier for vaccines, antibodies, enzymes, and proteins to be released. The existing study enlightens on the preparation method, evaluation, and prospective application in a medication delivery system and also focuses on patents filed in the field of nanosponges.Copyright © 2023 The Authors.

Rapid and Low-Cost Detection of Human Corona Virus Using MEMS ATR-FTIR Spectroscopy

The conventional methods used for the diagnostics of viral infection are either expensive and time-consuming or not accurate enough and dependent on consumable reagents. In the presence of pandemics, a fast and reagent-free solution is needed for mass screening. Recently, the diagnosis of viral infections using infrared spectroscopy has been reported as a fast and low-cost method. In this work a fast and low-cost solution for corona viral detection using infrared spectroscopy based on a compact micro-electro-mechanical systems (MEMS) device and artificial intelligence (AI) suitable for mass deployment is presented. Among the different variants of the corona virus that can infect people, 229E is used in this study due to its low pathogeny. The MEMS ATR-FTIR device employs a 6 reflections ZnSe crystal interface working in the spectral range of 2200-7000 cm-1. The virus was propagated and maintained in a medium for long enough time then cell supernatant was collected and centrifuged. The supernatant was then transferred and titrated using plaque titration assay. Positive virus samples were prepared with a concentration of 105 PFU/mL. Positive and negative control samples were applied on the crystal surface, dried using a heating lamp and the spectrum was captured. Principal component analysis and logistic regression were used as simple AI techniques. A sensitivity of about 90 % and a specificity of about 80 % were obtained demonstrating the potential detection of the virus based on the MEMS FTIR device. © 2023 SPIE.

Anomalies of O3, CO, C2H2, H2CO, and C2H6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability

Anomalies of tropospheric columns of ozone (O3), carbon monoxide (CO), acetylene (C2H2), formaldehyde (H2CO), and ethane (C2H6) are quantified during the 2020 stringent COVID-19 world-wide lockdown using multiple ground-based Fourier-transform infrared spectrometers covering urban and remote conditions. We applied an exponential smoothing forecasting approach to the data sets to estimate business-as-usual values for 2020, which are then contrasted with actual observations. The Community Atmosphere Model with chemistry (CAM-chem) is used to simulate the same gases using lockdown-adjusted and business-as-usual emissions. The role of meteorology, or natural variability, is assessed with additional CAM-chem simulations. The tropospheric column of O3 declined between March and May 2020 for most sites with a mean decrease of 9.2% ± 4.7%. Simulations reproduce these anomalies, especially under background conditions where natural variability explains up to 80% of the decline for sites in the Northern Hemisphere. While urban sites show a reduction between 1% and 12% in tropospheric CO, the remote sites do not show a significant change. Overall, CAM-chem simulations capture the magnitude of the anomalies and in many cases natural variability and lockdowns have opposite effects. We further used the long-term record of the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument to capture global anomalies of CO. Reductions of CO vary highly across regions but North America and Europe registered lower values in March 2020.The absence of CO reduction in April and May, concomitant with reductions of anthropogenic emissions, is explained by a negative anomaly in the hydroxyl radical (OH) found with CAM-chem.The implications of these findings are discussed for methane (CH4), which shows a positive lifetime anomaly during the COVID-19 lockdown period. The fossil fuel combustion by-product tracer C2H2 shows a mean drop of 13.6% ± 8.3% in urban Northern Hemisphere sites due to the reduction in emissions and in some sites exacerbated by natural variability. For some sites with anthropogenic influence there is a decrease in C2H6.The simulations capture the anomalies but the main cause may be related to natural variability. H2CO declined during the stringent 2020 lockdown in all urban sites explained by reductions in emissions of precursors. Copyright: © 2023 The Author(s).

Optimization and Characterization of Quercetin Vitamin C Nano-Phytosome Formulation

Objective: To design an optimal formulation for quercetin and vitamin C nano-phytosome. Method(s): Nano-phytosomes are prepared by the thin layer hydration technique using a 2-level-5-factor design experimental. A total of 32 experimental formulas were used for data analysis. The ratio of quercetin: soy lecithin (X1), the ratio of quercetin: cholesterol (X2), stirring speed (X3), stirring temperature (X4), and stirring time (X5) were used as independent factors, while globule size as a dependent factor. Data analysis was carried out by Design Expert12 application. Characterization of the optimal formula included physicochemical evaluation, globule size analysis, zeta potential, polydispersity index, entrapment efficiency, Transition Electron Microscopy (TEM) analysis, and FTIR analysis. Result(s): The optimal formula consisted of quercetin: vitamin C: lecithin: cholesterol ratio of 1: 1: 1.046: 0.105 mol;stirring speed 763.986 rpm;stirring time of 59 min, at temperature 51.73 degreeC which produced 59.26 nm average globule size, PDI value 0.66;zeta potential value-35.93+/-0.95 mV and average SPAN value 0.61. This formulation showed entrapment efficiency of quercetin 91.69+/-0.18 % and vitamin C 90.82+/-0.13 %. The TEM and FITR analysis showed the morphological of the globules and interactions between the drugs, soy lecithin, and cholesterol to form nano-phytosomes. Conclusion(s): The conditions to obtain the optimal formula for quercetin vitamin C nano-phytosome consisted of quercetin: vitamin C: lecithin: cholesterol ratio of 1: 1: 1.046: 0.105 mol;stirring speed 763.986 rpm;stirring time of 59 min, and at temperature 51.73 degreeC.Copyright © 2023 The Authors.

Raman and fourier transform infrared spectroscopy techniques for detection of coronavirus (COVID-19): a mini review.

Coronavirus pandemic has been a huge jeopardy to human health in various systems since it outbroke, early detection and prevention of further escalation has become a priority. The current popular approach is to collect samples using the nasopharyngeal swab method and then test for RNA using the real-time polymerase chain reaction, which suffers from false-positive results and a longer diagnostic time scale. Alternatively, various optical techniques, namely, optical sensing, spectroscopy, and imaging shows a great promise in virus detection. In this mini review, we briefly summarize the development progress of vibrational spectroscopy techniques and its applications in the detection of SARS-CoV family. Vibrational spectroscopy techniques such as Raman spectroscopy and infrared spectroscopy received increasing appreciation in bio-analysis for their speediness, accuracy and cost-effectiveness in detection of SARS-CoV. Further, an account of emerging photonics technologies of SARS-CoV-2 detection and future possibilities is also explained. The progress in the field of vibrational spectroscopy techniques for virus detection unambiguously show a great promise in the development of rapid photonics-based devices for COVID-19 detection.

Zn2+ and Cu2+ Interaction with the Recognition Interface of ACE2 for SARS-CoV-2 Spike Protein.

The spike protein (S) of SARS-CoV-2 is able to bind to the human angiotensin-converting enzyme 2 (ACE2) receptor with a much higher affinity compared to other coronaviruses. The binding interface between the ACE2 receptor and the spike protein plays a critical role in the entry mechanism of the SARS-CoV-2 virus. There are specific amino acids involved in the interaction between the S protein and the ACE2 receptor. This specificity is critical for the virus to establish a systemic infection and cause COVID-19 disease. In the ACE2 receptor, the largest number of amino acids playing a crucial role in the mechanism of interaction and recognition with the S protein is located in the C-terminal part, which represents the main binding region between ACE2 and S. This fragment is abundant in coordination residues such as aspartates, glutamates, and histidine that could be targeted by metal ions. Zn2+ ions bind to the ACE2 receptor in its catalytic site and modulate its activity, but it could also contribute to the structural stability of the entire protein. The ability of the human ACE2 receptor to coordinate metal ions, such as Zn2+, in the same region where it binds to the S protein could have a crucial impact on the mechanism of recognition and interaction of ACE2-S, with consequences on their binding affinity that deserve to be investigated. To test this possibility, this study aims to characterize the coordination ability of Zn2+, and also Cu2+ for comparison, with selected peptide models of the ACE2 binding interface using spectroscopic and potentiometric techniques.

Impedimetric Sensing: An Emerging Tool for Combating the COVID-19 Pandemic.

The COVID-19 pandemic revealed a pressing need for the development of sensitive and low-cost point-of-care sensors for disease diagnosis. The current standard of care for COVID-19 is quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). This method is sensitive, but takes time, effort, and requires specialized equipment and reagents to be performed correctly. This make it unsuitable for widespread, rapid testing and causes poor individual and policy decision-making. Rapid antigen tests (RATs) are a widely used alternative that provide results quickly but have low sensitivity and are prone to false negatives, particularly in cases with lower viral burden. Electrochemical sensors have shown much promise in filling this technology gap, and impedance spectroscopy specifically has exciting potential in rapid screening of COVID-19. Due to the data-rich nature of impedance measurements performed at different frequencies, this method lends itself to machine-leaning (ML) algorithms for further data processing. This review summarizes the current state of impedance spectroscopy-based point-of-care sensors for the detection of the SARS-CoV-2 virus. This article also suggests future directions to address the technology's current limitations to move forward in this current pandemic and prepare for future outbreaks.

Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy.

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the protein/receptor interaction mainly depends on the spike's conformation, particularly on its S1 unit, their secondary structures are poorly known. In this paper, the S1 conformation was investigated for MERS-CoV, SARS-CoV, and SARS-CoV-2 at serological pH by measuring their Amide I infrared absorption bands. The SARS-CoV-2 S1 secondary structure revealed a strong difference compared to those of MERS-CoV and SARS-CoV, with a significant presence of extended ß-sheets. Furthermore, the conformation of the SARS-CoV-2 S1 showed a significant change by moving from serological pH to mild acidic and alkaline pH conditions. Both results suggest the capability of infrared spectroscopy to follow the secondary structure adaptation of the SARS-CoV-2 S1 to different environments.

SERS Signature of SARS-CoV-2 in Saliva and Nasopharyngeal Swabs: Towards Perspective COVID-19 Point-of-Care Diagnostics.

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(-) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value-RMSEC and RMSECV below 0.3 and R2cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease.

Recent progress in online detection methods of bioaerosols

The aerosol transmission of coronavirus disease in 2019, along with the spread of other respiratory diseases, caused significant loss of life and property;it impressed upon us the importance of real-time bioaerosol detection. The complexity, diversity, and large spatiotemporal variability of bioaerosols and their external/internal mixing with abiotic components pose challenges for effective online bioaerosol monitoring. Traditional methods focus on directly capturing bioaerosols before subsequent time-consuming laboratory analysis such as culture-based methods, preventing the high-resolution time-based characteristics necessary for an online approach. Through a comprehensive literature assessment, this review highlights and discusses the most commonly used real-time bioaerosol monitoring techniques and the associated commercially available monitors. Methods applied in online bioaerosol monitoring, including adenosine triphosphate bioluminescence, laser/light-induced fluorescence spectroscopy, Raman spectroscopy, and bioaerosol mass spectrometry are summarized. The working principles, characteristics, sensitivities, and efficiencies of these real-time detection methods are compared to understand their responses to known particle types and to contrast their differences. Approaches developed to analyze the substantial data sets obtained by these instruments and to overcome the limitations of current real-time bioaerosol monitoring technologies are also introduced. Finally, an outlook is proposed for future instrumentation indicating a need for highly revolutionized bioaerosol detection technologies.

Investigation on the binding behavior of human α1-acid glycoprotein with Janus Kinase inhibitor baricitinib: Multi-spectroscopic and molecular simulation methodologies.

Baricitinib is a Janus Kinase (JAK) inhibitor that is primarily used to treat moderately to severely active rheumatoid arthritis in adults and has recently been reported for the treatment of patients with severe COVID-19. This paper describes the investigation of the binding behavior of baricitinib to human α1-acid glycoprotein (HAG) employing a variety of spectroscopic techniques, molecular docking and dynamics simulations. Baricitinib can quench the fluorescence from amino acids in HAG through a mix of dynamic and static quenching, according to steady-state fluorescence and UV spectra observations, but it is mainly static quenching at low concentration. The binding constant (Kb) of baricitinib to HAG at 298 K was at the level of 104 M-1, indicating a moderate affinity of baricitinib to HAG. Hydrogen bonding and hydrophobic interactions conducted the main effect, according to thermodynamic characteristics, competition studies between ANS and sucrose, and molecular dynamics simulations. For the change in HAG conformation, the results of multiple spectra showed that baricitinib was able to alter the secondary structure of HAG as well as increase the polarity of the microenvironment around the Trp amino acid. Furthermore, the binding behavior of baricitinib to HAG was investigated by molecular docking and molecular dynamics simulations, which validated experimental results. Also explored is the influence of K+, Co2+, Ni2+, Ca2+, Fe3+, Zn2+, Mg2+ and Cu2+plasma on binding affinity.

Sensitive Detection of SARS-CoV-2 Spike Protein based on Electrochemical Impedance Spectroscopy of Fe3O4@SiO2-Au/GCE Biosensor

Highly contagious COVID-19 disease is caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which poses a serious threat to global public health. Therefore, the development of a fast and reliable method for the detection of SARS-CoV-2 is an urgent research need. The Fe3O4@SiO2-Au is enriched with a variety of functional groups, which can be used to fabricate a sensitive electrochemical biosensor by biofunctionalization with angiotensin-converting enzyme 2 (ACE2). Accordingly, we developed a novel electrochemical sensor by chemically modifying a glassy carbon electrode (GCE) with Fe3O4@SiO2-Au nanocomposites (hereafter Fe3O4@SiO2-Au/GCE) for the rapid detection of S-protein spiked SARS-CoV-2 by electrochemical impedance spectroscopy (EIS). The new electrochemical sensor has a low limit detection (viz., 4.78 pg/mL) and a wide linear dynamic range (viz., 0.1 ng/mL to 10 μg/mL) for detecting the EIS response signal of S-protein. The robust Fe3O4@SiO2-Au/GCE biosensor has high selectivity, stability, and reproducibility for the detection of S-protein with good recovery of saliva samples.

Multi-scale sequential feature selection for disease classification using Raman spectroscopy data.

Raman spectroscopy (RS) optical technology promises non-destructive and fast application in medical disease diagnosis in a single step. However, achieving clinically relevant performance levels remains challenging due to the inability to search for significant Raman signals at different scales. Here we propose a multi-scale sequential feature selection method that can capture global sequential features and local peak features for disease classification using RS data. Specifically, we utilize the Long short-term memory network (LSTM) module to extract global sequential features in the Raman spectra, as it can capture long-term dependencies present in the Raman spectral sequences. Meanwhile, the attention mechanism is employed to select local peak features that were ignored before and are the key to distinguishing different diseases. Experimental results on three public and in-house datasets demonstrate the superiority of our model compared with state-of-the-art methods for RS classification. In particular, our model achieves an accuracy of 97.9 ± 0.2% on the COVID-19 dataset, 76.3 ± 0.4% on the H-IV dataset, and 96.8 ± 1.9% on the H-V dataset.

Rapid screening of benzyl dodecyl dimethyl ammonium bromide co-metabolic degrading bacteria based on NIR hyperspectral imaging technology.

As a typical disinfectant, the use of benzyl dodecyl dimethyl ammonium bromide (BDAB) has dramatically increased since the emergence of SARS-CoV-2, posing a threat to environmental balance and human health. Screening BDAB co-metabolic degrading bacteria is required for efficient microbial degradation. Conventional methods for screening co-metabolic degrading bacteria are laborious and time-consuming, especially when the number of strains is large. This study aimed to develop a novel method for the rapid screening of BDAB co-metabolic degrading bacteria from the cultured solid medium using near-infrared hyperspectral imaging (NIR-HSI) technology. Based on NIR spectra, the concentration of BDAB in the solid medium can be well predicted by partial least squares regression (PLSR) models, non-destructively and rapidly, with Rc2 > 0.872 and Rcv2 > 0.870. The results show that the predicted BDAB concentrations decrease after degrading bacteria utilization, comparing with the regions where no degrading bacteria grew. The proposed method was applied to directly identify the BDAB co-metabolic degrading bacteria cultured on the solid medium, and two kinds of co-metabolic degrading bacteria RQR-1 and BDAB-1 were correctly identified. This method provides a high-efficiency method for screening BDAB co-metabolic degrading bacteria from a large number of bacteria.

Exploring the authentication of COVID-19 vaccines using Surface-enhanced handheld Raman spectroscopy (SERS) equipped with orbital Raster scattering and machine learning

COVID-19 is a novel coronavirus first emerging in Wuhan, China in December 2019 and has since spread rapidly across the globe escalating into a worldwide pandemic causing millions of fatalities. Emergency response to the pandemic included social distancing and isolation measures as well as the escalation of vaccination programmes. The most popular COVID-19 vaccines are nucleic acid-based. The vast spread and struggles in containment of the virus has allowed a gap in the market to emerge for counterfeit vaccines. This study investigates the use of handheld Raman spectroscopy as a method for nucleic acid-based vaccine authentication and utilises machine learning analytics to assess the efficacy of the method. Conventional Raman spectroscopy requires a large workspace, is cumbersome and energy consuming, and handheld Raman systems show limitations with regards to sensitivity and sample detection. Surface Enhanced Raman spectroscopy (SERS) however, shows potential as an authentication technique for vaccines, allowing identification of characteristic nucleic acid bands in spectra. SERS showed strong identification potential through Correlation in Wavelength Space (CWS) with all vaccine samples obtaining an r value of approximately 1 when plotted against themselves. Variance was observed between some excipients and a selected number of DNA-based vaccines, possibly attributed to the stability of the SERS colloid where the colloid-vaccine complex had been measured over different time intervals. Further development of the technique would include optimisation of the SERS method, stability studies and more comprehensive analysis and interpretation of a greater sample size. © 2023 IEEE.

Salivary Analysis for Evidence based Ayurvedic Diagnosis

Ayurveda is called Mother of all medical sciences. It's the oldest therapeutic and medicinal treatment invented in ancient India. Ayurveda or Ayurvedic treatment is bit different from modern medical science. It believes in Nadi Pariksha and many subjective parameters are included to start diagnosis of disease. Whereas modern medical science has different approach of disease diagnosis. It utilizes different tools and testing to diagnose a disease effectively. Saliva analysis is already accepted in modern medical as an important bio-substance, as we see in COVID-19, but not in ayurveda. This paper shows how salivary analysis can act as an evidential proof for diagnosing a disease, in the ayurvedic way. The salivary contents can be analyzed use various biosensors. One of these is Surface Enhanced Raman Spectroscopy (SERS) platform. It allows molecular detection in bio fluids like saliva, sweat, urine, etc. The saliva analysis using SERS technique will help to detect various trace level molecules which is likely to assist the Ayurvedic diagnosis more accurately and dependency on subjective parameters will reduce to evaluate patient's condition. © 2023 IEEE.

Brain hypoxia, neurocognitive impairment, and quality of life in people post-COVID-19.

OBJECTIVE: Systemic hypoxia occurs in COVID-19 infection; however, it is unknown if cerebral hypoxia occurs in convalescent individuals. We have evidence from other conditions associated with central nervous system inflammation that hypoxia may occur in the brain. If so, hypoxia could reduce the quality of life and brain function. This study was undertaken to assess if brain hypoxia occurs in individuals after recovery from acute COVID-19 infection and if this hypoxia is associated with neurocognitive impairment and reduced quality of life. METHODS: Using frequency-domain near-infrared spectroscopy (fdNIRS), we measured cerebral tissue oxygen saturation (StO2) (a measure of hypoxia) in participants who had contracted COVID-19 at least 8 weeks prior to the study visit and healthy controls. We also conducted neuropsychological assessments and health-related quality of life assessments, fatigue, and depression. RESULTS: Fifty-six percent of the post-COVID-19 participants self-reported having persistent symptoms (from a list of 18), with the most reported symptom being fatigue and brain fog. There was a gradation in the decrease of oxyhemoglobin between controls, and normoxic and hypoxic post-COVID-19 groups (31.7 ± 8.3 µM, 27.8 ± 7.0 µM and 21.1 ± 7.2 µM, respectively, p = 0.028, p = 0.005, and p = 0.081). We detected that 24% of convalescent individuals' post-COVID-19 infection had reduced StO2 in the brain and that this relates to reduced neurological function and quality of life. INTERPRETATION: We believe that the hypoxia reported here will have health consequences for these individuals, and this is reflected in the correlation of hypoxia with greater symptomology. With the fdNIRS technology, combined with neuropsychological assessment, we may be able to identify individuals at risk of hypoxia-related symptomology and target individuals that are likely to respond to treatments aimed at improving cerebral oxygenation.

Preparation of PLA-based SMS nonwoven composites and its applications in protective apparel

The global COVID-19 pandemic has triggered a huge demand for the protective nonwovens. However, the main raw material of nonwovens comes from petroleum, and the massive consumption of petroleum-based polymers brings great pressure to ecosystem. Therefore, it is significant to develop biodegradable protective barrier products. In this work, a polylactic-based composite (a tri-layer nonwovens composed of spunbond, meltblown and spunbond, SMS) was prepared and applied for protective apparel. The surface morphology and chemical changes of the fibers were characterized and analyzed by scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR) and energy dispersive spectroscopy (EDS). The liquid contact angle and permeability, breathability and moisture permeability, frictional charge and mechanical strength of the samples were evaluated and compared. The samples degradability was also recorded. The results demonstrate that the optimum formula for anti-fouling treatment on SMS is F-30. The treated fabric possesses superior liquid repellency and anti-permeability, with contact angles of water and alcohol at 128° and 115° respectively, while the alcohol repellent grade reaches level 7. The treated sample has less strength loss but exhibits favorable breathability, moisture permeability and anti-static properties, which can meet the requirements of protective apparels. After fluorine resin coating, the composite still provide excellent degradation performance, and the weight loss rate reaches more than 80% after 10 days water degradation. These results provide new insights for the application of PLA-based SMS in biodegradable protective apparel. © 2023 The Textile Institute.