Immunomodulatory activity of polycaprolactone nanoparticles with calcium phosphate salts against Leishmania infantum infection

Objective:To prepare and characterize polycaprolactone(PCL)nanoparticles loaded with sonicator fragmented(SLA)and freeze-thaw Leishmania antigens(FTLA)and to investigate the in vitro immunogenicity of antigen-encapsulated nanoparticles with calcium phosphate adjuvant.Methods:The water/oil/water binary emulsion solvent evaporation method was used to synthesize antigen-loaded PCL nanoparticles.Particles were characterized by scanning electron microscopy and zeta potential measurements.Their cytotoxicity in J774 macrophages in vitro was determined by MTT analysis.In addition,the amount of nitric oxide and the level of cytokines produced by macrophages were determined by Griess reaction and ELISA method,respectively.The protective effect of the developed formulations was evaluated by determining the infection index percentage in macrophages infected with Leishmania infantum.Results:Compared to the control group,SLA PCL and FTLA PCL nanoparticles with calcium phosphate adjuvant induced a 6-and 7-fold increase in nitric oxide,respectively.Additionally,the vaccine formulations promoted the production of IFN-γand IL-12.SLA PCL and FTLA PCL nanoparticles combined with calcium phosphate adjuvant caused an approximately 13-and 11-fold reduction in infection index,respectively,compared to the control group.Conclusions:The encapsulation of antigens obtained by both sonication and freeze-thawing into PCL nanoparticles and the formulations with calcium phosphate adjuvant show strong in vitro immune stimulating properties.Therefore,PCL-based antigen delivery systems and calcium phosphate adjuvant are recommended as a potential vaccine candidate against leishmaniasis.

Development of an experimental method for well-controlled blast induced traumatic limb fracture in rats

Heterotopic ossification(HO)is a consequence of traumatic bone and tissue damage,which occurs in 65%of military casualties with blast-associated amputations.However,the mechanisms behind blast-induced HO remain unclear.Animal models are used to study blast-induced HO,but developing such models is challenging,particularly in how to use a pure blast wave(primary blast)to induce limb fracture that then requires an amputation.Several studies,including our recent study,have developed platforms to induce limb fractures in rats with blast loading or a mixture of blast and impact loading.However,these models are limited by the survivability of the animal and repeatability of the model.In this study,we developed an improved platform,aiming to improve the animal's survivability and injury repeatability as well as focusing on primary blast only.The platform exposed only one limb of the rat to a blast wave while providing proper protection to the rest of the rat's body.We obtained very consistent fracture outcome in the tibia(location and pattern)in cadaveric rats with a large range of size and weight.Importantly,the rats did not obviously move during the test,where movement is a potential cause of uncontrolled injury.We further conducted parametric studies by varying the features of the design of the platform.These factors,such as how the limb is fixed and how the cavity through which the limb is placed is sealed,significantly affect the resulting injury.This platform and test setups enable well-controlled limb fracture induced directly by pure blast wave,which is the fundamental step towards a complete in vivo animal model for blast-induced HO induced by primary blast alone,excluding secondary and tertiary blast injury.In addition,the platform design and the findings presented here,particularly regarding the proper protection of the animal,have implications for future studies investigating localized blast injuries,such as blast induced brain and lung injuries.

Unleashing the Potential of Electroactive Hybrid Biomaterials and Self‑Powered Systems for Bone Therapeutics

The incidence of large bone defects caused by traumatic injury is increasing worldwide,and the tissue regeneration process requires a long recovery time due to limited self-healing capability.Endogenous bioelectrical phenomena have been well recognized as critical biophysical factors in bone remodeling and regeneration.Inspired by bioelectricity,electrical stimulation has been widely considered an external intervention to induce the osteogenic lineage of cells and enhance the synthesis of the extracellular matrix,thereby accelerating bone regeneration.With ongoing advances in biomaterials and energy-harvesting techniques,electroactive biomaterials and self-powered systems have been considered biomimetic approaches to ensure functional recovery by recapitulating the natural electrophysiological microenvironment of healthy bone tissue.In this review,we first introduce the role of bioelectricity and the endogenous electric field in bone tissue and summarize different techniques to electrically stimulate cells and tissue.Next,we highlight the latest progress in exploring electroactive hybrid biomaterials as well as self-powered systems such as triboelectric and piezoelectric-based nanogenerators and photovoltaic cell-based devices and their implementation in bone tissue engineering.Finally,we emphasize the significance of simulating the target tissue’s electrophysiological microenvironment and propose the opportunities and challenges faced by electroactive hybrid biomaterials and self-powered bioelectronics for bone repair strategies.

Origin and evolution of a new tetraploid mangrove species in an intertidal zone

Polyploidy is a major factor in the evolution of plants,yet we know little about the origin and evolution of polyploidy in intertidal species.This study aimed to identify the evolutionary transitions in three truemangrove species of the genus Acanthus distributed in the Indo-West Pacific region.For this purpose,we took an integrative approach that combined data on morphology,cytology,climatic niche,phylogeny,and biogeography of 493 samples from 42 geographic sites.Our results show that the Acanthus ilicifolius lineage distributed east of the Thai-Malay Peninsula possesses a tetraploid karyotype,which is morphologically distinct from that of the lineage on the west side.The haplotype networks and phylogenetic trees for the chloroplast genome and eight nuclear genes reveal that the tetraploid species has two sub-genomes,one each from A.ilicifolius and A.ebracteatus,the paternal and maternal parents,respectively.Population structure analysis also supports the hybrid speciation history of the new tetraploid species.The two sub-genomes of the tetraploid species diverged from their diploid progenitors during the Pleistocene.Environmental niche models revealed that the tetraploid species not only occupied the near-entire niche space of the diploids,but also expanded into novel environments.Our findings suggest that A.ilicifolius species distributed on the east side of the Thai-Malay Peninsula should be regarded as a new species,A.tetraploideus,which originated from hybridization between A.ilicifolius and A.ebracteatus,followed by chromosome doubling.This is the first report of a true-mangrove allopolyploid species that can reproduce sexually and clonally reproduction,which explains the long-term adaptive potential of the species.

Abnormal function of EPHA2/p.R957P mutant in congenital cataract

AIM:To identify genetic defects in a Chinese family with congenital posterior polar cataracts and assess the pathogenicity.METHODS:A four-generation Chinese family affected with autosomal dominant congenital cataract was recruited.Nineteen individuals took part in this study including 5 affected and 14 unaffected individuals.Sanger sequencing targeted hot-spot regions of 27 congenital cataract-causing genes for variant discovery.The pathogenicity of the variant was evaluated by the guidelines of American College of Medical Genetics and InterVar software.Confocal microscopy was applied to detect the subcellular localization of fluorescence-labeled ephrin type-A receptor 2(EPHA2).Co-immunoprecipitation assay was implemented to estimate the interaction between EphA2 and other lens membrane proteins.The mRNA and protein expression were analyzed by reverse transcription-polymerase chain reaction(qRT-PCR)and Western blotting assay,respectively.The cell migration was analyzed by wound healing assay.Zebrafish model was generated by ectopic expression of human EPHA2/p.R957P mutant to demonstrate whether the mutant could cause lens opacity in vivo.RESULTS:A novel missense and pathogenic variant c.2870G>C was identified in the sterile alpha motif(SAM)domain of EPHA2.Functional studies demonstrated the variant’s impact:reduced EPHA2 protein expression,altered subcellular localization,and disrupted interactions with other lens membrane proteins.This mutant notably enhanced human lens epithelial cell migration,and induced a central cloudy region and roughness in zebrafish lenses with ectopic expression of human EPHA2/p.R957P mutant under differential interference contrast(DIC)optics.CONCLUSION:Novel pathogenic c.2870G>C variant of EPHA2 in a Chinese congenital cataract family contributes to disease pathogenesis.

Pathogenesis and research progress of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

In this editorial,we comment on the article by Mei et al.Nonalcoholic steatohep-atitis(NASH)is a severe inflammatory subtype of nonalcoholic fatty liver disease(NAFLD)with pathological features including steatosis,hepatocellular damage,and varying degrees of fibrosis.With the epidemic of metabolic diseases and obesity,the prevalence of NAFLD in China has increased,and it is now similar to that in developed countries;thus,NAFLD has become a major chronic liver disease in China.Human epidemiological data suggest that estrogen has a protective effect on NASH in premenopausal women and that sex hormones influence the development of liver disease.This review focuses on the path-ogenesis,treatment,and relationship between NASH and other diseases as well as on the relationship between NASH and sex hormone metabolism,with the aim of providing new strategies for the treatment of NASH.

Long-term impact of artificial intelligence on colorectal adenoma detection in high-risk colonoscopy

BACKGROUND Improved adenoma detection rate(ADR)has been demonstrated with artificial intelligence(AI)-assisted colonoscopy.However,data on the real-world appli-cation of AI and its effect on colorectal cancer(CRC)screening outcomes is limited.AIM To analyze the long-term impact of AI on a diverse at-risk patient population undergoing diagnostic colonoscopy for positive CRC screening tests or sympt-oms.METHODS AI software(GI Genius,Medtronic)was implemented into the standard proced-ure protocol in November 2022.Data was collected on patient demographics,procedure indication,polyp size,location,and pathology.CRC screening outcomes were evaluated before and at different intervals after AI introduction with one year of follow-up.RESULTS We evaluated 1008 colonoscopies(278 pre-AI,255 early post-AI,285 established post-AI,and 190 late post-AI).The ADR was 38.1%pre-AI,42.0%early post-AI(P=0.77),40.0%established post-AI(P=0.44),and 39.5%late post-AI(P=0.77).There were no significant differences in polyp detection rate(PDR,baseline 59.7%),advanced ADR(baseline 16.2%),and non-neoplastic PDR(baseline 30.0%)before and after AI introduction.CONCLUSION In patients with an increased pre-test probability of having an abnormal colonoscopy,the current generation of AI did not yield enhanced CRC screening metrics over high-quality colonoscopy.Although the potential of AI in colonoscopy is undisputed,current AI technology may not universally elevate screening metrics across all situations and patient populations.Future studies that analyze different AI systems across various patient populations are needed to determine the most effective role of AI in optimizing CRC screening in clinical practice.

Analysis of a New Toothbrushing Technique through Plaque Removal Success

Background/Aims: Determining the levels of oral health and the quality of dental care are fundamental to building concepts of oral health. This study aims to assess toothbrushing techniques using a technical and physical model, clarifying how children and pre-adults learn to brush their teeth. Materials and Methods: Data were recorded from 23 participants, both male and female of various ages, using a proposed electronic toothbrush equipped with X-Y-Z axes pathways. The data, collected before and after training experiments, were processed with MATLAB to generate plots for the three axes. Results: The study revealed that most parameter values, such as Mean Difference Between Amplitudes (MAV, 6.00), Wilson Amplitude (WAMP, 179.419), and Average Amplitude Coupling (AAC, 1.270), decreased from before to after the experiments. Furthermore, the average overall epoch lengths (AVG) showed a 75% reduction in movement amplitude between the two experiments. Conclusion: Dentist observations indicated which brushing methods were acceptable or not. Analytical values suggest that individuals learn the toothbrushing technique effectively, and medical observations clearly demonstrate the success of the proposed method.

Feasibility of Plug Production Utilizing Digestate from Home-Waste to Energy Systems (H-WEF)

The integration of sustainable technologies in waste management systems has become imperative in addressing the escalating challenges of agricultural productivity and sustainability. Plugs are essential when starting crop production in controlled environment agriculture (CEA) setups and greenhouses. Horticultural crops such as vegetables, fruiting, and ornamental plants that utilize plugs have demonstrated higher success rates, healthier plants, and higher total yields. The APS Laboratory for Sustainable Agriculture explored the innovative utilization of digestate from the Home Water-Energy-Food Systems (H-WEF). The H-WEF system converts household food waste into biogas, electricity, and nutrient-rich digestate. The digestate from the H-WEF system was used to produce agricultural plugs, presenting a novel approach to circular resource utilization. We carried out the growth of Rex Butterhead Lettuce Latuca sativa plugs with 1) control system (synthetic fertilizer) and seven different treatments, 2) 5% Digestate—95% RO Water (5D–95RO);3) 10% Digestate—90% RO Water (10D–90RO);4) 15% Digestate—85% RO Water (15D–85RO);5) 20% Digestate—80% RO Water (20D–80RO);6) 25% Digestate—75% RO Water (25D–75RO);7) 30% Digestate—70% RO Water (30D–70RO);8) 35% Digestate—65% RO Water (35D–65RO). The plugs were cultivated for 15 days in a controlled environment until two leaves had developed after the cotyledon. After 15 days, we collected data on wet weight (g), plug head area (cm2), total leaf area (cm2), total chlorophyll content (mg/cm2), and dry weight (g). In addition, we collected data on the Leaf Area Index (LAI, cm2/cm2) and Specific Leaf Area (SLA, cm2/g). The synthetic fertigation yielded a higher wet weight than the following treatments: 5D–95RO, 10D–90RO, and 35D–65RO. While the 30D–70RO treatment produced a larger plug head than all other treatments. The digestate-based fertilizers were comparable to the synthetic fertilizer at dilutions of 25D–75RO and 30D–70RO. This study underscores the viability of using digestate for plug production, providing crucial insights for growers navigating the challenges of sustainable agricultural practices.

Mechanotransduction pathways in articular chondrocytes and the emerging role of estrogen receptor-α

In the synovial joint,mechanical force creates an important signal that influences chondrocyte behavior.The conversion of mechanical signals into biochemical cues relies on different elements in mechanotransduction pathways and culminates in changes in chondrocyte phenotype and extracellular matrix composition/structure.Recently,several mechanosensors,the first responders to mechanical force,have been discovered.However,we still have limited knowledge about the downstream molecules that enact alterations in the gene expression profile during mechanotransduction signaling.Recently,estrogen receptorα(ERα)has been shown to modulate the chondrocyte response to mechanical loading through a ligand-independent mechanism,in line with previous research showing that ERαexerts important mechanotransduction effects on other cell types,such as osteoblasts.In consideration of these recent discoveries,the goal of this review is to position ERαinto the mechanotransduction pathways known to date.Specifically,we first summarize our most recent understanding of the mechanotransduction pathways in chondrocytes on the basis of three categories of actors,namely mechanosensors,mechanotransducers,and mechanoimpactors.Then,the specific roles played by ERαin mediating the chondrocyte response to mechanical loading are discussed,and the potential interactions of ERαwith other molecules in mechanotransduction pathways are explored.Finally,we propose several future research directions that may advance our understanding of the roles played by ERαin mediating biomechanical cues under physiological and pathological conditions.

Noninvasive Characterization of Metabolic Changes in Ischemic Stroke Using Z-spectrum-fitted Multiparametric Chemical Exchange Saturation Transfer-weighted Magnetic Resonance Imaging

Objective This study aimed to noninvasively characterize the metabolic alterations in ischemic brain tissues using Z-spectrum-fitted multiparametric chemical exchange saturation transfer-weighted magnetic resonance imaging(CEST-MRI).Methods Three sets of Z-spectrum data with saturation power(B_(1))values of 1.5,2.5,and 3.5µT,respectively,were acquired from 17 patients with ischemic stroke.Multiple contrasts contributing to the Z-spectrum,including fitted amide proton transfer(APT_(fitted)),+2 ppm peak(CEST@2ppm),concomitantly fitted APT_(fitted) and CEST@2ppm(APT&CEST@2ppm),semisolid magnetization transfer contrast(MT),aliphatic nuclear Overhauser effect(NOE),and direct saturation of water(DSW),were fitted with 4 and 5 Lorentzian functions,respectively.The CEST metrics were compared between ischemic lesions and contralateral normal white matter(CNWM),and the correlation between the CEST metrics and the apparent diffusion coefficient(ADC)was assessed.The differences in the Z-spectrum metrics under varied B1 values were also investigated.Results Ischemic lesions showed increased APTfitted,CEST@2ppm,APT&CEST@2ppm,NOE,and DSW as well as decreased MT.APT&CEST@2ppm,MT,and DSW showed a significant correlation with ADC[APT&CEST@2ppm at the 3 B_(1) values:R=0.584/0.467/0.551;MT at the 3 B_(1) values:R=−0.717/−0.695/−0.762(4-parameter fitting),R=−0.734/−0.711/−0.785(5-parameter fitting);DSW of 4-/5-parameter fitting:R=0.794/0.811(2.5µT),R=0.800/0.790(3.5µT)].However,the asymmetric analysis of amide proton transfer(APT_(asym))could not differentiate the lesions from CNWM and showed no correlation with ADC.Furthermore,the Z-spectrum contrasts varied with B_(1).Conclusion The Z-spectrum-fitted multiparametric CEST-MRI can comprehensively detect metabolic alterations in ischemic brain tissues.

BME 2.0: Engineering the Future of Medicine

If the 20th century was the age of mapping and controlling the external world,the 21st century is the biomedical age of mapping and controlling the biological internal world.The biomedical age is bringing new technological breakthroughs for sensing and controlling human biomolecules,cells,tissues,and organs,which underpin new frontiers in the biomedical discovery,data,biomanufacturing,and translational sciences.This article reviews what we believe will be the next wave of biomedical engineering(BME)education in support of the biomedical age,what we have termed BME 2.0.BME 2.0 was announced on October 122017 at BMES 49(https://www.bme.jhu.edu/news-events/news/miller-opens-2017-bmes-annual-meeting-with-vision-for-new-bme-era/).We present several principles upon which we believe the BME 2.0 curriculum should be constructed,and from these principles,we describe what view as the foundations that form the next generations of curricula in support of the BME enterprise.The core principles of BME 2.0 education are(a)educate students bilingually,from day 1,in the languages of modern molecular biology and the analytical modeling of complex biological systems;(b)prepare every student to be a biomedical data scientist;(c)build a unique BME community for discovery and innovation via a vertically integrated and convergent learning environment spanning the university and hospital systems;(d)champion an educational culture of inclusive excellence;and(e)codify in the curriculum ongoing discoveries at the frontiers of the discipline,thus ensuring BME 2.0 as a launchpad for training the future leaders of the biotechnology marketplaces.We envision that the BME 2.0 education is the path for providing every student with the training to lead in this new era of engineering the future of medicine in the 21st century.

Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics

Background:Traumatic brain injury can be caused by head impacts,but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo,and the characteristics of different types of impacts are not well studied.We investigated the spectral characteristics of different head impact types with kinematics classification.Methods:Data were analyzed from 3262 head impacts from lab reconstruction,American football,mixed martial arts,and publicly available car crash data.A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify head impact types(e.g.,football,car crash,mixed martial arts).To test the classifier robustness,another 271 lab-reconstructed impacts were obtained from 5 other instrumented mouthguards.Finally,with the classifier,type-specific,nearest-neighbor regression models were built for brain strain.Results:The classifier reached a median accuracy of 96% over 1000 random partitions of training and test sets.The most important features in the classification included both low-and high-frequency features,both linear acceleration features and angular velocity features.Different head impact types had different distributions of spectral densities in low-and high-frequency ranges(e.g.,the spectral densities of mixed martial arts impacts were higher in the high-frequency range than in the low-frequency range).The type-specific regression showed a generally higher R2value than baseline models without classification.Conclusion:The machine-learning-based classifier enables a better understanding of the impact kinematics spectral density in different sports,and it can be applied to evaluate the quality of impact-simulation systems and on-field data augmentation.

Advances in In Vitro and In Vivo Bioreactor-Based Bone Generation for Craniofacial Tissue Engineering

Craniofacial reconstruction requires robust bone of specified geometry for the repair to be both functional and aesthetic.While native bone from elsewhere in the body can be harvested,shaped,and implanted within a defect,using either an in vitro or in vivo bioreactors eliminates donor site morbidity while increasing the customizability of the generated tissue.In vitro bioreactors utilize cells harvested from the patient,a scaffold,and a device to increase mass transfer of nutrients,oxygen,and waste,allowing for generation of larger viable tissues.In vivo bioreactors utilize the patient’s own body as a source of cells and of nutrient transfer and involve the implantation of a scaffold with or without growth factors adjacent to vasculature,followed by the eventual transfer of vascularized,mineralized tissue to the defect site.Several different models of in vitro bioreactors exist,and several different implantation sites have been successfully utilized for in vivo tissue generation and defect repair in humans.In this review,we discuss the specifics of each bioreactor strategy,as well as the advantages and disadvantages of each and the future directions for the engineering of bony tissues for craniofacial defect repair.

Corrigendum to “Advances in In Vitro and In Vivo Bioreactor-Based Bone Generation for Craniofacial Tissue Engineering”

In the review article“Advances in In Vitro and In Vivo Bioreactor-Based Bone Generation for Craniofacial Tissue Engineering,”the authors made an error in Table.In Table,10 cells in the Results column contain the word“enter,”which was erroneously added instead of starting a new line of text during proofing.This error did not affect the results,discussion,or conclusion of this paper.Table 1 has now been corrected in the PDF and HTML(full text).

Introduction to the special issue on polarization of light in biomedical applications

Although birefringence was discovered just three years after white light was separated into different colors,polarimetry has lagged behind spectroscopy in characterizing diverse materials,likely due to our naked eyes'limited sensitivity to polarizations.Recent advancements in light sources,polarization optics,detectors,displays,data processing,and feature extraction techniques are rapidly propelling polarimetry as a convenient and potent tool for probing the distinct properties of complex and turbid materials.It is well known now that polarization properties of a material encode rich information on its distinct features,including not only the bulk optical properties related with dispersions and absorptions,but also distribution and microstructural properties of the scattering particles in turbid media such as the size,shape,orientation and alignment,surface morphology and internal structure,etc.All these features can be used for differentiating different materials,sensing ambient environment around scatterers,or monitoring dynamic processes in complex systems.

Comparison of point detection and area detection for point-scanning structured illumination microscopy

Structured illumination microscopy(SIM)is suitable for biological samples because of its relatively low-peak illumination intensity requirement and high imaging speed.The system resolution is affected by two typical detection modes:Point detection and area detection.However,a systematic analysis of the imaging performance of the different detection modes of the system has rarely been conducted.In this study,we compared laser point scanning point detection(PS-PD)and point scanning area detection(PS-AD)imaging in nonconfocal microscopy through theoretical analysis and simulated imaging.The results revealed that the imaging resolutions of PSPD and PS-AD depend on excitation and emission point spread functions(PSFs),respectively.Especially,we combined the second harmonic generation(SHG)of point detection(P-SHG)and area detection(A-SHG)with SIM to realize a nonlinear SIM-imaging technique that improves the imaging resolution.Moreover,we analytically and experimentally compared the nonlinear SIM performance of P-SHG with that of A-SHG.

Numerical Modeling and Computer Simulation of a Meander Line Antenna for Alzheimer’s Disease Treatment, a Feasibility Study

Alzheimer’s disease (AD) is a brain disorder that eventually causes memory loss and the ability to perform simple cognitive functions;research efforts within pharmaceuticals and other medical treatments have minimal impact on the disease. Our preliminary biological studies showed that Repeated Electromagnetic Field Stimulation (REFMS) applying an EM frequency of 64 MHz and a specific absorption rate (SAR) of 0.4 - 0.9 W/kg decrease the level of amyloid-β peptides (Aβ), which is the most likely etiology of AD. This study emphasizes uniform E/H field and SAR distribution with adequate penetration depth penetration through multiple human head layers driven with low input power for safety treatments. In this work, we performed numerical modeling and computer simulations of a portable Meander Line antenna (MLA) to achieve the required EMF parameters to treat AD. The MLA device features a low cost, small size, wide bandwidth, and the ability to integrate into a portable system. This study utilized a High-Frequency Simulation System (HFSS) in the design of the MLA with the desired characteristics suited for AD treatment in humans. The team designed a 24-turn antenna with a 60 cm length and 25 cm width and achieved the required resonant frequency of 64 MHz. Here we used two numerical human head phantoms to test the antenna, the MIDA and spherical head phantom with six and seven tissue layers, respectively. The antenna was fed from a 50-Watt input source to obtain the SAR of 0.6 W/kg requirement in the center of the simulated brain tissue layer. We found that the E/H field and SAR distribution produced was not homogeneous;there were areas of high SAR values close to the antenna transmitter, also areas of low SAR value far away from the antenna. This paper details the antenna parameters, the scattering parameters response, the efficiency response, and the E and H field distribution;we presented the computer simulation results and discussed future work for a practical model.

Erratum to “BME 2.0: Engineering the Future of Medicine”

In the article“BME 2.0:Engineering the Future of Medicine”[1],the competing interests statement was inadvertently omitted by the publisher from the published version of the article.This has now been corrected in the PDF and HTML(full text).

State-of-the-art and future directions of machine learning for biomass characterization and for sustainable biorefinery

Machine learning(ML)has emerged as a significant tool in the field of biorefinery,offering the capability to analyze and predict complex processes with efficiency.This article reviews the current state of biorefinery and its classification,highlighting various commercially successful biorefineries.Further,we delve into different categories of ML models,including their algorithms and applications in various stages of biorefinery lifecycle,such as biomass characterization,pretreatment,lignin valorization,chemical,thermochemical and biochemical conversion processes,supply chain analysis,and life cycle assessment.The benefits and limitations of each of these algorithms are discussed in detail.Finally,the article concludes with a discussion of the limitations and future prospects of ML in the field of biorefineries.