Spanish vs USA cohort comparison of prehospital trauma scores to predict short-term mortality.

BACKGROUND: This study aimed to evaluate three prehospital early warning scores (EWSs): RTS, MGAP and MREMS, to predict short-term mortality in acute life-threatening trauma and injury/illness by comparing United States (US) and Spanish cohorts. METHODS: A total of 8854 patients, 8598/256 survivors/nonsurvivors, comprised the unified cohort. Datasets were randomly divided into training and test sets. Training sets were used to analyze the discriminative power of the scores in terms of the area under the curve (AUC), and the score performance was assessed in the test set in terms of sensitivity (SE), specificity (SP), accuracy (ACC) and balanced accuracy (BAC). RESULTS: The three scores showed great discriminative power with AUCs>0.90, and no significant differences between cohorts were found. In the test set, RTS/MREMS/MGAP showed SE/SP/ACC/BAC values of 86.0/89.9/89.6/87.1%, 91.0/86.9/87.5/88.5%, and 87.7/82.9/83.4/85.2%, respectively. CONCLUSIONS: All EWSs showed excellent ability to predict the risk of short-term mortality, independent of the country.

Evaluation of antifungal activity of visible light-activated doped TiO2 nanoparticles.

Titanium dioxide (TiO2) is a well-known material for its biomedical applications, among which its implementation as a photosensitizer in photodynamic therapy has attracted considerable interest due to its photocatalytic properties, biocompatibility, high chemical stability, and low toxicity. However, the photoactivation of TiO2 requires ultraviolet light, which may lead to cell mutation and consequently cancer. To address these challenges, recent research has focused on the incorporation of metal dopants into the TiO2 lattice to shift the band gap to lower energies by introducing allowed energy states within the band gap, thus ensuring the harnessing of visible light. This study presents the synthesis, characterization, and application of TiO2 nanoparticles (NPs) in their undoped, doped, and co-doped forms for antimicrobial photodynamic therapy (APDT) against Candida albicans. Blue light with a wavelength of 450 nm was used, with doses ranging from 20 to 60 J/cm2 and an NP concentration of 500 µg/ml. It was observed that doping TiO2 with Cu, Fe, Ag ions, and co-doping Cu:Fe into the TiO2 nanostructure enhanced the visible light photoactivity of TiO2 NPs. Experimental studies were done to investigate the effects of different ions doped into the TiO2 crystal lattice on their structural, optical, morphological, and chemical composition for APDT applications. In particular, Ag-doped TiO2 emerged as the best candidate, achieving 90-100% eradication of C. albicans.

Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation.

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

Enhancing 3D human pose estimation with NIR single-pixel imaging and time-of-flight technology: a deep learning approach.

The extraction of 3D human pose and body shape details from a single monocular image is a significant challenge in computer vision. Traditional methods use RGB images, but these are constrained by varying lighting and occlusions. However, cutting-edge developments in imaging technologies have introduced new techniques such as single-pixel imaging (SPI) that can surmount these hurdles. In the near-infrared spectrum, SPI demonstrates impressive capabilities in capturing a 3D human pose. This wavelength can penetrate clothing and is less influenced by lighting variations than visible light, thus providing a reliable means to accurately capture body shape and pose data, even in difficult settings. In this work, we explore the use of an SPI camera operating in the NIR with time-of-flight (TOF) at bands 850-1550 nm as a solution to detect humans in nighttime environments. The proposed system uses the vision transformers (ViT) model to detect and extract the characteristic features of humans for integration over a 3D body model SMPL-X through 3D body shape regression using deep learning. To evaluate the efficacy of NIR-SPI 3D image reconstruction, we constructed a laboratory scenario that simulates nighttime conditions, enabling us to test the feasibility of employing NIR-SPI as a vision sensor in outdoor environments. By assessing the results obtained from this setup, we aim to demonstrate the potential of NIR-SPI as an effective tool to detect humans in nighttime scenarios and capture their accurate 3D body pose and shape.

Benznidazole-induced drug reaction with eosinophilia and systemic symptoms syndrome in a patient with human leucocyte antigen (HLA)-A*68.

Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare but severe drug hypersensitivity reaction with potentially life-threatening consequences. It is characterised by fever, extensive maculopapular exanthema, lymph node enlargement, abnormal blood cell counts, and organ-related complications. Diagnosis can be challenging due to incomplete or non-specific symptoms, and it can sometimes manifest as a purely systemic disease. Discontinuation of the causative drug is essential. Treatment may involve corticosteroids and supportive care. Genetic screening for specific markers, such as human leucocyte antigen (HLA)-A*68, A11:01, and A29:02, can help identify individuals at risk for severe reactions to benznidazole, a drug used to treat Chagas disease. This case report describes the rarity and severity of DRESS syndrome, underscoring the potential benefit of genetic screening to prevent adverse reactions in patients with Chagas disease.

Bio-inspired apparatus to produce luminescent cavitation in a rigid walled chamber.

A mechanical device inspired by the rapid rotational motion of the pistol shrimp plunger has been developed to experimentally study the contraction/expansion dynamics of a gas bubble inside a confined liquid volume and in the vicinity of solid surfaces. The apparatus consists of a limb with a V-shaped end, which fits into a socket forming a cylindrical compression chamber. Air bubbles of different sizes and in different positions inside the chamber were seeded to study their shape evolution in liquids when subjected to pressure pulses induced by the limb closure. By changing the standoff and curvature parameters, as well as the closing power of the limb it was possible to control the dynamical behavior of the cavity. Four stages describing the dynamic behavior of the bubble were found: 1) A slight expansion-contraction stage accompanied by very weak volumetric oscillations. 2) First compression stage. The formation of gas and liquid micro-jets is observed when the vertical symmetry axis of the bubble is initially located outside of the chamber symmetry axis, on the other hand, when there is a coincidence between these axes, the bubble only contracts exhibiting non-spherical shapes, alternating between oblate and prolate spheroidal structures. 3) An expansion stage where the cavity reaches the walls of the chamber exhibiting irregular shapes on its surface. 4) Second compression stage. This process begins when the limb rebounds and stops sealing the chamber allowing a jet of liquid to enter from the fluid medium outside, inducing a very violent collapse accompanied by the emission of light. The proposed technique represents a novel alternative to study the dynamic evolution of bubbles near and on solid boundaries of various geometries. Other attractive features of the apparatus are its low manufacturing cost, simple design and compact size which makes it easily portable.

Improved spatial speckle contrast model for tissue blood flow imaging: effects of spatial correlation among neighboring camera pixels.

Significance: Speckle contrast analysis is the basis of laser speckle imaging (LSI), a simple, inexpensive, noninvasive technique used in various fields of medicine and engineering. A common application of LSI is the measurement of tissue blood flow. Accurate measurement of speckle contrast is essential to correctly measure blood flow. Variables, such as speckle grain size and camera pixel size, affect the speckle pattern and thus the speckle contrast. Aim: We studied the effects of spatial correlation among adjacent camera pixels on the resulting speckle contrast values. Approach: We derived a model that accounts for the potential correlation of intensity values in the common experimental situation where the speckle grain size is larger than the camera pixel size. In vitro phantom experiments were performed to test the model. Results: Our spatial correlation model predicts that speckle contrast first increases, then decreases as the speckle grain size increases relative to the pixel size. This decreasing trend opposes what is observed with a standard speckle contrast model that does not consider spatial correlation. Experimental data are in good agreement with the predictions of our spatial correlation model. Conclusions: We present a spatial correlation model that provides a more accurate measurement of speckle contrast, which should lead to improved accuracy in tissue blood flow measurements. The associated correlation factors only need to be calculated once, and open-source software is provided to assist with the calculation.

Cluster headache: state of the art in treatment.

Cluster headache (CH) is the most common and devastating autonomic headache with multiple and recent advances in treatment. However, it usually goes unrecognized and is found to have a delayed and inappropriate treatment. This paper aims to review the current therapeutic options for patients with CH. We conducted a narrative literature review on the treatments available for this condition using the American Academy of Neurology (AAN) classification of therapeutic evidence. We found effective and safe pharmacological and non-pharmacological therapies with heterogeneity of clinical trial designs for patients with CH, and they are divided into three phases, namely, transitional, acute, and preventive interventions. Prednisone (A) is the most studied treatment in the transitional phase; acute attacks are treated using triptans (A), oxygen (A), and non-invasive transcutaneous vagal nerve stimulation (A). Verapamil (A) and monoclonal antibodies (possible A) are considered the first options in preventive treatments, followed by multiple pharmacological and non-pharmacological options in prophylactic treatments. In conclusion, numerous effective and safe treatments are available in treating patients with episodic, chronic, and pharmacoresistant CH according to the clinical profile of each patient.

Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) - protocol for a research collaboration.

Background: Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as 'early onset'). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at different life stages. We have established a research collaboration titled 'MELD-B' to understand how wider determinants, sentinel conditions (the first LTC in the lifecourse) and LTC accrual sequence affect risk of early-onset, burdensome MLTC-M, and to inform prevention interventions. Aim: Our aim is to identify critical periods in the lifecourse for prevention of early-onset, burdensome MLTC-M, identified through the analysis of birth cohorts and electronic health records, including artificial intelligence (AI)-enhanced analyses. Design: We will develop deeper understanding of 'burdensomeness' and 'complexity' through a qualitative evidence synthesis and a consensus study. Using safe data environments for analyses across large, representative routine healthcare datasets and birth cohorts, we will apply AI methods to identify early-onset, burdensome MLTC-M clusters and sentinel conditions, develop semi-supervised learning to match individuals across datasets, identify determinants of burdensome clusters, and model trajectories of LTC and burden accrual. We will characterise early-life (under 18 years) risk factors for early-onset, burdensome MLTC-M and sentinel conditions. Finally, using AI and causal inference modelling, we will model potential 'preventable moments', defined as time periods in the life course where there is an opportunity for intervention on risk factors and early determinants to prevent the development of MLTC-M. Patient and public involvement is integrated throughout.

Deep-learning blurring correction of images obtained from NIR single-pixel imaging.

In challenging scenarios characterized by low-photon conditions or the presence of scattering effects caused by rain, fog, or smoke, conventional silicon-based cameras face limitations in capturing visible images. This often leads to reduced visibility and image contrast. However, using near-infrared (NIR) light within the range of 850-1550 nm offers the advantage of reduced scattering by microparticles, making it an attractive option for imaging in such conditions. Despite NIR's advantages, NIR cameras can be prohibitively expensive. To address this issue, we propose a vision system that leverages NIR active illumination single-pixel imaging (SPI) operating at 1550 nm combined with time of flight operating at 850 nm for 2D image reconstruction, specifically targeting rainy conditions. We incorporate diffusion models into the proposed system to enhance the quality of NIR-SPI images. By simulating various conditions of background illumination and droplet size in an outdoor laboratory scenario, we assess the feasibility of utilizing NIR-SPI as a vision sensor in challenging outdoor environments.

An information-theoretic approach to single cell sequencing analysis.

BACKGROUND: Single-cell sequencing (sc-Seq) experiments are producing increasingly large data sets. However, large data sets do not necessarily contain large amounts of information. RESULTS: Here, we formally quantify the information obtained from a sc-Seq experiment and show that it corresponds to an intuitive notion of gene expression heterogeneity. We demonstrate a natural relation between our notion of heterogeneity and that of cell type, decomposing heterogeneity into that component attributable to differential expression between cell types (inter-cluster heterogeneity) and that remaining (intra-cluster heterogeneity). We test our definition of heterogeneity as the objective function of a clustering algorithm, and show that it is a useful descriptor for gene expression patterns associated with different cell types. CONCLUSIONS: Thus, our definition of gene heterogeneity leads to a biologically meaningful notion of cell type, as groups of cells that are statistically equivalent with respect to their patterns of gene expression. Our measure of heterogeneity, and its decomposition into inter- and intra-cluster, is non-parametric, intrinsic, unbiased, and requires no additional assumptions about expression patterns. Based on this theory, we develop an efficient method for the automatic unsupervised clustering of cells from sc-Seq data, and provide an R package implementation.

Bubble dynamics and speed of jets for needle-free injections produced by thermocavitation.

Significance: The number of injections administered has increased dramatically worldwide due to vaccination campaigns following the COVID-19 pandemic, creating a problem of disposing of syringes and needles. Accidental needle sticks occur among medical and cleaning staff, exposing them to highly contagious diseases, such as hepatitis and human immunodeficiency virus. In addition, needle phobia may prevent adequate treatment. To overcome these problems, we propose a needle-free injector based on thermocavitation. Aim: Experimentally study the dynamics of vapor bubbles produced by thermocavitation inside a fully buried 3D fused silica chamber and the resulting high-speed jets emerging through a small nozzle made at the top of it. The injected volume can range from ∼0.1 to 2 µL per shot. We also demonstrate that these jets have the ability to penetrate agar skin phantoms and ex-vivo porcine skin. Approach: Through the use of a high-speed camera, the dynamics of liquid jets ejected from a microfluidic device were studied. Thermocavitation bubbles are generated by a continuous wave laser (1064 nm). The 3D chamber was fabricated by ultra-short pulse laser-assisted chemical etching. Penetration tests are conducted using agar gels (1%, 1.25%, 1.5%, 1.75%, and 2% concentrations) and porcine tissue as a model for human skin. Result: High-speed camera video analysis showed that the average maximum bubble wall speed is about 10 to 25 m/s for almost any combination of pump laser parameters; however, a clever design of the chamber and nozzle enables one to obtain jets with an average speed of ∼70 m/s. The expelled volume per shot (0.1 to 2 µl) can be controlled by the pump laser intensity. Our injector can deliver up to 20 shots before chamber refill. Penetration of jets into agar of different concentrations and ex-vivo porcine skin is demonstrated. Conclusions: The needle-free injectors based on thermocavitation may hold promise for commercial development, due to their cost and compactness.

Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search.

Fragment merging is a promising approach to progressing fragments directly to on-scale potency: each designed compound incorporates the structural motifs of overlapping fragments in a way that ensures compounds recapitulate multiple high-quality interactions. Searching commercial catalogues provides one useful way to quickly and cheaply identify such merges and circumvents the challenge of synthetic accessibility, provided they can be readily identified. Here, we demonstrate that the Fragment Network, a graph database that provides a novel way to explore the chemical space surrounding fragment hits, is well-suited to this challenge. We use an iteration of the database containing >120 million catalogue compounds to find fragment merges for four crystallographic screening campaigns and contrast the results with a traditional fingerprint-based similarity search. The two approaches identify complementary sets of merges that recapitulate the observed fragment-protein interactions but lie in different regions of chemical space. We further show our methodology is an effective route to achieving on-scale potency by retrospective analyses for two different targets; in analyses of public COVID Moonshot and Mycobacterium tuberculosis EthR inhibitors, potential inhibitors with micromolar IC50 values were identified. This work demonstrates the use of the Fragment Network to increase the yield of fragment merges beyond that of a classical catalogue search.

Ultra-high-speed liquid chromatography combined with mass spectrometry detection analytical methods for the determination of nitrosamine drug substance-related impurities.

In the present study, five simple, feasible, and sensitive Ultra-high-speed liquid chromatography combined with mass spectrometry detection methods, using electrospray ionization are proposed. These methods were developed and validated for the determination of four different nitrosamine drug substance-related impurities-N-nitrosoacebutolol, N-nitrosobisoprolol, N-nitrosometoprolol, and N-nitrososotalol-in five beta blockers active pharmaceutical ingredients-acebutolol HCl, bisoprolol fumarate, metoprolol tartrate, metoprolol succinate, and sotalol HCl. The proposed methods were validated as per regulatory guidelines. Acquity HSS T3 (3.0 × 100 mm, 1.8 µm) column and formic acid 0.1% in water combined with methanol or acetonitrile were used for chromatographic separation in all methods. The limit of detection and the limit of quantification were found to be in the range of 0.02-1.2 and 2-20 parts per billion, respectively. The accuracy and precision of the five methods have been demonstrated in the working range of each one, giving values of recovery within the range of 64.1%-113.3%, and the regression coefficients (R) were found to be in the range of 0.9978-0.9999. These methods could be used for controlling nitrosamine drug substance-related impurities content for beta blockers drug substances batches manufactured at Moehs group.

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

BACKGROUND: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. OBJECTIVE: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. METHODS: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. RESULTS: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. CONCLUSION: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

Persistent homology analysis distinguishes pathological bone microstructure in non-linear microscopy images.

We present a topological method for the detection and quantification of bone microstructure from non-linear microscopy images. Specifically, we analyse second harmonic generation (SHG) and two photon excited autofluorescence (TPaF) images of bone tissue which capture the distribution of matrix (fibrillar collagen) structure and autofluorescent molecules, respectively. Using persistent homology statistics with a signed Euclidean distance transform filtration on binary patches of images, we are able to quantify the number, size, distribution, and crowding of holes within and across samples imaged at the microscale. We apply our methodology to a previously characterized murine model of skeletal pathology whereby vascular endothelial growth factor expression was deleted in osteocalcin-expressing cells (OcnVEGFKO) presenting increased cortical porosity, compared to wild type (WT) littermate controls. We show significant differences in topological statistics between the OcnVEGFKO and WT groups and, when classifying the males, or females respectively, into OcnVEGFKO or WT groups, we obtain high prediction accuracies of 98.7% (74.2%) and 77.8% (65.8%) respectively for SHG (TPaF) images. The persistence statistics that we use are fully interpretable, can highlight regions of abnormality within an image and identify features at different spatial scales.

Drug-drug interactions of ritonavir-boosted SARS-CoV-2 protease inhibitors in solid organ transplant recipients: experience from the initial use of lopinavir-ritonavir.

OBJECTIVES: To review the drug-drug interactions between tacrolimus and lopinavir/ritonavir in 23 patients who received solid organ transplant during the first wave of COVID-19 and to determine the efficacy as well as safety of prednisone monotherapy. METHODS: Observational study performed between March and June 2020 in solid organ transplant recipients admitted with an established diagnosis of SARS-CoV-2 infection who received lopinavir/ritonavir (≥2 doses). Once lopinavir/ritonavir therapy was initiated, calcineurin inhibitor treatment was temporarily switched to prednisone monotherapy (15-20 mg/d) to avoid drug-drug interactions and toxicity. After lopinavir/ritonavir treatment completion, immunosuppressive treatment was restarted with reduced doses of prednisone-tacrolimus (target minimum blood concentration -C0- approximately 5 ng/mL). Patients were observed for 3 months to confirm the absence of rejection. RESULTS: The median time from discontinuation of tacrolimus to initiation of lopinavir/ritonavir was 14 hours (interquartile range [IQR], 12-15) and from discontinuation of lopinavir/ritonavir to resumption of tacrolimus 58 hours (IQR, 47-81). The duration of lopinavir/ritonavir treatment was 7 days (IQR, 5-7). Nine of the 21 (42.8%) patients on tacrolimus treatment had C0 above the cutoff point after lopinavir/ritonavir initiation, despite having been substituted with prednisone before lopinavir/ritonavir initiation. Three patients had very high concentrations (>40 ng/mL) and developed toxicity. No episodes of acute rejection were diagnosed. DISCUSSION: We did not observe toxicity in patients for whom tacrolimus was discontinued 24 hours before starting lopinavir/ritonavir and reintroduced at half dose 48 to 72 hours after lopinavir/ritonavir discontinuation. Prednisone monotherapy during lopinavir/ritonavir therapy was safe with no episodes of acute rejection. Experience with lopinavir/ritonavir may be applicable to the use of nirmatrelvir/ritonavir, but larger multicentre studies are needed to confirm these findings.

["Carbon Net Zer0 2030" strategy of Canary Islands Health Service]. / Estrategia «Salud Zero Emisiones Netas 2030¼ del Servicio Canario de la Salud.

The Canary Islands Health Service is aware of the health risks arising from climate change. So health systems must be, with their action, part of the solution, not part of the problem. Currently, 4.4% of global carbon dioxide emissions come from activities related to the health field. To respond to this situation, the Canary Islands Health Service has launched the "Carbon Net Zer0 2030" strategy intending to achieve neutrality in net carbon emissions in the year 2030, applying measures direct and indirect, especially on the supply chain of the public health system. This is a ground-breaking project in Spain and is under continuous review, adding new specific actions to the strategy as the carbon footprint of the different procedures involved in the provision of health services is quantified.

Estrategia «Salud Zer0 Emisiones Netas 2030» del Servicio Canario de la Salud / “Carbon Net Zer0 2030” strategy of Canary Islands Health Service

El Servicio Canario de la Salud es consciente de los riesgos para la salud derivados del cambio climático y de que los sistemas de salud deben ser, con su acción, parte de la solución y no parte del problema. Actualmente, el 4,4% de las emisiones mundiales de dióxido de carbono provienen de actividades relacionadas con el ámbito sanitario. Para dar respuesta a esta situación, el Servicio Canario de la Salud ha puesto en marcha la estrategia «Salud Zer0 Emisiones Netas 2030», con la que se pretende alcanzar la neutralidad en emisiones netas de carbono en el año 2030 aplicando medidas tanto directas como indirectas, en especial sobre la cadena de suministro del sistema público de salud de Canarias. Este proyecto es pionero en España y está sujeto a revisión continua, sumándose nuevas acciones concretas a la estrategia conforme se vaya cuantificando la huella de carbono de los diferentes procedimientos implicados en la prestación de servicios sanitarios. (AU)

The Canary Islands Health Service is aware of the health risks arising from climate change. So health systems must be, with their action, part of the solution, not part of the problem. Currently, 4.4% of global carbon dioxide emissions come from activities related to the health field. To respond to this situation, the Canary Islands Health Service has launched the “Carbon Net Zer0 2030” strategy intending to achieve neutrality in net carbon emissions in the year 2030, applying measures direct and indirect, especially on the supply chain of the public health system. This is a ground-breaking project in Spain and is under continuous review, adding new specific actions to the strategy as the carbon footprint of the different procedures involved in the provision of health services is quantified. (AU)

Nanomaterials-Incorporated Chemically Modified Gelatin Methacryloyl-Based Biomedical Composites: A Novel Approach for Bone Tissue Engineering.

Gelatin methacryloyl (GelMA)-based composites are evolving three-dimensional (3D) networking hydrophilic protein composite scaffolds with high water content. These protein composites have been devoted to biomedical applications due to their unique abilities, such as flexibility, soft structure, versatility, stimuli-responsiveness, biocompatibility, biodegradability, and others. They resemble the native extracellular matrix (ECM) thanks to their remarkable cell-adhesion and matrix-metalloproteinase (MMP)-responsive amino acid motifs. These favorable properties promote cells to proliferate and inflate within GelMA-protein scaffolds. The performance of GelMA composites has been enriched using cell-amenable components, including peptides and proteins with a high affinity to harmonize cellular activities and tissue morphologies. Due to their inimitable merits, GelMA systems have been used in various fields such as drug delivery, biosensor, the food industry, biomedical, and other health sectors. The current knowledge and the role of GelMA scaffolds in bone tissue engineering are limited. The rational design and development of novel nanomaterials-incorporated GelMA-based composites with unique physicochemical and biological advantages would be used to regulate cellular functionality and bone regeneration. Substantial challenges remain. This review focuses on recent progress in mitigating those disputes. The study opens with a brief introduction to bone tissue engineering and GelMA-based composites, followed by their potential applications in bone tissue engineering. The future perspectives and current challenges of GelMA composites are demonstrated. This review would guide the researchers to design and fabricate more efficient multifunctional GelMA-based composites with improved characteristics for their practical applications in bone tissue engineering and biomedical segments.