Regional homogeneity and functional connectivity of freezing of gait conversion in Parkinson's disease.

Background: Freezing of gait (FOG) is common in the late stage of Parkinson's disease (PD), which can lead to disability and impacts the quality of life. Therefore, early recognition is crucial for therapeutic intervention. We aimed to explore the abnormal regional homogeneity (ReHo) and functional connectivity (FC) in FOG converters and evaluate their diagnostic values. Methods: The data downloaded from the Parkinson's Disease Progression Markers Project (PPMI) cohort was subdivided into PD-FOG converters (n = 16) and non-converters (n = 17) based on whether FOG appeared during the 3-year follow-up; 16 healthy controls were well-matched. ReHo and FC analyses were used to explore the variations in spontaneous activity and interactions between significant regions among three groups of baseline data. Correlations between clinical variables and the altered ReHo values were assessed in FOG converter group. Last, logistic regression and receiver operating characteristic curve (ROC) were used to predict diagnostic value. Results: Compared with the non-converters, FOG converters had reduced ReHo in the bilateral medial superior frontal gyrus (SFGmed), which was negatively correlated with the postural instability and gait difficulty (PIGD) score. ReHo within left amygdala/olfactory cortex/putamen (AMYG/OLF/PUT) was decreased, which was correlated with anxiety and autonomic dysfunction. Also, increased ReHo in the left supplementary motor area/paracentral lobule was positively correlated with the rapid eye movement sleep behavior disorder screening questionnaire. FOG converters exhibited diminished FC in the basal ganglia, limbic area, and cognitive control cortex, as compared with non-converters. The prediction model combined ReHo of basal ganglia and limbic area, with PIGD score was the best predictor of FOG conversion. Conclusion: The current results suggested that abnormal ReHo and FC in the basal ganglia, limbic area, and cognitive control cortex may occur in the early stage of FOG. Basal ganglia and limbic area dysfunction combined with higher PIGD score are useful for the early recognition of FOG conversion.

Association of Cortical Gyrification With Imaging and Serum Biomarkers in Patients With Parkinson Disease.

BACKGROUND AND OBJECTIVES: Pathologic progression across the cortex is a key feature of Parkinson disease (PD). Cortical gyrification is a morphologic feature of human cerebral cortex that is tightly linked to the integrity of underlying axonal connectivity. Monitoring cortical gyrification reductions may provide a sensitive marker of progression through structural connectivity, preceding the progressive stages of PD pathology. We aimed to examine the progressive cortical gyrification reductions and their associations with overlying cortical thickness, white matter (WM) integrity, striatum dopamine availability, serum neurofilament light (NfL) chain, and CSF α-synuclein levels in PD. METHODS: This study included a longitudinal dataset with baseline (T0), 1-year (T1), and 4-year (T4) follow-ups and 2 cross-sectional datasets. Local gyrification index (LGI) was computed from T1-weighted MRI data to measure cortical gyrification. Fractional anisotropy (FA) was computed from diffusion-weighted MRI data to measure WM integrity. Striatal binding ratio (SBR) was measured from 123Ioflupane SPECT scans. Serum NfL and CSF α-synuclein levels were also measured. RESULTS: The longitudinal dataset included 113 patients with de novo PD and 55 healthy controls (HCs). The cross-sectional datasets included 116 patients with relatively more advanced PD and 85 HCs. Compared with HCs, patients with de novo PD showed accelerated LGI and FA reductions over 1-year period and a further decline at 4-year follow-up. Across the 3 time points, the LGI paralleled and correlated with FA (p = 0.002 at T0, p = 0.0214 at T1, and p = 0.0037 at T4) and SBR (p = 0.0095 at T0, p = 0.0035 at T1, and p = 0.0096 at T4) but not with overlying cortical thickness in patients with PD. Both LGI and FA correlated with serum NfL level (LGI: p < 0.0001 at T0, p = 0.0043 at T1; FA: p < 0.0001 at T0, p = 0.0001 at T1) but not with CSF α-synuclein level in patients with PD. In the 2 cross-sectional datasets, we revealed similar patterns of LGI and FA reductions and associations between LGI and FA in patients with more advanced PD. DISCUSSION: We demonstrated progressive reductions in cortical gyrification that were robustly associated with WM microstructure, striatum dopamine availability, and serum NfL level in PD. Our findings may contribute biomarkers for PD progression and potential pathways for early interventions of PD.

Tailoring a novel ovalbumin emulsion gel for stability improvement and functional properties enhancement: Effect of oil phase structure changes by beeswax.

This study aimed to form a novel emulsion gel (EG) through structured oil phase of natural component beeswax (BW), together with ovalbumin (OVA), and to investigate the mechanism of its formation and stabilization in terms of microstructure and processing properties. Confocal laser scanning microscopy (CLSM) demonstrated that the EG formed a continuous double network structure since the superior crystallinity of the oil phase was given by BW. Fourier transform infrared spectroscopy (FT-IR) illustrated that the acylation of the phenolic hydroxyl group in BW with an amide bond in OVA, increased the hydrogen bonding of EG. Furthermore, the immobilization of the oil phase results in better thermal and freeze-thaw stability of EG. Finally, EG was used as a curcumin delivery system, and the presence of BW significantly improved its adaptability to multiple environmental factors. In summary, our study would provide valuable ideas for developing the design of finely structured functional food.

The complex interplay of hypoxia and sleep disturbance in gray matter structure alterations in obstructive sleep apnea patients.

Background: Obstructive Sleep Apnea (OSA) characteristically leads to nocturnal hypoxia and sleep disturbance. Despite clear evidence of OSA-induced cognitive impairments, the literature offers no consensus on the relationship between these pathophysiological processes and brain structure alterations in patients. Objective: This study leverages the robust technique of structural equation modeling to investigate how hypoxia and sleep disturbance exert differential effects on gray matter structures. Methods: Seventy-four Male participants were recruited to undergo overnight polysomnography and T1-weighted Magnetic Resonance Imaging. Four structural outcome parameters were extracted, namely, gray matter volume, cortical thickness, sulcal depth, and fractal dimension. Structural equation models were constructed with two latent variables (hypoxia, and sleep disturbance) and three covariates (age, body mass index, and education) to examine the association between gray matter structural changes in OSA and the two latent variables, hypoxia and sleep disturbance. Results: The structural equation models revealed hypoxia-associated changes in diverse regions, most significantly in increased gray matter volume, cortical thickness and sulcal depth. In contrast, sleep disturbance. Was shown to be largely associated with reduce gray matter volume and sulcal depth. Conclusion: This study provides new evidence showing significant effects of OSA-induced hypoxia and sleep disturbance on gray matter volume and morphology in male patients with obstructive sleep apnea. It also demonstrates the utility of robust structural equation models in examining obstructive sleep apnea pathophysiology.

Cortical thinning in male obstructive sleep apnoea patients with excessive daytime sleepiness.

Background and purpose: Obstructive sleep apnoea is associated with excessive daytime sleepiness due to sleep fragmentation and hypoxemia, both of which can lead to abnormal brain morphology. However, the pattern of brain structural changes associated with excessive daytime sleepiness is still unclear. This study aims to investigate the effects of excessive daytime sleepiness on cortical thickness in patients with obstructive sleep apnoea. Materials and methods: 61 male patients with newly diagnosed obstructive sleep apnoea were included in the present study. Polysomnography and structural MRI were performed for each participant. Subjective daytime sleepiness was assessed using the Epworth Sleepiness Scale score. Surface-based morphometric analysis was performed using Statistical Parametric Mapping 12 and Computational Anatomy 12 toolboxes to extract cortical thickness. Results: Using the median Epworth Sleepiness Scale score, patients were divided into the non-sleepiness group and the sleepiness group. The cortical thickness was markedly thinner in the sleepiness group in the left temporal, frontal, and parietal lobe and bilateral pre- and postcentral gyri (pFWE < 0.05). There was a significant negative correlation between the cortical thickness and the Epworth Sleepiness Scale score. After adjusting for age, body mass index, and obstructive sleep apnoea severity, the Epworth Sleepiness Scale score remained an independent factor affecting the cortical thickness of the left middle temporal lobe, transverse temporal and temporal pole. Conclusion: Subjective daytime sleepiness is associated with decreased cortical thickness, and the Epworth Sleepiness Scale score may be of utility as a clinical marker of brain injury in patients with obstructive sleep apnoea.

Differences in eccentricity for sound-induced flash illusion in four visual fields.

A sound-induced flash illusion (SiFI) is a multisensory illusion dominated by auditory stimuli, in which the individual perceives that the number of visual flashes is equal to the number of auditory stimuli when visual flashes are presented along with an unequal number of auditory stimuli. Although the mechanisms underlying fission and fusion illusions have been documented, there is not yet a consensus on how they vary according to the different eccentricities. In the present study, by incorporating the classic SiFI paradigm into four different eccentricities, we aimed to investigate whether the SiFI varies under the different eccentricities. The results showed that the fission illusion varied significantly across the four eccentricities, with the perifovea (7°) and peripheral (11°) illusions being greater than the fovea and parafovea (3°) illusions. In contrast, the fusion illusion did not vary significantly across the four eccentricities. Our findings revealed that SiFI was affected by different visual fields and that there were differences between the fission and the fusion illusions. Furthermore, by examining the SiFI of eccentricity across visual fields, this study also suggests that bottom-up factors affect the SiFI.

Optimized DOX Drug Deliveries via Chitosan-Mediated Nanoparticles and Stimuli Responses in Cancer Chemotherapy: A Review.

Chitosan nanoparticles (NPs) serve as useful multidrug delivery carriers in cancer chemotherapy. Chitosan has considerable potential in drug delivery systems (DDSs) for targeting tumor cells. Doxorubicin (DOX) has limited application due to its resistance and lack of specificity. Chitosan NPs have been used for DOX delivery because of their biocompatibility, biodegradability, drug encapsulation efficiency, and target specificity. In this review, various types of chitosan derivatives are discussed in DDSs to enhance the effectiveness of cancer treatments. Modified chitosan-DOX NP drug deliveries with other compounds also increase the penetration and efficiency of DOX against tumor cells. We also highlight the endogenous stimuli (pH, redox, enzyme) and exogenous stimuli (light, magnetic, ultrasound), and their positive effect on DOX drug delivery via chitosan NPs. Our study sheds light on the importance of chitosan NPs for DOX drug delivery in cancer treatment and may inspire the development of more effective approaches for cancer chemotherapy.

Machine Learning Models for Diagnosis of Parkinson's Disease Using Multiple Structural Magnetic Resonance Imaging Features.

Purpose: This study aimed to develop machine learning models for the diagnosis of Parkinson's disease (PD) using multiple structural magnetic resonance imaging (MRI) features and validate their performance. Methods: Brain structural MRI scans of 60 patients with PD and 56 normal controls (NCs) were enrolled as development dataset and 69 patients with PD and 71 NCs from Parkinson's Progression Markers Initiative (PPMI) dataset as independent test dataset. First, multiple structural MRI features were extracted from cerebellar, subcortical, and cortical regions of the brain. Then, the Pearson's correlation test and least absolute shrinkage and selection operator (LASSO) regression were used to select the most discriminating features. Finally, using logistic regression (LR) classifier with the 5-fold cross-validation scheme in the development dataset, the cerebellar, subcortical, cortical, and a combined model based on all features were constructed separately. The diagnostic performance and clinical net benefit of each model were evaluated with the receiver operating characteristic (ROC) analysis and the decision curve analysis (DCA) in both datasets. Results: After feature selection, 5 cerebellar (absolute value of left lobule crus II cortical thickness (CT) and right lobule IV volume, relative value of right lobule VIIIA CT and lobule VI/VIIIA gray matter volume), 3 subcortical (asymmetry index of caudate volume, relative value of left caudate volume, and absolute value of right lateral ventricle), and 4 cortical features (local gyrification index of right anterior circular insular sulcus and anterior agranular insula complex, local fractal dimension of right middle insular area, and CT of left supplementary and cingulate eye field) were selected as the most distinguishing features. The area under the curve (AUC) values of the cerebellar, subcortical, cortical, and combined models were 0.679, 0.555, 0.767, and 0.781, respectively, for the development dataset and 0.646, 0.632, 0.690, and 0.756, respectively, for the independent test dataset, respectively. The combined model showed higher performance than the other models (Delong's test, all p-values < 0.05). All models showed good calibration, and the DCA demonstrated that the combined model has a higher net benefit than other models. Conclusion: The combined model showed favorable diagnostic performance and clinical net benefit and had the potential to be used as a non-invasive method for the diagnosis of PD.

Egg White Peptides Increased the Membrane Liquid-Ordered Phase of Giant Unilamellar Vesicles: Visualization, Localization, and Phase Regulation Mechanism.

Cell membranes are heterogeneous and consist of liquid-ordered (Lo) and liquid-disordered (Ld) phases due to phase separation. Membrane regulation of egg white peptides (LCAY and QVPLW) was confirmed in our previous study. However, the underlying mechanism of phase regulation by the peptides has not been elucidated. This study aimed to explore the effect of LCAY and QVPLW on the membrane phase separation and illustrate their mechanism by giant unilamellar vesicles (GUVs). Based on phase separation visualization, LCAY and QVPLW were found to increase the Lo phase by rearranging lipids and ordering the Ld phase. LCAY and QVPLW can bind to the GUVs and localize in the amphiphilic region of the membrane. By hydrogen bonds and hydrophobic interactions, LCAY and QVPLW may play a cholesterol-like role in regulating phase separation.

Long-term training reduces the responses to the sound-induced flash illusion.

The sound-induced flash illusion (SiFI) is a robust auditory-dominated multisensory integration phenomenon that is used as a reliable indicator to assess multisensory integration. Previous studies have indicated that the SiFI effect is correlated with perceptual sensitivity. However, to date, there is no consensus regarding how it corresponds to sensitivity with long-term training. The present study adopted the classic SiFI paradigm with feedback training to investigate the effect of a week of long-term training on the SiFI effect. Both the training group and control group completed a pretest and a posttest before and after the perceptual training; however, only the training group was required to complete 7-day behavioral training. The results showed that (1) long-term training could reduce the response of fission and fusion illusions by improving perceptual sensitivity and that (2) there was a "plateau effect" that emerged during the training stage, which tended to stabilize by the fifth day. These findings demonstrated that the SiFI effect could be modified with long-term training by ameliorating perceptual sensitivity, especially in terms of the fission illusion. Therefore, the present study supplements perceptual training in SiFI domains and provides evidence that the SiFI could be used as an assessment intervention to improve the efficiency of multisensory integration.

Characterization of resistant starch nanoparticles prepared via debranching and nanoprecipitation.

Cyperus esculentus starch was treated by pullulanase debranching and nanoprecipitation to prepare resistant starch nanoparticles. Amylose contents, rheological properties of debranched starch and the size, crystalline structure, resistant starch contents of the prepared starch nanoparticles were investigated. The results of amylose contents showed that enzymatic hydrolysis 4 h was the most appropriate enzymatic hydrolysis time. Dynamic light scattering analysis and scanning electron microscopy observations showed that when the starch solution was added to the ethanol, the larger the amount of ethanol, the more conducive to the formation of small size starch nanoparticles. When volume ratio of starch solution/ethanol was 1/5, the particle size was 271.1 nm, the content of resistant starch was higher (15.28%). X-ray diffraction results indicated that resistant starch nanoparticles had V-type crystalline structure. Pullulanase debranching and nanoprecipitation can be utilized to prepare smaller size of Cyperus esculentus resistant starch with higher efficiency.

Egg White-Derived Peptides QVPLW and LCAY Inhibit the Activity of Angiotensin I-Converting Enzyme in Human Umbilical Vein Endothelial Cells by Suppressing Its Recruitment into Lipid Rafts.

As a membrane protein, the activity of angiotensin I-converting enzyme (ACE) can be modulated via regulation of its localization in the cell membrane with food-derived peptides. This study aimed to explore the effect of egg white peptides on the cell membrane localization and activity of ACE in human umbilical vein endothelial cells. ACE activity was found to be related to lipid rafts by using methyl-ß-cyclodextrin (MßCD). QVPLW and LCAY can inhibit ACE activity by preventing ACE recruitment into lipid rafts, with in situ IC50 values of 238.46 ± 11.35 µM and 31.55 ± 2.64 µM in the control groups, as well as 45.43 ± 6.15 µM and 34.63 ± 1.59 µM in the MßCD groups, respectively. QVPLW and LCAY may alter the cell membrane properties, including the fluidity, potential, and permeability, and eventually promote the transposition of ACE.

Patterns of Sulcal depth and cortical thickness in Parkinson's disease.

Previous voxel-based morphometry (VBM) and cortical thickness (CT) studies on Parkinson's disease (PD) have mainly reported the gray matter size reduction, whereas the shape of cortical surface can also change in PD patients. For the first time, we analyzed sulcal depth (SD) patterns in PD patients by using whole brain region of interest (ROI)-based approach. In a cross-sectional study, high-resolution brain structural MRI images were collected from 60 PD patients without dementia and 56 age-and sex-matched healthy controls (HC). SD and CT were estimated using the Computational Anatomy Toolbox (CAT12) and statistically compared between groups on whole brain ROI-based level using statistical parametric mapping 12 (SPM12). Additionally, correlations between regional brain changes and clinical variables were also examined. Compared to HC, PD patients showed lower SD in widespread regions, including temporal (the bilateral transverse temporal, the left inferior temporal, the right middle temporal and the right superior temporal), insular (the left insula), frontal (the left pars triangularis, the left pars opercularis and the left precentral), parietal (the bilateral superior parietal) and occipital (the right cuneus) regions. For CT, only the left pars opercularis showed lower CT in PD patients compared to HC. No regions showed higher SD or CT in PD patients compared to HC. In PD patients, a significant positive correlation was found between SD of the left pars opercularis and MMSE scores, such that lower MMSE scores were related to lower SD of the left pars opercularis. Our results of widespread lower SD, but relatively localized lower CT, indicate that SD seems to be more sensitive to brain changes than CT and may be mainly affected by white matter damage. Hence, SD may be a more promising indicator to investigate the surface shape changes in PD patients. The significant positive correlation between SD of the left pars opercularis and MMSE scores suggests that SD may be prognostic of future cognitive decline.

Influence of esterification and ultrasound treatment on formation and properties of starch nanoparticles and their impact as a filler on chitosan based films characteristics.

Starch nanoparticles were prepared by citrate esterification and ultrasound treatment. With the increase of ultrasonic treatment time, the mean size and PDI of the particles decreased gradually, when the ultrasonic treatment time was 5 min, the prepared starch nanoparticles had a mean size and PDI of 352.8 nm and 0.292, respectively. X-ray diffraction (XRD) showed that the starch nanoparticles prepared by ultrasonic treatment for 5 min had an A-type crystalline structure and a crystallinity of 41.42%. The chitosan composite films were reinforced by esterified starch with different ultrasound treatment times, the results indicated that the addition of starch nanoparticles resulted in a significant increase in the mechanical properties of films. This study indicates that esterification and ultrasound treatment can be used to prepare starch nanoparticles with a higher crystallinity and higher efficiency, which will further promote the application of nanocomposite films in packaging applications.

Detecting Abnormal Brain Regions in Schizophrenia Using Structural MRI via Machine Learning.

Utilizing neuroimaging and machine learning (ML) to differentiate schizophrenia (SZ) patients from normal controls (NCs) and for detecting abnormal brain regions in schizophrenia has several benefits and can provide a reference for the clinical diagnosis of schizophrenia. In this study, structural magnetic resonance images (sMRIs) from SZ patients and NCs were used for discriminative analysis. This study proposed an ML framework based on coarse-to-fine feature selection. The proposed framework used two-sample t-tests to extract the differences between groups first, then further eliminated the nonrelevant and redundant features with recursive feature elimination (RFE), and finally utilized the support vector machine (SVM) to learn the decision models with selected gray matter (GM) and white matter (WM) features. Previous studies have tended to report differences at the group level instead of at the individual level and cannot be widely applied. The method proposed in this study extends the diagnosis to the individual level and has a higher recognition rate than previous methods. The experimental results of this study demonstrate that the proposed framework distinguishes SZ patients from NCs, with the highest classification accuracy reaching over 85%. The identified biomarkers are also consistent with previous literature findings. As a universal method, the proposed framework can be extended to diagnose other diseases.

Construction and Application of Membrane-Bound Angiotensin-I Converting Enzyme System: A New Approach for the Evaluation of Angiotensin-I Converting Enzyme Inhibitory Peptides.

The effect of the plasma membrane on the activity of angiotensin-I converting enzyme (ACE) plays a crucial role in the evaluation of food-derived ACE inhibitory peptides, although these peptides are commonly evaluated in the system with ACE in its free state. In this study, we constructed an in vitro membrane-bound ACE C domain system to simulate the presence of the plasma membrane. The resultant Km and Vmax suggested that the presence of the membrane reduced the affinity between ACE C domain and hippuryl-histidyl-leucine, while it increased the reaction velocity. The ACE inhibitory activity of four egg white peptides and five structurally modified peptides suggested that a moderate hydrophobicity/hydrophilicity of the peptide is beneficial for the improvement of their ACE inhibitory activity in a membrane-bound system. These results also indicated that the N terminal plays a significant role in the ACE inhibitory activity of peptides in the membrane-bound system.

Cortical complexity and gyrification patterns in Parkinson's disease.

This study aimed to investigate the cortical complexity and gyrification patterns in Parkinson's disease (PD) using local fractional dimension (LFD) and local gyrification index (LGI), respectively. In a cross-sectional study, LFD and LGI in 60 PD patients without dementia and 56 healthy controls (HC) were investigated using brain structural MRI data. LFD and LGI were estimated using the Computational Anatomy Toolbox (CAT12) and statistically analyzed between groups on a vertex level using statistical parametric mapping 12 (SPM12). Additionally, correlations between structural changes and clinical indices were further examined. PD patients showed widespread LFD reductions mainly in the left pre- and postcentral cortex, the left superior frontal cortex, the left caudal middle frontal cortex, the bilaterally superior parietal cortex and the right superior temporal cortex compared to HC. For LGI, there was no significant difference between PD and HC. In PD patients group, a significant negative correlation was found between LFD of the left postcentral cortex and duration of illness (DOI). Our results of widespread LFD reductions, but not LGI, indicate that LFD may provide a more sensitive diagnostic biomarker and encode specific information of PD. The significant negative correlation between LFD of the left postcentral cortex and DOI suggests that LFD may be a biomarker to monitor disease progression in PD.

Abnormal Topological Organization of Sulcal Depth-Based Structural Covariance Networks in Parkinson's Disease.

Recent research on Parkinson's disease (PD) has demonstrated the topological abnormalities of structural covariance networks (SCNs) using various morphometric features from structural magnetic resonance images (sMRI). However, the sulcal depth (SD)-based SCNs have not been investigated. In this study, we used SD to investigate the topological alterations of SCNs in 60 PD patients and 56 age- and gender-matched healthy controls (HC). SCNs were constructed by thresholding SD correlation matrices of 68 regions and analyzed using graph theoretical approaches. Compared with HC, PD patients showed increased normalized clustering coefficient and normalized path length, as well as a reorganization of degree-based and betweenness-based hubs (i.e., less frontal hubs). Moreover, the degree distribution analysis showed more high-degree nodes in PD patients. In addition, we also found the increased assortativity and reduced robustness under a random attack in PD patients compared to HC. Taken together, these findings indicated an abnormal topological organization of SD-based SCNs in PD patients, which may contribute in understanding the pathophysiology of PD at the network level.

Effect of green tea consumption on human brain function in resting-state functional MRI.

BACKGROUND AND OBJECTIVES: Green tea is reported to have wide benefits on psychological states and cognitive functions. Studies that focus on the underlying neural mechanisms of green tea are limited to its single composition while people usually benefit from green tea water that contains various composition. In this study, we examined the human brain activity changes after drinking natural green tea by using regional homogeneity and functional connectivity based on the resting-state functional MRI technique. METHODS AND STUDY DESIGN: Fifteen healthy volunteers participated in two imaging sessions: a control (water) session and a green tea session, each session comprised a predrinking, drinking, and postdrinking section, during the drinking section, the subject consumed 200 mL of green tea infusion or water in 3 to 5 minutes. Then the post-tea and post-water imaging data were selected for regional homogeneity and functional connectivity analysis. RESULTS: Our results revealed that, compared with the control group, the green tea group exhibited an increased regional homogeneity in the frontal, parietal, and occipital areas of the brain, decreased regional homogeneity values in the left cuneus and left lingual gyrus, mainly a decreased functional connectivity in the default mode network, somatosensory, visual cortex, and parieto-frontal areas and enhanced functional connectivity in brain regions associated with memory. CONCLUSIONS: This result indicates that green tea consumption impacts the brain activity during resting state.

Effects of Polypropylene Fibre and Strain Rate on Dynamic Compressive Behaviour of Concrete.

This paper presents an experimental study on the dynamic compressive behaviour of polypropylene (PP) fibre reinforced concrete under various strain rates using split Hopkinson pressure bar (SHPB) equipment. The effects of PP fibre content and strain rate on the dynamic compressive stress-strain relationship and failure patterns were estimated. The results indicated that the addition of PP fibre enhanced the dynamic compressive properties of concrete mixtures although it resulted in a significant reduction in workability and a slight decrease in static compressive strength. Considering the workability, static compressive strength and dynamic compressive behaviour, the optimal PP fibre content was found to be 0.9 kg/m3 as the mixture exhibited the highest increase in dynamic compressive strength of 5.6%, 40.3% in fracture energy absorption and 11.1% in total energy absorption; further, it showed the least reduction (only 5.8%) in static compressive strength among all mixtures compared to the reference mixture without fibre. For all mixtures, the dynamic compressive properties, energy absorption capacity, strain at peak stress, ultimate strain and dynamic increase factor (DIF) were significantly influenced by strain rate, i.e., strain rate effect. When the strain rate was relatively low, PP fibres were effective in controlling the cracking, and the dynamic compressive properties of PP fibre reinforced mixtures were improved accordingly.