Development of a screening system of gene sets for estimating the time of early skeletal muscle injury based on second-generation sequencing technology.

The present study is aimed to address the challenge of wound age estimation in forensic science by identifying reliable genetic markers using low-cost and high-precision second-generation sequencing technology. A total of 54 Sprague-Dawley rats were randomly assigned to a control group or injury groups, with injury groups being further divided into time points (4 h, 8 h, 12 h, 16 h, 20 h, 24 h, 28 h, and 32 h after injury, n = 6) to establish rat skeletal muscle contusion models. Gene expression data were obtained using second-generation sequencing technology, and differential gene expression analysis, weighted gene co-expression network analysis (WGCNA) and time-dependent expression trend analysis were performed. A total of six sets of biomarkers were obtained: differentially expressed genes at adjacent time points (127 genes), co-expressed genes most associated with wound age (213 genes), hub genes exhibiting time-dependent expression (264 genes), and sets of transcription factors (TF) corresponding to the above sets of genes (74, 87, and 99 genes, respectively). Then, random forest (RF), support vector machine (SVM) and multilayer perceptron (MLP), were constructed for wound age estimation from the above gene sets. The results estimated by transcription factors were all superior to the corresponding hub genes, with the transcription factor group of WGCNA performed the best, with average accuracy rates of 96% for three models' internal testing, and 91.7% for the highest external validation. This study demonstrates the advantages of the indicator screening system based on second-generation sequencing technology and transcription factor level for wound age estimation.

Treatment planning computed tomography radiomics for predicting treatment outcomes and haematological toxicities in locally advanced cervical cancer treated with radiotherapy: A retrospective cohort study.

OBJECTIVE: We evaluated whether radiomic features extracted from planning computed tomography (CT) scans predict clinical end points in patients with locally advanced cervical cancer (LACC) undergoing intensity-modulated radiation therapy and brachytherapy. DESIGN: A retrospective cohort study. SETTING: Xiangya Hospital of Central South University, Changsha, Hunan, China. POPULATION: Two hundred and fifty-seven LACC patients who were treated with intensity-modulated radiotherapy from 2014 to 2017. METHODS: Patients were allocated into the training/validation sets (3:1 ratio) using proportional random sampling, resulting in the same proportion of groups in the two sets. We extracted 254 radiomic features from each of the gross target volume, pelvis and sacral vertebrae. The sequentially backward elimination support vector machine algorithm was used for feature selection and end point prediction. MAIN OUTCOMES AND MEASURES: Clinical end points include tumour complete response (CR), 5-year overall survival (OS), anaemia, and leucopenia. RESULTS: A combination of ten clinicopathological parameters and 34 radiomic features performed best for predicting CR (validation balanced accuracy: 80.8%). The validation balanced accuracy of 54 radiomic features was 85.8% for OS, and their scores can stratify patients into the low-risk and high-risk groups (5-year OS: 95.5% versus 36.4%, p < 0.001). The clinical and radiomic models were also predictive of anaemia and leucopenia (validation balanced accuracies: 71.0% and 69.9%). CONCLUSION: This study demonstrated that combining clinicopathological parameters with CT-based radiomics may have value for predicting clinical end points in LACC. If validated, this model may guide therapeutic strategy to optimise the effectiveness and minimise toxicity or treatment for LACC.

Scale-invariant sensitivity for multi-purpose water reservoirs management with temporal scale-dependent modeling.

High-resolution temporal data (e.g., daily) is valuable for the decision-making of water resources management because it more accurately captures fine-scale processes and extremes than the coarse temporal data (e.g., weekly or monthly). However, many studies rarely consider this superior suitability for water resource modeling and management; instead, they often use whichever data is more readily available. So far, no comparative investigations have been conducted to determine if access to different time-scale data would change decision-maker perceptions or the rationality of decision making. This study proposes a framework for assessing the impact of different temporal scales on water resource management and the performance objective's sensitivity to uncertainties. We built the multi-objective operation models and operating rules of a water reservoir system based on daily, weekly, and monthly scales, respectively, using an evolution multi-objective direct policy search. The temporal scales of the input variables (i.e., streamflow) affect both the model structures and the output variables. In exploring these effects, we reevaluated the temporal scale-dependent operating rules under uncertain streamflow sets generated from synthetic hydrology. Finally, we obtained the output variable's sensitivities to the uncertain factors at different temporal scales using the distribution-based sensitivity analysis method. Our results show that water management based on too coarse resolution might give decision makers the wrong perception because the effect of actual extreme streamflow process on the performance objectives is ignored. The streamflow uncertainty is more influential than the uncertainty associated with operating rules. However, the sensitivities are characterized by temporal scale invariance, as the differences of the sensitivity between different temporal scales are not obvious over the uncertainties in streamflow and thresholds. These results show that water management should consider the resolution-dependent effect of temporal scales for balancing modeling complexity and computational cost.

A simple technology for plastid transformation with fragmented DNA.

Plastid engineering has several unique advantages such as high expression of transgenes due to high polyploidy of plastid genomes and environmental biosafety because of maternal inheritance of transgenes, and has become a promising tool for molecular farming, metabolic engineering, and genetic improvement. However, there are no standard vectors available for plastid transformation. Moreover, the construction of plastid transformation vectors containing long operons or genes encoding proteins that are toxic to Escherichia coli was tedious or difficult. Here, we developed a simple plastid transformation technology without the need for in vitro vector construction by using multiple linear DNA fragments which share homologous sequences (HSs) at their ends. The strategy is based on homologous recombination between HSs of DNA fragments via endogenous recombination machinery in plastids, which subsequently are integrated into the plastid genome. We found that HSs of 200 bp or longer were sufficient for mediating the integration into the plastid genome with at least similar efficiency to that of plasmid DNA-based plastid transformation. Furthermore, we successfully used this method to introduce a phage lysin-encoding gene and a long operon into a tobacco plastid genome. The establishment of this technology simplifies the plastid transformation procedure and provides a novel solution for expressing proteins, which are either toxic to the cloning host or large operons in plastids, without need of vector cloning.

Recognition of freezing of gait in Parkinson's disease based on combined wearable sensors.

Freezing of gait is a common gait disorder among patients with advanced Parkinson's disease and is associated with falls. This paper designed the relevant experimental procedures to obtain FoG signals from PD patients. Accelerometers, gyroscopes, and force sensing resistor sensors were placed on the lower body of patients. On this basis, the research on the optimal feature extraction method, sensor configuration, and feature quantity selection in the FoG detection process is carried out. Thirteen typical features consisting of time domain, frequency domain and statistical features were extracted from the sensor signals. Firstly, we used the analysis of variance (ANOVA) to select features through comparing the effectiveness of two feature selection methods. Secondly, we evaluated the detection effects with different combinations of sensors to get the best sensors configuration. Finally, we selected the optimal features to construct FoG recognition model based on random forest. After comprehensive consideration of factors such as detection performance, cost, and actual deployment requirements, the 35 features obtained from the left shank gyro and accelerometer, and 78.39% sensitivity, 91.66% specificity, 88.09% accuracy, 77.58% precision and 77.98% f-score were achieved. This objective FoG recognition method has high recognition accuracy, which will be helpful for early FoG symptoms screening and treatment.

Molecular basis for allosteric regulation of the type 2 ryanodine receptor channel gating by key modulators.

The type 2 ryanodine receptor (RyR2) is responsible for releasing Ca2+ from the sarcoplasmic reticulum of cardiomyocytes, subsequently leading to muscle contraction. Here, we report 4 cryo-electron microscopy (cryo-EM) structures of porcine RyR2 bound to distinct modulators that, together with our published structures, provide mechanistic insight into RyR2 regulation. Ca2+ alone induces a contraction of the central domain that facilitates the dilation of the S6 bundle but is insufficient to open the pore. The small-molecule agonist PCB95 helps Ca2+ to overcome the barrier for opening. FKBP12.6 induces a relaxation of the central domain that decouples it from the S6 bundle, stabilizing RyR2 in a closed state even in the presence of Ca2+ and PCB95. Although the channel is open when PCB95 is replaced by caffeine and adenosine 5'-triphosphate (ATP), neither of the modulators alone can sufficiently counter the antagonistic effect to open the channel. Our study marks an important step toward mechanistic understanding of the sophisticated regulation of this key channel whose aberrant activity engenders life-threatening cardiac disorders.

The coupling interaction of soil organic carbon stock and water storage after vegetation restoration on the Loess Plateau, China.

Vegetation restoration may increase the soil organic carbon stock (SOCS) but decrease the soil water storage (SWS) of terrestrial ecosystems in arid and semiarid regions. To guarantee the sustainability of restoration, it is critical to evaluate the coupling interaction of SOCS and SWS. Here, we examined the spatial distributions of SOCS and SWS across a 0-200 cm soil profile in a grassland, forestland and shrubland on the Loess Plateau and determined the driving factors that affected their variations. Our results showed that SOCS and SWS varied across the 0-200 cm soil profile and considerably accumulated in the deep soil layers (100-200 cm). In comparison to SOCS, SWS generally had higher relative benefits in most studied plant communities, which ensured sustainable restoration. In addition, land use played a less important role than local environmental conditions in determining the variations in SOCS and SWS. Specifically, the interaction between SOCS and SWS was mainly strong in the surface soil layers (0-20 cm). Topography was a predominant factor that affected SOCS and SWS in the deep soil layers (100-200 cm), while soil texture was a stable driving factor influencing their variations across the whole soil profile (0-200 cm). Given the low moisture consumption of grasslands and the lowest root mean square deviation (RMSD) of Hippophae rhamnoides, we proposed an advanced scenario for ecological restoration on the Loess Plateau: establishing reasonably large Hippophae rhamnoides patches with fewer edges in a contiguous grassland matrix. Furthermore, this scenario should be tailored to local environmental conditions, such as soil water, texture and topography, followed by natural vegetation succession.

SET1/KMT2-governed histone H3K4 methylation coordinates the lifecycle in vivo and in vitro of the fungal insect pathogen Beauveria bassiana.

Biological control potential of insect-pathogenic fungi against pests is an overall output of various cellular processes regulated by signalling and epigenetic networks. In Beauveria bassiana, mono/di/trimethylation of histone H3 Lys 4 (H3K4me1/me2/m3) was abolished by inactivation of the histone lysine methyltransferase SET1/KMT2, leading to marked virulence loss, reductions in conidial hydrophobicity and adherence to insect cuticle, impeded proliferation in vivo, severe defects in growth and conidiation, and increased sensitivities to cell wall perturbation, H2 O2 and heat shock. Such compromised phenotypes correlated well with transcriptional abolishment or repression of carbon catabolite-repressing transcription factor Cre1, classes I and II hydrophobins Hyd1 and Hyd2 required for cell hydrophobicity, key developmental regulators, and stress-responsive enzymes/proteins. Particularly, expression of cre1, which upregulates hyd4 upon activation by KMT2-mediated H3K4me3 in Metarhizium robertsii, was nearly abolished in the Δset1 mutant, leading to abolished expression of hyd1 and hyd2 as homologues of hyd4. These data suggest that the SET1-Cre1-Hyd1/2 pathway function in B. bassiana like the KMT2-Cre1-Hyd4 pathway elucidated to mediate pathogenicity in M. robertsii. Our findings unveil not only a regulatory role for the SET1-cored pathway in fungal virulence but also its novel role in mediating asexual cycle in vitro and stress responses in B. bassiana.

Remote video-based outcome measures of patients with Parkinson's disease after deep brain stimulation using smartphones: a pilot study.

OBJECTIVE: To provide better postoperative healthcare for patients with Parkinson's disease (PD) who received deep brain stimulation (DBS) surgery and to allow surgeons improved tracking of surgical outcomes, the authors sought to examine the applicability and feasibility of remote assessment using smartphones. METHODS: A disease management mobile application specifically for PD was used to perform the remote assessment of patients with PD who underwent DBS. Connection with patients was first established via a phone call or a social application, and instructions for completing the remote assessment were delivered. During the video-based virtual meeting, three nonmotor assessment scales measuring the quality of life and mental state, and a modified version of the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale, part III (MDS-UPDRS III) measuring motor abilities were evaluated. After the assessment, a report and the satisfaction questionnaire were sent to the patient. RESULTS: Overall, 22 patients were recruited over a 4-week period. Among those, 18 patients completed the assessment on the mobile application. The mean duration was 41.3 minutes for video assessment and 17.5 minutes for nonmotor assessment via telephone. The mean estimated cost was 427.68 Chinese yuan (CNY) for an in-person visit and 20.91 CNY for a virtual visit (p < 0.001). The mean time estimate for an in-person visit was 5.51 hours and 0.68 hours for a virtual visit (p = 0.002). All patients reported satisfaction (77.78% very satisfied and 22.22% satisfied) with the virtual visit and were specifically impressed by the professionalism and great attitude of the physician assistant. The majority of patients agreed that the evaluation time was reasonable (50% totally agree, 44.44% agree, and 5.56% neither agree nor disagree) and all patients expressed interest in future virtual visits (61.11% very willingly and 38.89% willingly). No adverse events were observed during the virtual visit. CONCLUSIONS: Innovation in remote assessment technologies was highly feasible for its transforming power in the clinical management of patients with PD who underwent DBS and research. Video-based remote assessment offered considerable time and resource reduction for both patients and doctors. It also increased safety and was a well-accepted, favored tool. Finally, the results of this study have shown there is potential to combine remote assessment tools with real-life clinical visits and other telemedical technologies to collectively benefit the postoperative healthcare of patients with PD undergoing DBS.

Effects of Melatonin on Dairy Herd Improvement (DHI) of Holstein Cow with High SCS.

Mastitis is a common disease in cows breeding. The milk quality will be significantly reduced with increased milk somatic cells, which often occurs in cows with mastitis. In this study, the influence of seasonal changes, age and lactation stages in the Dairy Herd Improvement (DHI) of cows was investigated. Then, the Dairy Herd Improvement (DHI) of cows with high somatic cell score (SCS) after melatonin treatment was systemically investigated. The results showed that melatonin significantly suppressed the milk somatic cell score under all of the tested conditions. The melatonin treatment also improved the milk nutritional value by reducing its fat but increasing its lactose and protein contents. The application of melatonin significantly improved the DHI. The beneficial effects of melatonin on DHI are likely attributed to the antioxidant and anti-inflammatory activities of melatonin.

[Epidemiological characteristics of respiratory syncytial virus in hospitalized children with acute lower respiratory tract infection in Chongqing, China, from 2013 to 2018: an analysis of 2 066 cases].

OBJECTIVE: To study the detection rate, epidemic pattern, and clinical features of respiratory syncytial virus (RSV) in hospitalized children with acute lower respiratory infection (ALRI). METHODS: Nasopharyngeal aspirates were collected from children with ALRI, aged < 2 years, who were hospitalized in Children's Hospital of Chongqing Medical University from June 2013 to May 2018. Multiplex PCR was used to detect 16 common respiratory viruses. The epidemiological characteristics of RSV were analyzed. RESULTS: A total of 2 066 hospitalized children with ALRI were enrolled. Among the children, 1 595 (77.20%) tested positive for virus and 826 (39.98%) tested positive for RSV [410(49.6%) positive for RSV-A, 414 (50.1%) positive for RSV-B, and 2 (0.2%) positive for both RSV-A and RSV-B]. RSV-B was the main subtype detected in 2013-2014 and 2016-2017, while RSV-A was the main subtype in 2014-2015 and 2017-2018, and these two subtypes were prevalent in 2015-2016. The highest detection rate of RSV was noted in winter. RSV + human rhinovirus was the most common combination of viruses and was detected in 123 children. These children were more likely to develop wheezing than those with single RSV detected (P=0.030). A total of 298 samples were detected with single RSV, 148 were detected with RSV mixed with other viruses, 389 were detected with other viruses, and 241 were detected negative for viruses. Compared with the other viruses and negative virus groups, the single RSV group had a significantly younger age and significantly higher incidence rates of dyspnea, respiratory failure, and severe lower respiratory tract infection (P < 0.0083). The RSV-A positive group had a significantly higher proportion of boys than the RSV-B positive group (P=0.004), but there were no significant differences in clinical manifestations between the two groups. CONCLUSIONS: In Chongqing in 2013-2018, RSV-A and RSV-B not only can predominate alternately, but also can co-circulate during a season. RSV is the major viral pathogen of hospitalized children with ALRI and can cause severe lower respiratory tract infection. There are no differences in clinical manifestations between children with RSV-A infection and those with RSV-B infection, but boys are more susceptible to RSV-A infection.

Pleiotropic effects of Ubi4, a polyubiquitin precursor required for ubiquitin accumulation, conidiation and pathogenicity of a fungal insect pathogen.

Ubi4 is a polyubiquitin precursor well characterized in yeasts but unexplored in insect mycopathogens. Here, we report that orthologous Ubi4 plays a core role in ubiquitin- and asexual lifestyle-required cellular events in Beauveria bassiana. Deletion of ubi4 led to abolished ubiquitin accumulation, blocked autophagic process, severe defects in conidiation and conidial quality, reduced cell tolerance to oxidative, osmotic, cell wall perturbing and heat-shock stresses, decreased transcript levels of development-activating and antioxidant genes, but light effect on radial growth under normal conditions. The deletion mutant lost insect pathogenicity via normal cuticle infection and was severely compromised in virulence via cuticle-bypassing infection due to a block of dimorphic transition critical for acceleration of host mummification. Proteomic and ubiquitylomic analyses revealed 1081 proteins differentially expressed and 639 lysine residues significantly hyper- or hypo-ubiquitylated in the deletion mutant, including dozens of ubiquitin-activating, conjugating and ligating enzymes, core histones, and many more involved in proteasomes, autophagy-lysosome process and protein degradation. Singular deletions of seven ubiquitin-conjugating enzyme genes exerted differential Ubi4-like effects on conidiation level and conidial traits. These findings uncover an essential role of Ubi4 in ubiquitin transfer cascade and its pleiotropic effects on the in vitro and in vivo asexual cycle of B. bassiana.

Origin and Functional Prediction of Pollen Allergens in Plants.

Pollen allergies have long been a major pandemic health problem for human. However, the evolutionary events and biological function of pollen allergens in plants remain largely unknown. Here, we report the genome-wide prediction of pollen allergens and their biological function in the dicotyledonous model plant Arabidopsis (Arabidopsis thaliana) and the monocotyledonous model plant rice (Oryza sativa). In total, 145 and 107 pollen allergens were predicted from rice and Arabidopsis, respectively. These pollen allergens are putatively involved in stress responses and metabolic processes such as cell wall metabolism during pollen development. Interestingly, these putative pollen allergen genes were derived from large gene families and became diversified during evolution. Sequence analysis across 25 plant species from green alga to angiosperms suggest that about 40% of putative pollen allergenic proteins existed in both lower and higher plants, while other allergens emerged during evolution. Although a high proportion of gene duplication has been observed among allergen-coding genes, our data show that these genes might have undergone purifying selection during evolution. We also observed that epitopes of an allergen might have a biological function, as revealed by comprehensive analysis of two known allergens, expansin and profilin. This implies a crucial role of conserved amino acid residues in both in planta biological function and allergenicity. Finally, a model explaining how pollen allergens were generated and maintained in plants is proposed. Prediction and systematic analysis of pollen allergens in model plants suggest that pollen allergens were evolved by gene duplication and then functional specification. This study provides insight into the phylogenetic and evolutionary scenario of pollen allergens that will be helpful to future characterization and epitope screening of pollen allergens.

Construction of a Stable Expression System Based on the Endogenous hbpB/hbpC Toxin-Antitoxin System of Halomonas bluephagenesis.

Halomonas bluephagenesis is a halophilic bacterium capable of efficiently producing polyhydroxyalkanoates and other valuable chemicals through high salinity open fermentation, offering an appealing platform for next-generation industrial biotechnology. Various techniques have been developed to engineer Halomonas bluephagenesis, each with its inherent shortcomings. Genome editing methods often entail complex and time-consuming processes, while flexible expression systems relying on plasmids necessitate the use of antibiotics. In this study, we developed a stable recombinant plasmid vector, pHbPBC, based on a novel hbpB/hbpC toxin-antitoxin system found within the endogenous plasmid of Halomonas bluephagenesis. Remarkably, pHbPBC exhibited exceptional stability during 7 days of continuous subculture, eliminating the need for antibiotics or other selection pressures. This stability even rivaled genomic integration, all while achieving higher levels of heterologous expression. Our research introduces a novel approach for genetically modifying and harnessing nonmodel halophilic bacteria, contributing to the advancement of next-generation industrial biotechnology.

Wearable sensor-based quantitative gait analysis in Parkinson's disease patients with different motor subtypes.

Gait impairments are among the most common and disabling symptoms of Parkinson's disease and worsen as the disease progresses. Early detection and diagnosis of subtype-specific gait deficits, as well as progression monitoring, can help to implement effective and preventive personalized treatment for PD patients. Yet, the gait features have not been fully studied in PD and its motor subtypes. To characterize comprehensive and objective gait alterations and to identify the potential gait biomarkers for early diagnosis, subtype differentiation, and disease severity monitoring. We analyzed gait parameters related to upper/lower limbs, trunk and lumbar, and postural transitions from 24 tremor-dominant (TD) and 20 postural instability gait difficulty (PIGD) dominant PD patients who were in early stage and 39 matched healthy controls (HC) during the Timed Up and Go test using wearable sensors. Results show: (1) Both TD and PIGD groups showed restricted backswing range in bilateral lower extremities and more affected side (MAS) arm, reduced trunk and lumbar rotation range in the coronal plane, and low turning efficiency. The receiver operating characteristic (ROC) analysis revealed these objective gait features had high discriminative value in distinguishing both PD subtypes from the HC with the area under the curve (AUC) values of 0.7~0.9 (p < 0.01). (2) Subtle but measurable gait differences existed between TD and PIGD patients before the onset of clinically apparent gait impairment. (3) Specific gait parameters were significantly associated with disease severity in TD and PIGD subtypes. Objective gait biomarkers based on wearable sensors may facilitate timely and personalized gait treatments in PD subtypes through early diagnosis, subtype differentiation, and disease severity monitoring.

Using sustained vowels to identify patients with mild Parkinson's disease in a Chinese dataset.

Introduction: Parkinson's disease (PD) is the second most common neurodegenerative disease and affects millions of people. Accurate diagnosis and subsequent treatment in the early stages can slow down disease progression. However, making an accurate diagnosis of PD at an early stage is challenging. Previous studies have revealed that even for movement disorder specialists, it was difficult to differentiate patients with PD from healthy individuals until the average modified Hoehn-Yahr staging (mH&Y) reached 1.8. Recent researches have shown that dysarthria provides good indicators for computer-assisted diagnosis of patients with PD. However, few studies have focused on diagnosing patients with PD in the early stages, specifically those with mH&Y ≤ 1.5. Method: We used a machine learning algorithm to analyze voice features and developed diagnostic models for differentiating between healthy controls (HCs) and patients with PD, and for differentiating between HCs and patients with mild PD (mH&Y ≤ 1.5). The models were independently validated using separate datasets. Results: Our results demonstrate that, a remarkable diagnostic performance of the model in identifying patients with mild PD (mH&Y ≤ 1.5) and HCs, with area under the ROC curve 0.93 (95% CI: 0.851.00), accuracy 0.85, sensitivity 0.95, and specificity 0.75. Conclusion: The results of our study are helpful for screening PD in the early stages in the community and primary medical institutions where there is a lack of movement disorder specialists and special equipment.

Machine-learning model for the prediction of acute orthostatic hypotension after levodopa administration.

BACKGROUND: Levodopa could induce orthostatic hypotension (OH) in Parkinson's disease (PD) patients. Accurate prediction of acute OH post levodopa (AOHPL) is important for rational drug use in PD patients. Here, we develop and validate a prediction model of AOHPL to facilitate physicians in identifying patients at higher probability of developing AOHPL. METHODS: The study involved 497 PD inpatients who underwent a levodopa challenge test (LCT) and the supine-to-standing test (STS) four times during LCT. Patients were divided into two groups based on whether OH occurred during levodopa effectiveness (AOHPL) or not (non-AOHPL). The dataset was randomly split into training (80%) and independent test data (20%). Several models were trained and compared for discrimination between AOHPL and non-AOHPL. Final model was evaluated on independent test data. Shapley additive explanations (SHAP) values were employed to reveal how variables explain specific predictions for given observations in the independent test data. RESULTS: We included 180 PD patients without AOHPL and 194 PD patients with AOHPL to develop and validate predictive models. Random Forest was selected as our final model as its leave-one-out cross validation performance [AUC_ROC 0.776, accuracy 73.6%, sensitivity 71.6%, specificity 75.7%] outperformed other models. The most crucial features in this predictive model were the maximal SBP drop and DBP drop of STS before medication (ΔSBP/ΔDBP). We achieved a prediction accuracy of 72% on independent test data. ΔSBP, ΔDBP, and standing mean artery pressure were the top three variables that contributed most to the predictions across all individual observations in the independent test data. CONCLUSIONS: The validated classifier could serve as a valuable tool for clinicians, offering the probability of a patient developing AOHPL at an early stage. This supports clinical decision-making, potentially enhancing the quality of life for PD patients.

[Research Progress of Carboxymethyl Chitosan-Based Haemostatic Materials and Their Haemostatic Mechanism --Review].

Effective haemostatic materials can quickly control bleeding and achieve the purpose of saving patients' lives. In recent years, chitosan-based haemostatic materials have shown good haemostatic effects, but their application is limited because chitosan is almost insoluble in water. Carboxymethyl chitosan-based haemostatic materials can promote hemostasis by activating red blood cells and aggregating platelets. In addition, carboxymethyl chitosan can bind with Ca2+ to activate platelets and coagulation factors, and start endogenous coagulation pathways, which can adsorb fibrinogen in plasma to promote haemostasis. In this paper, the latest research progress of carboxymethyl chitosan-based haemostatic materials and their haemostatic mechanism were reviewed, in order to further strengthen the understanding of the haemostatic mechanism of carboxymethyl chitosan-based haemostatic materials, and provide new idea for the research and clinical application of carboxymethyl chitosan-based haemostatic materials.

Ga3+ loaded radiation crosslinked gel-Alg-CMC hydrogels for promoting diabetic wound healing.

The metal gallium holds great promise in the fight against infection by disrupting bacterial iron metabolism through a "Trojan horse" technique. It is well worth trying to investigate the potential for gallium-mediated hydrogels for the treatment of infected wounds. In this paper, Ga3+ is innovatively given an important role in hydrogels based on the conventional multi-component hydrogel with metal ion binding gelation strategy. Thus, Ga@Gel-Alg-CMCs hydrogel with broad-spectrum antimicrobial activity is reported on the treatment of infected wounds. The morphology, degradability, and swelling behavior together indicated the excellent physical properties of this hydrogel. Interestingly, in vivo results also showed favorable biocompatibility, slowing down wound infection and promoting diabetic wound healing, making the gallium-doped hydrogel an ideal antimicrobial dressing.

Hemostatic effect and safety evaluation of the absorbable macroporous polysaccharides composite hemostatic material prepared by a green fabrication approach.

Carboxymethyl chitosan is widely used in the medical field such as wound healing and other medical fields. We previously fabricated the absorbable macroporous polysaccharides composite hemostatics (AMPCs) mainly composed of carboxymethyl chitosan which possess excellent hemostatic effect. To further elucidate the impact of CMCTs on the hemostatic effect and biosafety of AMPCs, carboxymethyl chitosan with different properties were used to prepare AMPCs. By comparing the physical and chemical properties, AMPCs performed high water absorption ability, especially Group 1 (swelling ratio reached 5792%), which facilitated the rapid formation of blood clots. It was confirmed by blood clotting index (BCI) and blood coagulation tests in vitro that Group 1 showed a slightly higher coagulation capacity than groups 2 and 3, which may be due to the positive charge on the surface of the cations in the salts attaches to the negative charge on the surface of the red blood cells, an electrostatic neutralization reaction occurs. The biosafety was a preliminary evaluation by implanted AMPCs into the back of Sprague-Dawley rats and the tissue was harvested after feeding for 28 days. The AMPCs exhibited good biosafety for whole blood and major organs during the degradation in vivo: during the degradation of AMPCs, excluding changes in some serum indicators, no tissue necrosis or inflammatory cell infiltration was observed in these organs, either by gross observation or histological analysis. These findings demonstrate that expecting to develop a highly functional and safe hemostatic agent based on Group 1 for rapid hemostasis applications in emergencies.