Sustained release of vascular endothelial growth factor A and basic fibroblast growth factor from nanofiber membranes reduces oxygen/glucose deprivation-induced injury to neurovascular units

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

One memristor–one electrolyte-gated transistor-based high energy-efficient dropout neuronal units

Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.

The Regulatory Role and Mechanism of Circadian Rhythm in Hemoglobin Co-cultured Neurovascular Unit

Objective Intracranial hemorrhage(ICH),the second most common subtype of stroke,exacerbates the disruption of the blood-brain barrier(BBB),leading to vasogenic edema,plasma protein extravasation,and infiltration of neurotoxic substances.The clearance capacity of the brain plays a crucial role in maintaining BBB homeostasis and facilitating patient recovery after hemorrhage.This study aimed to investigate the effect of circadian rhythms on BBB function,neuronal damage,and clearance capabilities.Methods The transwell model and hemoglobin were co-cultured to simulate the BBB environment after ICH.After intervention with different light groups,neuronal apoptosis was determined,glial phagocytosis was analyzed,the expression of endogenous clearing-related proteins aquaporin 4(AQP4)and low-density lipoprotein receptor-related protein 1(LRP1)was detected by western blotting and immunofluorescence dual standard method,and the expression of the tight junction protein occludin and melatonin receptor 1A(MTNR1A)was quantitatively analyzed.Results Circadian rhythms play a key role in maintaining the integrity of the BBB,reducing oxidative stress-induced neuronal damage,and improving microglial phagocytosis.Meanwhile,the expression of occludin and MTNR1A in neurovascular unit(NVU)co-cultured with hemoglobin improved the expression of AQP4 and LRP1,the key proteins in the NVU's endogenous brain clearance system.Conclusion Circadian rhythm(alternating black and white light)protects the NVU BBB function after ICH,promotes the expression of proteins related to the clearance of the hematoma,provides new evidence for the clinical treatment of patients recovering from ICH,and improves the circadian rhythm to promote brain metabolism and hematoma clearance.

Hydrodynamic Assessment of A New Nature-Based Armour Unit on Rubble Mound Breakwater for Coastal Protection

This research proposes a novel nature-based design of a new concrete armour unit for the cover layer of a rubblemoundbreakwater. Armour units are versatile with respect to shape, orientation, surface condition details, and porosity.Therefore, a detailed analysis is required to investigate the exact state of their hydraulic interactions and structuralresponses. In this regard, the performance results of several traditional armour units, including the Antifer cube,Tetrapod, X-block and natural stone, are considered for the first step of this study. Then, the related observed resultsare compared with those obtained for a newly designed (artificial coral) armour unit. The research methodology utilizesthe common wave flume test procedure. Furthermore, several verified numerical models in OpenFOAM code areused to gain the extra required data. The proposed armour is configured to provide an effective shore protection as anenvironmental-friendly coastal structure. Thus it is designed with a main trunk including deep grooves to imitate thetypical geometry of a coral type configuration, so as to attain desirable performance. The observed results and ananalytic hierarchy process (AHP) concept are used to compare the hydraulic performance of the studied traditionaland newly proposed (artificial coral) armour units. The results indicate that the artificial coral armour unit demonstratesacceptable performance. The widely used traditional armour units might be replaced by newer designs for betterwave energy dissipation, and more importantly, for fewer adverse effects on the marine environment.

Analysis of the Erosion-Corrosion Mechanism of the Air Cooler in a Hydrocracking Unit:A Numerical and Experimental Study

Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.

Petrogenesis and Tectonic Implications of the Early Triassic Nianzi Adakitic Granite Unit in the Yanshan Fold and Thrust Belt:New Constraints from U-Pb Geochronology and Sr-Nd-Hf Isotopes

The Nianzi granite unit,which includes the Nianzi,Xiaolianghou and Xiawopu granitic intrusions,is a significant component of the northern part of the North China Craton(NCC)and is situated in the Yanshan fold and thrust belt(YFTB).However,there is still debate regarding the tectonic evolutionary history of the YFTB during the late Permian to Triassic period,specifically regarding the timing of subduction and collision between the NCC and the Paleo-Asian Ocean.The Nianzi granite unit exhibits unique petrological,geochronological and geochemical signatures that shed light on the tectonic evolutionary history of the YFTB.This study presents detailed petrology,whole-rock geochemistry,together with Sr-Nd isotopic,zircon U-Pb dating and Lu-Hf isotopic data of the granites within the Nianzi granite unit.Our findings demonstrate that the granites primarily consist of subhedral K-feldspar,plagioclase,quartz,minor biotite and hornblende,with accessory titanite,apatite,magnetite and zircon.Zircon U-Pb dating indicates that the Xiaolianghou granite was emplaced at 247.5±0.62 Ma.Additionally,the adakitic characteristics of the Nianzi,Xiawopu and Xiaolianghou granitic intrusions,such as high Sr and Ba contents and high ratios of Sr/Y and(La/Yb)N,combined with negative Sr-Nd and Lu-Hf isotopes(87Sr/86Sr)i=0.705681–0.7057433,εNd(t)=−21.98 to−20.97,zirconεHf(t)=−20.26 to−9.92,as well as the I-type granite features of high SiO_(2),Na_(2)O and K_(2)O/Na_(2)O ratios,enriched Rb,K,Sr and Ba,along with depleted Th,U,Nb,Ta,P and Ti,suggest that the Nianzi granitic unit was mainly derived from the partial melting of a thickened lower crust containing hydrous,calc-alkaline to high-K calc-alkaline,mafic to intermediate metamorphic rocks.In light of these parameters,we further integrate our data with previous studies and conclude that the Nianzi granitic unit was generated in a post-collisional extensional environment during the Early Triassic.

Bionic lightweight design of limb leg units for hydraulic quadruped robots by additive manufacturing and topology optimization

Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.

The neurovascular unit-on-a-chip:modeling ischemic stroke to stem cell therapy

The neurovascular unit and stem cell therapy in ischemic stroke:Ischemic stroke,accounts for approximately 85% of all stroke incidents and is a major global health burden.It is the leading cause of disability and death worldwide,posing immense societal and economic challenges due to the long-term care required for stro ke survivors and the significant healthcare costs associated with its treatment and management(Amarenco et al.,2009).

An Interpretable Light Attention-Convolution-Gate Recurrent Unit Architecture for the Highly Accurate Modeling of Actual Chemical Dynamic Processes

To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.

Geologic characteristics,exploration and production progress of shale oil and gas in the United States:An overview

We present a systematic summary of the geological characteristics,exploration and development history and current state of shale oil and gas in the United States.The hydrocarbon-rich shales in the major shale basins of the United States are mainly developed in six geological periods:Middle Ordovician,Middle-Late Devonian,Early Carboniferous(Middle-Late Mississippi),Early Permian,Late Jurassic,and Late Cretaceous(Cenomanian-Turonian).Depositional environments for these shales include intra-cratonic basins,foreland basins,and passive continental margins.Paleozoic hydrocarbon-rich shales are mainly developed in six basins,including the Appalachian Basin(Utica and Marcellus shales),Anadarko Basin(Woodford Shale),Williston Basin(Bakken Shale),Arkoma Basin(Fayetteville Shale),Fort Worth Basin(Barnett Shale),and the Wolfcamp and Leonardian Spraberry/Bone Springs shale plays of the Permian Basin.The Mesozoic hydrocarbon-rich shales are mainly developed on the margins of the Gulf of Mexico Basin(Haynesville and Eagle Ford)or in various Rocky Mountain basins(Niobrara Formation,mainly in the Denver and Powder River basins).The detailed analysis of shale plays reveals that the shales are different in facies and mineral components,and"shale reservoirs"are often not shale at all.The United States is abundant in shale oil and gas,with the in-place resources exceeding 0.246×10^(12)t and 290×10^(12)m^(3),respectively.Before the emergence of horizontal well hydraulic fracturing technology to kick off the"shale revolution",the United States had experienced two decades of exploration and production practices,as well as theory and technology development.In 2007-2023,shale oil and gas production in the United States increased from approximately 11.2×10^(4)tons of oil equivalent per day(toe/d)to over 300.0×10^(4)toe/d.In 2017,the shale oil and gas production exceeded the conventional oil and gas production in the country.In 2023,the contribution from shale plays to the total U.S.oil and gas production remained above 60%.The development of shale oil and gas has largely been driven by improvements in drilling and completion technologies,with much of the recent effort focused on“cube development”or“co-development”.Other efforts to improve productivity and efficiency include refracturing,enhanced oil recovery,and drilling of“U-shaped”wells.Given the significant resources base and continued technological improvements,shale oil and gas production will continue to contribute significant volumes to total U.S.hydrocarbon production.

Hounsfield units in assessing bone mineral density in ankylosing spondylitis patients with cervical fracture-dislocation

BACKGROUND Cervical spine fracture-dislocations in patients with ankylosing spondylitis(AS)are mostly unstable and require surgery.However,osteoporosis,one of the comorbidities for AS,could lead to detrimental prognoses.There are few accurate assessments of bone mineral density in AS patients.AIM To analyze Hounsfield units(HUs)for assessing bone mineral density in AS patients with cervical fracture-dislocation.METHODS The HUs from C2 to C7 of 51 patients obtained from computed tomography(CT)scans and three-dimensional reconstruction of the cervical spine were independently assessed by two trained spinal surgeons and statistically analyzed.Inter-reader reliability and agreement were assessed by interclass correlation coefficient.RESULTS The HUs decreased gradually from C2 to C7.The mean values of the left and right levels were significantly higher than those in the middle.Among the 51 patients,25 patients(49.02%)may be diagnosed with osteoporosis,and 16 patients(31.37%)may be diagnosed with osteopenia.CONCLUSION The HUs obtained by cervical spine CT are feasible for assessing bone mineral density with excellent agreement in AS patients with cervical fracture-dislocation.

Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication space.Considering that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of B5G.The multiwatermarking process employs spread transform dither modulation.During the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading vectors.Consequently,multiple watermarks can be simultaneously embedded into the same position of a multimedia signal.Moreover,the multiple watermarks can be extracted without affecting one another during the extraction process.We analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.

Risk factors for intensive-care-unit-acquired weakness

Wang et al reported 1063 cases from the initial 14 d of intensive care unit(ICU)stay,and analyzed relevant data such as age,comorbidities,recent dosages,vapor pressure dosages,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,which are closely related to ICU-acquired weakness(ICUAW).It is suggested that the length of ICU stay and the duration of mechanical ventilation are the main factors.ICU-AW is the most common neuromuscular injury in the ICU,which affects clinical progression and outcomes of patients.This manuscript helps to improve the early recognition of ICU-AW,thereby reducing mortality and improving prognosis.

Improved Unit Commitment with Accurate Dynamic Scenarios Clustering Based on Multi-Parametric Programming and Benders Decomposition

Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

Characteristics of patients with Wilson disease in the United States: An insurance claims database study

BACKGROUND Wilson disease(WD)is a progressive,potentially fatal degenerative disease affecting the liver and central nervous system.Given its low prevalence,collecting data on large cohorts of patients with WD is challenging.Comprehensive insur-ance claims databases provide powerful tools to collect retrospective data on large numbers of patients with rare diseases.AIM To describe patients with WD in the United States,their treatment and clinical outcome,using a large insurance claims database.METHODS This retrospective,longitudinal study was performed in the Clarivate Real-World Data Product database.All patients with≥2 claims associated with an Interna-tional Classification of Diseases 10(ICD-10)diagnostic code for WD(E83.01)between 2016 and 2021 were included and followed until death or study end.Patients were divided into two groups by whether or not they were documented to have received a specific treatment for WD.Clinical manifestations,hospital-isations,liver transplantation and death were documented.RESULTS Overall,5376 patients with an ICD-10 diagnostic code for WD were identified.The mean age at inclusion was 41.2 years and 52.0%were men.A specific WD treatment was documented for 885 patients(15.1%),although the number of patients taking zinc salts may be underestimated due to over the counter purchase.At inclusion,the mean age of patients with a documented treatment was 36.6±17.8 years vs 42.2±19.6 years in those without a documented treatment.During follow-up,273 patients(5.1%)died.Compared with the American general population,the standardised mortality ratio was 2.19.The proportion of patients with a documented WD-specific treatment who died during follow-up was 4.0%and the mean age at death 52.7 years.CONCLUSION Patients treated for WD in the United States had an excess early mortality compared with the American population.These findings indicate that there is a significant unmet need for effective treatment for WD in the United States.

Evaluation of the effectiveness of preventive nursing measures for pressure injuries in patients in the neurology intensive care unit

BACKGROUND Patients in neurology intensive care units(ICU)are prone to pressure injuries(PU)due to factors such as severe illness,long-term bed rest,and physiological dysfunction.PU not only causes pain and complications to patients,but also increases medical burden,prolongs hospitalization time,and affects the recovery process.AIM To evaluate and optimize the effectiveness of pressure injury prevention nursing measures in neurology ICU patients.METHODS A retrospective study was conducted,and 60 patients who were admitted to the ICU of the Department of Neurology were selected and divided into an observation group and a control group according to the order of admission,with 30 people in each group.The observation group implemented pressure injury prevention and nursing measures,while the control group adopted routine care.RESULTS Comparison between observation and control groups following pressure injury prevention nursing intervention revealed significantly lower incidence rates in the observation group compared to the control group at 48 h(8.3%vs 26.7%),7 d(16.7%vs 43.3%),and 14 d(20.0%vs 50.0%).This suggests a substantial reduction in pressure injury incidence in the observation group,with the gap widening over time.Additionally,patients in the observation group exhibited quicker recovery,with a shorter average time to get out of bed(48 h vs 72 h)and a shorter average length of stay(12 d vs 15 d)compared to the control group.Furthermore,post-intervention,patients in the observation group reported significantly improved quality of life scores,including higher scores in body satisfaction,feeling and function,and comfort(both psychological and physiological),indicating enhanced overall well-being and comfort following the implementation of pressure injury prevention nursing measures.CONCLUSION Implementing pressure injury preventive care measures for neurology ICU patients will have better results.