Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

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.

Intensive care unit-acquired weakness:Unveiling significant risk factors and preemptive strategies through machine learning

This editorial discusses an article recently published in the World Journal of Clinical Cases,focusing on risk factors associated with intensive care unit-acquired weak-ness(ICU-AW).ICU-AW is a serious neuromuscular complication seen in criti-cally ill patients,characterized by muscle dysfunction,weakness,and sensory impairments.Post-discharge,patients may encounter various obstacles impacting their quality of life.The pathogenesis involves intricate changes in muscle and nerve function,potentially leading to significant disabilities.Given its global significance,ICU-AW has become a key research area.The study identified critical risk factors using a multilayer perceptron neural network model,highlighting the impact of intensive care unit stay duration and mechanical ventilation duration on ICU-AW.Recommendations were provided for preventing ICU-AW,empha-sizing comprehensive interventions and risk factor mitigation.This editorial stresses the importance of external validation,cross-validation,and model tran-sparency to enhance model reliability.Moreover,the application of machine learning in clinical medicine has demonstrated clear benefits in improving disease understanding and treatment decisions.While machine learning presents oppor-tunities,challenges such as model reliability and data management necessitate thorough validation and ethical considerations.In conclusion,integrating ma-chine learning into healthcare offers significant potential and challenges.Enhan-cing data management,validating models,and upholding ethical standards are crucial for maximizing the benefits of machine learning in clinical practice.

Evaluating neuromuscular electrical stimulation for preventing and managing intensive care unit-acquired weakness:Current evidence and future directions

Intensive care unit-acquired weakness(ICU-AW)is a prevalent issue in critical care,leading to significant muscle atrophy and functional impairment.Aiming to address this,Neuromuscular Electrical Stimulation(NMES)has been explored as a therapy.This systematic review assesses NMES's safety and effectiveness in enhancing functional capacity and mobility in pre-and post-cardiac surgery patients.NMES was generally safe and feasible,with intervention sessions varying in frequency and duration.Improvements in muscle strength and 6-minute walking test distances were observed,particularly in preoperative settings,but postoperative benefits were inconsistent.NMES showed promise in preventing muscle loss and improving strength,although its impact on overall functional capacity remained uncertain.Challenges such as short ICU stays and body composition affecting NMES efficacy were noted.NMES also holds potential for other conditions like cerebral palsy and stroke.Further research is needed to optimize NMES protocols and better understand its full benefits in preventing ICU-AW and improving patient outcomes.

Pioneering role of machine learning in unveiling intensive care unitacquired weakness

In the research published in the World Journal of Clinical Cases,Wang and Long conducted a quantitative analysis to delineate the risk factors for intensive care unit-acquired weakness(ICU-AW)utilizing advanced machine learning methodologies.The study employed a multilayer perceptron neural network to accurately predict the incidence of ICU-AW,focusing on critical variables such as ICU stay duration and mechanical ventilation.This research marks a significant advancement in applying machine learning to clinical diagnostics,offering a new paradigm for predictive medicine in critical care.It underscores the importance of integrating artificial intelligence technologies in clinical practice to enhance patient management strategies and calls for interdisciplinary collaboration to drive innovation in healthcare.

Predicting intensive care unit-acquired weakness:A multilayer perceptron neural network approach

In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.

Unveiling significant risk factors for intensive care unit-acquired weakness:Advancing preventive care

In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World Journal of Clinical Cases.Intensive care unit-acquired weakness(ICU-AW)is a debilitating condition that affects critically ill patients,with significant implications for patient outcomes and their quality of life.This study explored the use of artificial intelligence and machine learning techniques to predict ICU-AW occurrence and identify key risk factors.Data from a cohort of 1063 adult intensive care unit(ICU)patients were analyzed,with a particular emphasis on variables such as duration of ICU stay,duration of mechanical ventilation,doses of sedatives and vasopressors,and underlying comorbidities.A multilayer perceptron neural network model was developed,which exhibited a remarkable impressive prediction accuracy of 86.2%on the training set and 85.5%on the test set.The study highlights the importance of early prediction and intervention in mitigating ICU-AW risk and improving patient outcomes.

Machine learning insights on intensive care unit-acquired weakness

Intensive care unit-acquired weakness(ICU-AW)significantly hampers patient recovery and increases morbidity.With the absence of established preventive strategies,this study utilizes advanced machine learning methodologies to unearth key predictors of ICU-AW.Employing a sophisticated multilayer perceptron neural network,the research methodically assesses the predictive power for ICU-AW,pinpointing the length of ICU stay and duration of mechanical ventilation as pivotal risk factors.The findings advocate for minimizing these elements as a preventive approach,offering a novel perspective on combating ICU-AW.This research illuminates critical risk factors and lays the groundwork for future explorations into effective prevention and intervention strategies.

Advancing critical care recovery:The pivotal role of machine learning in early detection of intensive care unit-acquired weakness

This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient recovery.Highlightingthe paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's impact.Innovatively,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting ICU-AWrisk.This advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model applicability.The editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.

Intensive care unit-acquired weakness–preventive,and therapeutic aspects;future directions and special focus on lung transplantation

In this editorial,comments are made on an interesting article in the recent issue of the World Journal of Clinical Cases by Wang and Long.The authors describe the use of neural network model to identify risk factors for the development of intensive care unit(ICU)-acquired weakness.This condition has now become common with an increasing number of patients treated in ICUs and continues to be a source of morbidity and mortality.Despite identification of certain risk factors and corrective measures thereof,lacunae still exist in our understanding of this clinical entity.Numerous possible pathogenetic mechanisms at a molecular level have been described and these continue to be increasing.The amount of retrievable data for analysis from the ICU patients for study can be huge and enormous.Machine learning techniques to identify patterns in vast amounts of data are well known and may well provide pointers to bridge the knowledge gap in this condition.This editorial discusses the current knowledge of the condition including pathogenesis,diagnosis,risk factors,preventive measures,and therapy.Furthermore,it looks specifically at ICU acquired weakness in recipients of lung transplantation,because–unlike other solid organ transplants-muscular strength plays a vital role in the preservation and survival of the transplanted lung.Lungs differ from other solid organ transplants in that the proper function of the allograft is dependent on muscle function.Muscular weakness especially diaphragmatic weakness may lead to prolonged ventilation which has deleterious effects on the transplanted lung–ranging from ventilator associated pneumonia to bronchial anastomotic complications due to prolonged positive pressure on the anastomosis.

Clinical Effect of Modified Shengyang Yiwei Decoction in the Treatment of Diarrhea-Predominant Irritable Bowel Syndrome due to Spleen and Stomach Weakness

Objective:To explore the therapeutic effect of Shengyang Yiwei Decoction in patients with diarrhea-predominant irritable bowel syndrome(IBS)due to spleen and stomach weakness.Methods:40 patients with diarrhea-predominant IBS who were treated from April 2018 to April 2020 were taken as samples.TCM(traditional Chinese medicine)syndrome differentiation found that they were all due to spleen and stomach weakness.They were randomly divided into two groups.Group A was treated with modified prescriptions of Shengyang Yiwei Decoction,while Group B was treated with Western medicine.The therapeutic effects in the two groups were compared.Results:The treatment efficacy in Group A was higher than that in Group B(P<0.05);the symptom scores of Group A such as loose stools,chills,physical weakness,poor appetite,and abdominal distension after meals were all lower than those in Group B(P<0.05);the SF-36(36-Item Short Form Health Survey)scores of patients with diarrhea-predominant IBS in Group A were higher than those in Group B(P<0.05);the treatment satisfaction of Group A was higher than that of Group B(P<0.05).Conclusion:Treatment of diarrhea-predominant IBS patients with spleen and stomach weakness by Shengyang Yiwei Decoction can promote the disappearance of gastrointestinal discomfort symptoms,improve the quality of life,and enhance treatment efficacy.Hence,it is an efficient and feasible treatment for diarrhea-predominant IBS due to spleen and stomach weakness.

血清sTWEAK、Netrin-1联合APACHEⅡ评分对重型颅脑损伤患者术后预后不良的预测价值

目的探讨血清可溶性肿瘤坏死因子样凋亡弱诱导因子(sTWEAK)、神经轴突导向因子-1(Netrin-1)联合急性生理学与慢性健康状况评分系统Ⅱ(APACHEⅡ)评分对重型颅脑损伤患者术后预后不良的预测价值。方法选取2020年6月至2022年6月该院收治的120例重型颅脑损伤患者,根据术后30 d预后情况分为预后良好组和预后不良组。对比两组血清sTWEAK、Netrin-1水平及APACHEⅡ评分。采用单因素和多因素Logistic回归分析重型颅脑损伤患者术后预后不良的影响因素,并据以构建血清sTWEAK、Netrin-1及APACHEⅡ评分联合应用的预测模型,受试者工作特征(ROC)曲线分析血清sTWEAK、Netrin-1水平及APACHEⅡ评分对重型颅脑损伤患者术后预后不良的预测价值。结果预后不良组的重症监护室居住时间长于预后良好组,白蛋白水平、入院时格拉斯哥昏迷评分法评分和血清Netrin-1水平低于预后良好组,多发脑挫裂伤占比、机械通气占比、入院时APACHEⅡ评分和血清sTWEAK、血清肌酐、血尿素氮水平均高于预后良好组,差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,多发脑挫裂伤、Netrin-1水平降低、入院时APACHEⅡ评分升高、sTWEAK水平升高为重型颅脑损伤患者术后预后不良的危险因素(P<0.05)。ROC曲线分析结果显示,血清sTWEAK、Netrin-1及APACHEⅡ评分3个指标单独及联合应用时曲线下面积及其95%CI分别为0.742(0.552~0.925)、0.731(0.488~0.963)、0.714(0.502~0.911)、0.882(0.795~0.947)。结论血清sTWEAK、Netrin-1联合APACHEⅡ评分对重型颅脑损伤患者术后预后不良具有较好的预测价值,可为临床治疗方案的制订提供参考。

自发性急性脑出血患者血浆sCD163/sTWEAK比值与预后的关系

目的探究自发性急性脑出血(ACH)患者血浆可溶性CD163(sCD163)/可溶性肿瘤坏死因子样凋亡弱诱导因子(sTWEAK)比值与预后的关系。方法纳入ACH患者90例作为病例组,根据格拉斯哥预后评分将病例组分为预后不良组(38例)和预后良好组(52例);另选取同期体检健康者45例为对照组。酶联免疫吸附试验检测血浆sCD163、sTWEAK水平并计算sCD163/sTWEAK比值。分析血浆sCD163、sTWEAK水平及sCD163/sTWEAK比值与临床资料的相关性;Logistic回归分析ACH患者预后不良的影响因素;受试者工作特征(ROC)曲线分析sCD163/sTWEAK比值对ACH患者预后不良的预测价值。结果病例组血浆sCD163、sTWEAK水平及sCD163/sTWEAK比值均显著高于对照组;预后良好组上述指标均低于预后不良组(P<0.05)。预后良好组血肿体积、美国国立卫生研究院卒中量表(NIHSS)评分、高血压及幕下出血比例均低于预后不良组,低密度脂蛋白胆固醇(LDL-C)高于预后不良组(P<0.05)。相关性分析表明,血浆sCD163、sTWEAK水平及sCD163/sTWEAK比值与出血部位、血肿体积、NIHSS评分、白细胞计数、血小板计数、中性粒细胞/淋巴细胞比值(NLR)呈正相关(P<0.05)。Logistic回归分析显示,sCD163/sTWEAK比值、出血部位、血肿体积、NIHSS评分为ACH患者预后不良的影响因素(P<0.05)。ROC曲线结果表明,sCD163/sTWEAK比值评估ACH患者预后不良的AUC为0.850,敏感度和特异度分别为86.84%和69.23%。结论sCD163/sTWEAK比值在ACH患者血浆中水平较高,并与预后不良有关,该值对此类患者的预后有一定预测价值。

注意缺陷多动障碍患儿血清ACE2,TWEAK和CCL5水平检测及诊断价值研究

目的 探究血清血管紧张素转换酶2(angiotensin-converting enzyme 2,ACE2),细胞因子肿瘤坏死因子样细胞凋亡弱诱导因子(tumor necrosis factor-like weak inducer of apoptosis,TWEAK)和CC趋化因子配体5(CC motif chemokine ligand 5,CCL5)水平在注意缺陷多动障碍(attention deficit hyperactivity disorder,ADHD)患儿诊断、病情严重程度评估中的价值。方法 选取2022年10月~2023年10月在河北省儿童医院就诊的125例ADHD患儿记为ADHD组,另选105例在河北省妇幼保健中心体检的健康儿童为对照组,根据临床总体印象严重程度量表(CGI-S)将患儿分为轻中度组(n=83)和重度组(n=42)。ELISA方法检测血清ACE2,TWEAK,CCL5,促黄体生成素(LH)和催乳素(PRL)水平,联合型瑞文测验(CRT)和Conners父母症状问卷(PSQ)对患儿认知和行为状况进行评分。Spearman相关性分析重度组血清ACE2,TWEAK,CCL5与CGI-S,CRT,PSQ评分的相关性;受试者工作特征(ROC)曲线分析ACE2,TWEAK,CCL5对ADHD及严重程度的诊断价值。结果 ADHD患儿血清ACE2(284.35±92.34 pg/ml),TWEAK(2.56±0.76 pg/ml)水平低于对照组(379.23±106.28 pg/ml,3.52±1.12 pg/ml),CCL5水平(7.36±2.37ng/ml)高于对照组(5.24±1.63 ng/ml),差异具有统计学意义(t=7.244,7.703,7.753,均P<0.05);重度组患儿CRT,血清ACE2,TWEAK水平低于轻中度组(t=5.318,6.686,6.490),而PSQ,CCL5水平较高于轻中度组(t=5.220,6.134),差异具有统计学意义(均P<0.05);Spearman相关性分析结果显示,重度组患儿血清ACE2,TWEAK水平与CGI-S,PSQ评分负相关(r=-0.432,-0.453;-0.421,-0.426,均P<0.001),与CRT评分呈正相关(r=0.427,0.418,均P<0.001);CCL5与CGI-S,PSQ评分呈正相关(r=0.421,0.433,均P<0.001),与CRT评分呈负相关(r=-0.446,P<0.001)。血清ACE2,TWEAK和CCL5诊断ADHD发生的AUC分别为0.814,0.803和0.807,三者联合诊断的AUC为0.945,优于各自单独诊断(Z=5.439,4.258,5.576,均P<0.001);血清ACE2,TWEAK,CCL5诊断重度ADHD的AUC分别为0.853,0.796和0.805,三者联合诊断的AUC为0.930,优于各自单独诊断(Z=2.604,3.851,3.567,均P<0.001)。结论 血清ACE2,TWEAK在ADHD患儿血清中低表达,而CCL5高表达,三者表达水平具有相关性,并且诊断ADHD发生和严重程度具有较高的价值。

Eccentric exercise-induced muscle weakness abolishes sex differences in fatigability during sustained submaximal isometric contractions

Background:Females are typically less fatigable than males during sustained isometric contractions at lower isometric contraction intensities.This sex difference in fatigability becomes more variable during higher intensity isometric and dynamic contractions.While less fatiguing than isometric or concentric contractions,eccentric contractions induce greater and longer lasting impairments in force production.However,it is not clear how muscle weakness influences fatigability in males and females during sustained isometric contractions.Methods:We investigated the effects of eccentric exercise-induced muscle weakness on time to task failure(TTF)during a sustained submaximal isometric contraction in young(18-30 years)healthy males(n=9)and females(n=10).Participants performed a sustained isometric contraction of the dorsiflexors at 35°plantar flexion by matching a 30%maximal voluntary contraction(MVC)torque target until task failure(i.e.,falling below 5%of their target torque for>2 s).The same sustained isometric contraction was repeated 30 min after 150 maximal eccentric contractions.Agonist and antagonist activation were assessed using surface electromyography over the tibialis anterior and soleus muscles,respectively.Results:Males were~41%stronger than females.Following eccentric exercise both males and females experienced an~20%decline in maximal voliuntary contraction torque.TTF was-34%longer in females than males prior to eccentic exercise-induced muscle weakness.However,following eccentric exercise-induced muscle weakness,this sex-related difference was abolished,with both groups having an"45%shorter TTF.Notably,there was~100%greater antagonist activation in the female group during the sustained isometric contraction following exercise-induced weakness as compared to the males.Conclusion:This increase in antagonist activation disadvantaged females by decreasing their TTF,resulting in a blunting of their typical fatigability advantage over males.

A robust & weak-nucleophilicity electrocatalyst with an inert response for chlorine ion oxidation in large-current seawater electrolysis

Seawater splitting into hydrogen,a promising technology,is seriously limited by the durability and tolerance of electrocatalysts for chlorine ions in seawater at large current densities due to chloride oxidation and corrosion.Here,we present a robust and weak-nucleophilicity nickel-iron hydroxide electrocatalyst with excellent selectivity for oxygen evolution and an inert response for chlorine ion oxidation which are key and highly desired for efficient seawater electrolysis.Such a weak-nucleophilicity electrocatalyst can well match with strong-nucleophilicity OH-compared with the weak-nucleophilicity Cl^(-),resultantly,the oxidation of OH-in electrolyte can be more easily achieved relative to chlorine ion oxidation,confirmed by ethylenediaminetetraacetic acid disodium probing test.Further,no strongly corrosive hypochlorite is produced when the operating voltage reaches about 2.1 V vs.RHE,a potential that is far beyond the thermodynamic potential of chlorine ion oxidatio n.This concept and approach to reasonably designing weaknucleophilicity electrocatalysts that can greatly avoid chlorine ion oxidation under alkaline seawater environments can push forward the seawater electrolysis technology and also accelerate the development of green hydrogen technique.

Ankle and toe weakness caused by calcified ligamentum flavum cyst: A case report

BACKGROUND Ligamentum flavum cysts,which are most common in mobile junctional levels of the spine,can be a rare cause of spinal stenosis.There have been several case reports of ligamentum flavum cysts.However,there is yet to be a documented case report of a calcified ligamentum flavum cyst.Herein,we report the first case of a calcified ligamentum flavum cyst causing ankle and toe weakness.CASE SUMMARY A 66-year-old male visited our hospital complaining of claudication as well as thigh and calf pain in his left leg,all beginning two weeks prior.Physical examination revealed motor weakness of the left ankle dorsiflexion and great toe dorsiflexion.Lumbar spinal computed tomography scans showed spinal stenosis combined with a calcified mass at the left side of the L4-5 level.Magnetic reso-nance imaging showed dural sac compression caused by the calcified mass at the left ligamentum flavum of the L4-5 level.We performed decompressive laminectomy and excision of the calcified mass combined with posterior lumbar interbody fusion at the L4-5 level.Intra-operatively,we found a firm and nodule like mass originating from the ventral surface of ligamentum flavum.Pathological examination suggested a calcified pseudocyst without a capsular lining.After the operation,the patient’s motor weakness in the ankle and great toe improved gradually.CONCLUSION The patient’s ankle and great toe weakness were improved successfully after surgical removal of the calcified cyst.

血清Gal-3、TWEAK对精神分裂症的诊断价值及与精神症状严重程度的关系

目的研究血清半乳糖凝集素3(Gal-3)、肿瘤坏死因子样弱凋亡诱导因子(TWEAK)对精神分裂症的诊断价值及与精神症状严重程度的关系。方法选取2019年3月至2021年3月在该院诊治的96例精神分裂症患者作为病例组,以同期60例健康体检者为对照组,进行回顾性分析。采用酶联免疫吸附试验检测血清Gal-3、TWEAK水平。采用Pearson相关分析血清Gal-3、TWEAK水平与临床指标的相关性;采用多因素Logistic回归分析影响精神分裂症发生的因素;采用受试者工作特征(ROC)曲线分析血清Gal-3、TWEAK单项及联合检测对精神分裂症的诊断价值。结果观察组PANSS评分总分、阳性症状评分、阴性症状评分、一般精神病理学症状评分及血清Gal-3、TWEAK水平均高于对照组,差异均有统计学意义(P<0.001)。血清Gal-3、TWEAK水平与PANSS评分总分、阳性症状评分、阴性症状评分、一般精神病理学症状评分呈正相关(P<0.001)。PANSS评分总分、阳性症状评分、一般精神病理学症状评分升高及血清Gal-3、TWEAK水平升高均是精神分裂症发生的独立危险因素(P<0.001)。血清Gal-3、TWEAK联合检测诊断精神分裂症的曲线下面积为0.870(95%CI:0.831~0.919),明显高于血清Gal-3、TWEAK单项检测诊断精神分裂症的AUC[0.812(95%CI:0.769~0.847)、0.820(95%CI:0.771~0.852)],差异均有统计学意义(Z=4.345,P<0.001;Z=4.010,P=0.002)。结论精神分裂症患者血清Gal-3、TWEAK水平升高,二者与精神症状严重程度有关,血清Gal-3、TWEAK联合检测对精神分裂症具有较高的诊断价值。

Ultrahigh-brightness 50 MeV electron beam generation from laser wakefield acceleration in a weakly nonlinear regime

We propose an efficient scheme to produce ultrahigh-brightness tens of MeV electron beams by designing a density-tailored plasma to induce a wakefield in the weakly nonlinear regime with a moderate laser energy of 120 mJ.In this scheme,the second bucket of the wakefield can have a much lower phase velocity at the steep plasma density down-ramp than the first bucket and can be exploited to implement longitudinal electron injection at a lower laser intensity,leading to the generation of bright electron beams with ultralow emittance together with low energy spread.Three-dimensional particle-in-cell simulations are carried out and demonstrate that high-quality electron beams with a peak energy of 50 MeV,ultralow emittance of28 nm rad,energy spread of 1%,charge of 4.4 pC,and short duration less than 5 fs can be obtained within a 1-mm-long tailored plasma density,resulting in an ultrahigh six-dimensional brightness B6D,n of2×1017 A/m2/0.1%.By changing the density parameters,tunable bright electron beams with peak energies ranging from 5 to 70 MeV,a small emittance of B0.1 mm mrad,and a low energy spread at a few-percent level can be obtained.These bright MeV-class electron beams have a variety of potential applications,for example,as ultrafast electron probes for diffraction and imaging,in laboratory astrophysics,in coherent radiation source generation,and as injectors for GeV particle accelerators.

Measuring small longitudinal phase shifts via weak measurement amplification

Weak measurement amplification,which is considered as a very promising scheme in precision measurement,has been applied to various small physical quantities estimations.Since many physical quantities can be converted into phase signals,it is interesting and important to consider measuring small longitudinal phase shifts by using weak measurement.Here,we propose and experimentally demonstrate a novel weak measurement amplification-based small longitudinal phase estimation,which is suitable for polarization interferometry.We realize one order of magnitude amplification measurement of a small phase signal directly introduced by a liquid crystal variable retarder and show that it is robust to the imperfection of interference.Besides,we analyze the effect of magnification error which is never considered in the previous works,and find the constraint on the magnification.Our results may find important applications in high-precision measurements,e.g.,gravitational wave detection.