Identification and Analysis of Human-Exoskeleton Coupling Parameters in Lower Extremities.

This paper proposed linear and non-linear models for predicting human-exoskeleton coupling forces to enhance the studies of human-exoskeleton coupling dynamics. Then the parameters of these models were identified with a newly designed platform and the help of ten adult male and ten adult female volunteers (Age: 23.65 ±4.03 years, Height: 165.60 ±8.32 mm, Weight: 62.35 ±14.09 kg). Comparing the coupling force error predicted by the models with experimental measurements, one obtained a more accurate and robust prediction of the coupling forces with the non-linear model. Moreover, statistical analysis of the experimental data was performed to reveal the correlation between the coupling parameters and coupling positions and looseness. Finally, backpropagation (BP) neural network and Gaussian Process Regression (GPR) were used to predict the human-exoskeleton coupling parameters. The significance of each input parameter to the human-exoskeleton coupling parameters was assessed by analyzing the sensitivity of GPR performance to its inputs. The novelty and contribution are the establishment of the non-linear coupling model, the design of the coupling experimental platform and a regression model which provides a possibility to obtain human-exoskeleton without experimental measurement and identification. Based on this work, one can optimize control algorithm and design comfortable human-exoskeleton interaction.

Coronary hemodynamic simulation study.

In this paper, a two-way fluid-structure coupling model is developed to simulate and analyze the hemodynamic process based on dynamic coronary angiography, and examine the influence of different hemodynamic parameters on coronary arteries in typical coronary stenosis lesions. Using the measured FFR pressure data of a patient, the pressure-time function curve is fitted to ensure the accuracy of the boundary conditions. The average error of the simulation pressure results compared to the test data is 6.74%. In addition, the results related to blood flow, pressure contour and wall shear stress contour in a typical cardiac cycle are obtained by simulation analysis. These results are found to be in good agreement with the laws of the real cardiac cycle, which verifies the rationality of the simulation. In conclusion, based on the modeling and hemodynamic simulation analysis process of dynamic coronary angiography, this paper proposes a method to assist the analysis and evaluation of coronary hemodynamic and functional parameters, which has certain practical significance.

Multivariable machine learning models for clinical prediction of subsequent hip fractures in older people using the Chinese population database.

PURPOSE: This study aimed to develop and validate clinical prediction models using machine learning (ML) algorithms for reliable prediction of subsequent hip fractures in older individuals, who had previously sustained a first hip fracture, and facilitate early prevention and diagnosis, therefore effectively managing rapidly rising healthcare costs in China. METHODS: Data were obtained from Grade A Tertiary hospitals for older patients (age ≥ 60 years) diagnosed with hip fractures in southwest China between 1 January 2009 and 1 April 2020. The database was built by collecting clinical and administrative data from outpatients and inpatients nationwide. Data were randomly split into training (80%) and testing datasets (20%), followed by six ML-based prediction models using 19 variables for hip fracture patients within 2 years of the first fracture. RESULTS: A total of 40,237 patients with a median age of 66.0 years, who were admitted to acute-care hospitals for hip fractures, were randomly split into a training dataset (32,189 patients) and a testing dataset (8,048 patients). Our results indicated that three of our ML-based models delivered an excellent prediction of subsequent hip fracture outcomes (the area under the receiver operating characteristics curve: 0.92 (0.91-0.92), 0.92 (0·92-0·93), 0.92 (0·92-0·93)), outperforming previous prediction models based on claims and cohort data. CONCLUSIONS: Our prediction models identify Chinese older people at high risk of subsequent hip fractures with specific baseline clinical and demographic variables such as length of hospital stay. These models might guide future targeted preventative treatments.

Multi-omics analysis reveals GAPDH posttranscriptional regulation of IFN-γ and PHGDH as a metabolic checkpoint of microglia polarization.

A "switch" in the metabolic pattern of microglia is considered to be required to meet the metabolic demands of cell survival and functions. However, how metabolic switches regulate microglial function remains controversial. We found here that exposure to amyloid-ß triggers microglial inflammation accompanied by increasing GAPDH levels. The increase of GAPDH, a glycolysis enzyme, leads to the reduced release of interferon-γ (IFN-γ) from inflammatory microglia. Such alternation is translational and is regulated by the binding of glycolysis enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) to IFN-γ mRNA. GAPDH, by engaging/disengaging glycolysis and through influencing IFN-γ expression, regulates microglia functions, including phagocytosis and cytokine production. Phosphoglycerate dehydrogenase (PHGDH), screened from different state microglia by metabolomics combined with METARECON analysis, is a metabolic enzyme adjacent downstream of GAPDH and synthesizes serine on the collateral pathway derived from glycolysis. Polarization of microglial with PHGDH as a metabolic checkpoint can be bidirectionally regulated by adding IL-4 or giving PHGDH inhibitors. Therefore, regulation of metabolic enzymes not only reprograms metabolic patterns, but also manipulates microglia functions. Further study should be performed to explore the mechanism of metabolic checkpoints in human microglia or more in vivo animal experiments, and may expand to the effects of various metabolic substrates or enzyme, such as lipids and amino acids, on the functions of microglia.

Menin Reduces Parvalbumin Expression and is Required for the Anti-Depressant Function of Ketamine.

Dysfunction of parvalbumin (PV) neurons is closely involved in depression, however, the detailed mechanism remains unclear. Based on the previous finding that multiple endocrine neoplasia type 1 (Protein: Menin; Gene: Men1) mutation (G503D) is associated with a higher risk of depression, a Menin-G503D mouse model is generated that exhibits heritable depressive-like phenotypes and increases PV expression in brain. This study generates and screens a serial of neuronal specific Men1 deletion mice, and found that PV interneuron Men1 deletion mice (PcKO) exhibit increased cortical PV levels and depressive-like behaviors. Restoration of Menin, knockdown PV expression or inhibition of PV neuronal activity in PV neurons all can ameliorate the depressive-like behaviors of PcKO mice. This study next found that ketamine stabilizes Menin by inhibiting protein kinase A (PKA) activity, which mediates the anti-depressant function of ketamine. These results demonstrate a critical role for Menin in depression, and prove that Menin is key to the antidepressant function of ketamine.

Lower Limb Joint Torque Prediction Using Long Short-Term Memory Network and Gaussian Process Regression.

The accurate prediction of joint torque is required in various applications. Some traditional methods, such as the inverse dynamics model and the electromyography (EMG)-driven neuromusculoskeletal (NMS) model, depend on ground reaction force (GRF) measurements and involve complex optimization solution processes, respectively. Recently, machine learning methods have been popularly used to predict joint torque with surface electromyography (sEMG) signals and kinematic information as inputs. This study aims to predict lower limb joint torque in the sagittal plane during walking, using a long short-term memory (LSTM) model and Gaussian process regression (GPR) model, respectively, with seven characteristics extracted from the sEMG signals of five muscles and three joint angles as inputs. The majority of the normalized root mean squared error (NRMSE) values in both models are below 15%, most Pearson correlation coefficient (R) values exceed 0.85, and most decisive factor (R2) values surpass 0.75. These results indicate that the joint prediction of torque is feasible using machine learning methods with sEMG signals and joint angles as inputs.

Hypothalamic Menin regulates systemic aging and cognitive decline.

Aging is a systemic process, which is a risk factor for impaired physiological functions, and finally death. The molecular mechanisms driving aging process and the associated cognitive decline are not fully understood. The hypothalamus acts as the arbiter that orchestrates systemic aging through neuroinflammatory signaling. Our recent findings revealed that Menin plays important roles in neuroinflammation and brain development. Here, we found that the hypothalamic Menin signaling diminished in aged mice, which correlates with systemic aging and cognitive deficits. Restoring Menin expression in ventromedial nucleus of hypothalamus (VMH) of aged mice extended lifespan, improved learning and memory, and ameliorated aging biomarkers, while inhibiting Menin in VMH of middle-aged mice induced premature aging and accelerated cognitive decline. We further found that Menin epigenetically regulates neuroinflammatory and metabolic pathways, including D-serine metabolism. Aging-associated Menin reduction led to impaired D-serine release by VMH-hippocampus neural circuit, while D-serine supplement rescued cognitive decline in aged mice. Collectively, VMH Menin serves as a key regulator of systemic aging and aging-related cognitive decline.

Gait Prediction and Variable Admittance Control for Lower Limb Exoskeleton With Measurement Delay and Extended-State-Observer.

The measurement delay of the feedback control system is a universal problem in industrial engineering, which will degrade output performance, especially causing undesirable chatter responses. In this study, a deep-Gaussian-process (DGP)-based method for operator's gait prediction is proposed to estimate the real-time motion intention and to compensate for the measurement delay of the inertial measurement unit (IMU). On the basis of these gait prediction uncertainties quantified by the DGP method, a variable admittance controller is designed to reduce real-time human-exoskeleton interaction torque. The reference trajectory is generated by the admittance controller, which is smoothed by the two-order Bessel interpolation. Meanwhile, the admittance parameters are self-regulated based on the defined uncertainty index of gait prediction. The extend-state observer (ESO) with backstepping iteration is adopted to compensate unmeasured system state, model uncertainties, and unmodeled dynamics of lower limb exoskeleton. The effectiveness of the proposed gait prediction and control scheme is verified by both the comparative simulations and experimental results of the human-exoskeleton cooperative motion.

Brain Energy Metabolism: Astrocytes in Neurodegenerative Diseases.

Astrocytes are the most abundant cells in the brain. They have many important functions in the central nervous system (CNS), including the maintenance of glutamate and ion homeostasis, the elimination of oxidative stress, energy storage in glycogen, tissue repair, regulating synaptic activity by releasing neurotransmitters, and participating in synaptic formation. Astrocytes have special highly ramified structure. Their branches contact with synapses of neurons inwardly, with fine structure and wrapping synapses; their feet contact with blood vessels of brain parenchyma outward, almost wrapping the whole brain. The adjacent astrocytes rarely overlap and communicate with each other through gap junction channels. The ideal location of astrocytes enables them to sense the weak changes of their surroundings and provide the structural basis for the energy supply of neurons. Neurons and astrocytes are closely coupled units of energy metabolism in the brain. Neurons consume a lot of ATPs in the process of neurotransmission. Astrocytes provide metabolic substrates for neurons, maintain high activity of neuron, and facilitate information transmission of neurons. This article reviews the characteristics of glucose metabolism, lipid metabolism, and amino acid metabolism of astrocytes. The metabolic interactions between astrocytes and neurons, astrocytes and microglia were also detailed discussed. Finally, we classified analyzed the role of metabolic disorder of astrocytes in the occurrence and development of neurodegenerative diseases.

Microglial hexokinase 2 deficiency increases ATP generation through lipid metabolism leading to ß-amyloid clearance.

Microglial cells consume adenosine triphosphate (ATP) during phagocytosis to clear neurotoxic ß-amyloid in Alzheimer's disease (AD). However, the contribution of energy metabolism to microglial function in AD remains unclear. Here, we demonstrate that hexokinase 2 (HK2) is elevated in microglia from an AD mouse model (5xFAD) and AD patients. Genetic deletion or pharmacological inhibition of HK2 significantly promotes microglial phagocytosis, lowers the amyloid plaque burden and attenuates cognitive impairment in male AD mice. Notably, the ATP level is dramatically increased in HK2-deficient or inactive microglia, which can be attributed to a marked upregulation in lipoprotein lipase (LPL) expression and subsequent increase in lipid metabolism. We further show that two downstream metabolites of HK2, glucose-6-phosphate and fructose-6-phosphate, can reverse HK2-deficiency-induced upregulation of LPL, thus supporting ATP production and microglial phagocytosis. Our findings uncover a crucial role for HK2 in phagocytosis through regulation of microglial energy metabolism, suggesting a potential therapeutic strategy for AD by targeting HK2.

Correlation analysis of national elite Chinese male table tennis players' shoulder proprioception and muscle strength.

BACKGROUND: Shoulder is the most injured part in table tennis players, and it takes multiple roles in transmitting power and striking the center of the ball during the stroke. Proprioception is strongly correlated with high level of athletic performance. It is customary to assume that there is a correlation between proprioception and muscle strength and therefore proprioceptive assessment and rehabilitation is often neglected. AIM: To investigate the correlation between isokinetic muscle strength and proprioception in the internal and external rotation muscle groups of elite Chinese male table tennis players, to provide reference for physical training and rehabilitation of elite table tennis players. METHODS: A total of 19 national elite table tennis players from the Chinese National Table Tennis Team were recruited in this research. All of them had more than 10 years training experience and had participated major competitions such as the National Games and World Youth Championships. IsoMed 2000 was used to test the peak torque of internal and external rotation isokinetic concentric contraction of the athletes' bilateral shoulder joints at low speed (60°/s) and high speed (180°/s) respectively; IsoMed 2000 was used to conduct the Joint Position Reproduction test to evaluate the athletes' proprioceptive ability capacity at low speed (60°/s) and high speed (180°/s) respectively. If the data satisfied the normal distribution, the correlation between the differences in peak torque s and angles in different directions was analyzed using a Pearson simple linear model; otherwise, Spearman correlation analysis was used. The comparison of proprioceptive ability between the table tennis racket-holding hand and non-racket-holding hands was performed using independent samples t-test if the data satisfied a normal distribution; otherwise, the Mann-Whitney U test was used. RESULTS: There was no direct linear correlation between the strength and proprioceptive correlation analysis at slow speed (60°/s) and fast speed (180°/s) in the racket-holding hand; At the slow speed (60°/s) and fast speed (180°/s), there was no correlation between muscle strength and proprioception in the non-racket-holding hand except for the internal rotation variable error (VE) and external rotation relative peak torque, which showed a moderate positive correlation (r = 0.477, P < 0.05), (r = 0.554, P < 0.05). The internal rotation's constant error (CE) and VE were 1.06 ± 3.99 and 2.94 ± 2.16, respectively, for the racket-holding hand, and -3.36 ± 2.39 and 1.22 ± 0.93, respectively, for the non-racket-holding hand; the internal rotation's CE, VE of the racket-holding hand was lower than that of the non-racket-holding hand, and there was a highly significant difference (P < 0.01). CONCLUSION: There was no correlation between muscle strength and proprioceptive function in the internal and external rotation of the racket-holding hand's shoulder in elite Chinese male table tennis players. These results may be useful for interventions for shoulder injuries and for the inclusion of proprioceptive training in rehabilitation programs.

Application of CT Medical Imaging Combined with Deep Learning 3D Reconstruction in the Diagnosis and Rehabilitation of Anterior Cruciate Ligament Injury in Table Tennis Players.

Because of the intense competition, table tennis requires players to bear a strong physiological load, which increases the risk of sports injury. Anterior cruciate ligament (ACL) is an important structure of the knee joint to maintain forward stability and rotational stability and is also a common sports injury in table tennis players. ACL has poor self-repair ability after injury. Therefore, the purpose of this study is to provide a more comprehensive, reliable, and representative theoretical basis for the diagnosis and rehabilitation of anterior cruciate ligament injury in table tennis players, and three-dimensional reconstruction of ACL using dual-source computed tomography (DSCT) combined with deep learning was conducted. For this purpose, a number of table tennis players with ACL injuries were collected, and each patient underwent arthroscopic anterior cruciate ligament reconstruction. DSCT scanning was performed on several knee joints, the 3D model of the knee joint was reconstructed using a CT image postprocessing workstation, and the medial wall of the femoral lateral condyle was reconstructed, as well as the reconstructed single tract of bony canal, tibial plateau, and bony canal. Then, the Lysholm score was used to score the cases, with scores greater than 75 as the excellent group and below 75 as the poor group. The relative positions of the central points of the femoral and tibial canals were marked and measured. The results were as follows: 3D-CT reconstruction could clearly reflect the situation after anterior cruciate ligament reconstruction. In clinic, it is used to evaluate the relationship between bone tunnel location and graft shape so as to guide the surgeon to improve the operation.

Common Polymorphisms in the RGMa Promoter Are Associated With Cerebrovascular Atherosclerosis Burden in Chinese Han Patients With Acute Ischemic Cerebrovascular Accident.

Repulsive guidance molecule a (RGMa) plays a vital role in the progression of numerous inflammatory diseases. However, whether it participates in atherosclerosis development is not known. Here, we explored the influence of RGMa in atherogenesis by investigating whether an association exists between functional polymorphisms in the RGMa promoter and cerebrovascular atherosclerosis burden (CAB) in Chinese Han patients diagnosed with acute ischemic cerebrovascular accident. To this end, we conducted a genetic association study on 201 patients with prior diagnoses of acute ischemic stroke or transient ischemic attack recruited from our hospital. After admission, we conducted three targeted single-nucleotide polymorphisms (SNPs) genotyping and evaluated CAB by computed tomography angiography. We used logistic regression modeling to analyze genetic associations. Functional polymorphism analysis indicated an independent association between the rs725458 T allele and increased CAB in patients with acute ischemic cerebrovascular accident [adjusted odds ratio (OR) = 1.66, 95% confidence interval (CI) = 1.01-2.74, P = 0.046]. In contrast, an association between the rs4778099 AA genotype and decreased CAB (adjusted OR = 0.10, 95% CI = 0.01-0.77, P = 0.027) was found. Our Gene Expression Omnibus analysis revealed lower RGMa levels in the atherosclerotic aortas and in the macrophages isolated from plaques than that in the normal aortas and macrophages from normal tissue, respectively. In conclusion, the relationship between RGMa and cerebrovascular atherosclerosis suggests that RGMa has a potential vasoprotective effect. The two identified functional SNPs (rs725458 and rs4778099) we identified in the RGMa promoter are associated with CAB in patients diagnosed with acute ischemic cerebrovascular accident. These findings offer a promising research direction for RGMa-related translational studies on atherosclerosis.

Serum Interleukin-33 is a Novel Predictive Biomarker of Hemorrhage Transformation and Outcome in Acute Ischemic Stroke.

INTRODUCTION: Hemorrhage Transformation (HT) in acute ischemic stroke (AIS) depends on multiple factors. Some studies have shown that serum interleukin-33 (IL-33) is of central significance as a neuroprotective factor. However, the relationship between serum IL-33 and HT in AIS has not been evaluated. OBJECTIVE: To investigate the relationship between serum IL-33 concentration and HT in AIS. METHODS: We recruited 151 consecutive non-thrombolytic patients with AIS clinically diagnosed in The First Affiliated Hospital of Chongqing Medical University from December 2018 to October 2019. If the patients showed radiographic presentation of HT within two weeks following admission, they were assigned to the HT group; others were assigned to the non-HT group. There were 40 healthy control subjects recruited during the same period. Serum IL-33 concentration was detected by ELISA and the independent risk value of HT in AIS was predicted by multivariate logistic regression. The accuracy was analyzed by receiver operating characteristic (ROC) curves. In three months after admission, the functional outcome was measured by modified Rankin scale (mRS). RESULTS: ROC curve showed that the area under the curve (AUC) of serum IL-33 was 0.739 (95% CI: 0.657-0.821, P < .001) in predicting HT in AIS. When serum IL-33 concentration was ≤ 67.66 ng/L, the sensitivity and specificity of the prediction were 81.3% and 63%, respectively. Multivariate logistic regression analysis showed that serum IL-33 concentration ≤ 67.66 ng/L was an independent predictor of HT in AIS (OR = 5.773, 95% CI: 1.685-19.792, P = .005). The follow-up results of mRS showed a higher probability of an unfavorable outcome in those with HT compared to those without HT (OR = 6.520, 95% CI: 2.530-16.803, P < .001). CONCLUSIONS: HT in AIS is negatively correlated with outcome. Furthermore, serum IL-33 is an independent predictive biomarker of HT and outcome in AIS.

Application of antidepressants in depression: A systematic review and meta-analysis.

BACKGROUND: The type and quantities of antidepressants are increasing, but the efficacy and safety of first-line and emerging drugs vary between studies. In this article, we estimated the efficacy and safety of first-line and emerging antidepressants (anti-inflammatory drugs and ketamine). METHOD: ystematic search of EMBASE, ERIC, MEDLINE, psycARTICLES, and psycINFO without language restriction for studies on the depression, depressive symptoms, antidepressants, fluoxetine (Prozac), paroxetine, escitalopram, sertraline, fluvoxamine, venlafaxine, duloxetine, NSAIDs, anti-cytokine drugs or pioglitazone published before May 1st, 2019. Information on study characteristics, depression or depressive symptoms, antidepressants and the descriptive statistics (including efficacy and safety of antidepressants) was extracted independently by 2 investigators. Estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using stratified meta-analysis and meta-regression. The response and remission of antidepressants were used as clinical evaluation indicators, and the evaluation criteria were clinical depression scales. OR value of antidepressants as assessed by meta-analysis. RESULTS: The literature search retrieved 5529 potentially relevant articles of which 49 studies were finally included. We compared the efficacy of antidepressants (seven first-line antidepressants (fluoxetine, paroxetine, escitalopram, sertraline, fluvoxamine, venlafaxine, duloxetine), there kinds of anti-inflammatory drugs(NASIDs, cytokine-inhibitor, pioglitazone) and ketamine) by comparing the OR values. CONCLUSION: The three drugs with the highest OR value in response were NASID (OR = 3.62(1.58, 8.32)), venlafaxin (OR = 3.50(1.83, 6.70)) and ketamine (OR = 3.28(1.89, 5.68)), while the highest OR value in remission were NASID (OR = 3.17(1.60, 6.29)), ketamine (OR = 2.99(1.58, 5.67)) and venlafaxin (OR = 2.55(1.72, 3.78)). Through reading the literature, we found 69 SNPs associated with depression. Major depression was a debilitating disorder that could ultimately lead to enormous societal and economical challenge [1]. The number of person which affected by depression was up to 16% of the population worldwide. More than 300 million individuals were estimated to suffer depression these days [1,2]. Therefore, it is apparent that safety and effective treatments for depression are necessary. In the 1930 s, the first drug for schizophrenia was discovered. This finding was a landmark for the emerging of biological psychiatry. In the 1950 s, pharmacologists had stumbled upon the antidepressant effect of imipramine. Since then, every 30 years, the use of antidepressants had made a pulsatile leap. Selective serotonin reuptake inhibitors (SSRIs) are the most widely-prescribed psychiatric drugs for the treatment of depression. However, the efficacy was variable and incomplete: 60%-70% of the patients do not experience remission, while 30%-40% do not show a significant response [3,4]. Nevertheless, SSRIs, SNRIs (selective serotonin-norepinephrine reuptake inhibitors, which can block norepinephrine at the same time) and NaSSAs (norepinephrine and selective serotonin receptor agonist), constituted the first-line clinical drugs. Nearly 30 years after the outbreak of SSRIs, antidepressants have ushered in a new chapter. It has been found that anti-inflammatory drugs could also have the small and moderate antidepressant effect and it's widely discussed [5]. More than 40 anti-inflammatory drugs have been certificated to have antidepressant effects in preclinical and clinical studies [6]. The antidepressant that has been approved for use recently is ketamine. There is no comprehensive comparison of the efficacy of all these drugs. In this review, we tried to estimate the efficacy and safety of first-line antidepressants, anti-inflammatory drugs and ketamine. On the other hand, with the development of GWAS, SNPs related to depression have been reported, and the corresponding mechanisms have been elaborated, respectively. However, patients with these SNPs have not been treated with individualized drugs according to the mechanisms. We hope to push this process forward through the summary of this article. METHODS: Search Strategy and Study Eligibility.

Serum Interleukin-33 is a Predictor of Depression in Patients with Acute Ischemic Stroke.

OBJECTIVE: The study aimed to investigate the relationship between serum interleukin-33 (IL-33) concentrations and poststroke depression (PSD) in patients with acute ischemic stroke (AIS). METHODS: Serum IL-33 concentrations were determined using an enzyme-linked immunosorbent assay. Patients were assigned to the PSD group after a six-month follow-up if their score on the 17- item Hamilton Rating Scale for Depression was ≥7 or to the non-PSD group if their score was <7. IL-33 was used to predict the risk of PSD using multivariate logistic regression analysis, while a receiver operating characteristic (ROC) curve was used to analyze the accuracy of PSD prediction. In addition, the modified Rankin scale (mRS) was used for follow-up scoring six months after disease onset. RESULTS: A total of 151 AIS patients and 40 healthy controls were included in this study. ROC curve results showed that the area under the curve was 0.684 (95% confidence interval: 0.594-0.774,Ρ=0.001) for IL-33 as a predictor of PSD. When the IL-33 concentration was ≤71.85 ng/L, prediction sensitivity and specificity were 77.5% and 57.3%, respectively. Multivariate logistic regression analysis showed that IL-33 concentration of ≤71.85 ng/L was an independent predictor of PSD (95% CI: 1.129-7.515, P=0.027). The follow-up mRS data showed that serum IL-33 is a protective prognosis factor in patients with AIS (95% CI: 0.954-0.997, P=0.024). CONCLUSION: Serum IL-33 is an independent predictor of PSD and a protective prognosis factor in patients with AIS.

Comparison of clinical manifestations and antibiotic resistances among three genospecies of the Acinetobacter calcoaceticus-Acinetobacter baumannii complex.

The Acinetobacter calcoaceticus-Acinetobacter baumannii (ACB) complex has emerged as a high priority among hospital-acquired pathogens in intensive care units (ICUs), posing a challenge to infection management practices. In this study, the clinical characteristics, antimicrobial susceptibility patterns, and patients outcome among genospecies were retrospectively compared. Samples were taken from the tracheal secretions of 143 patients in the ICU. Genospecies of the ACB complex were discriminated by analysis of the 16S-23S rRNA gene intergenic spacer (ITS) sequence. Univariate and multiple variable logistic regression analyses were performed to identify risk factors for infection and mortality. Three genospecies were isolated: A. baumannii (73, 51.0%), A. nosocomialis (29, 20.3%), and A. pittii (41, 28.7%). The results showed that the distribution of infection and colonization among the three genospecies were the same, while A. baumannii was more resistant to common antibiotics than A. nosocomialis and A. pittii. Advanced age, a long stay in the ICU, acute physiology and chronic health evaluation (APACHE) II score, the use of a mechanical ventilator, and previous antibiotic use were risk factors for patient infection. The APACHE II score was a risk factor for mortality in patients with ACB complex isolated from tracheal secretions. Poor outcome of patients with ACB complex isolated from tracheal secretion appears to be related to the APACHE II score rather than genospecies.

High energy, widely tunable Si-prism-array coupled terahertz-wave parametric oscillator with a deformed pump and optimal crystal location for angle tuning.

A high energy, widely tunable Si-prism-array coupled terahertz-wave parametric oscillator (TPO) has been demonstrated by using a deformed pump. The deformed pump is cut from a beam spot of 2 mm in diameter by a 1-mm-wide slit. In comparison with a small pump spot (1-mm diameter), the THz-wave coupling area for the deformed pump is increased without limitation to the low-frequency end of the tuning range. Besides, the crystal location is specially designed to eliminate the alteration of the output position of the pump during angle tuning, so the initially adjusted nearest pumped region to the THz-wave exit surface is maintained throughout the tuning range. The tuning range is 0.58-2.5 THz for the deformed pump, while its low frequency end is limited at approximately 1.2 THz for the undeformed pump with 2 mm diameter. The highest THz-wave output of 2 µJ, which is 2.25 times as large as that from the pump of 1 mm in diameter, is obtained at 1.15 THz under 38 mJ (300 MW/cm2) pumping. The energy conversion efficiency is 5.3×10-5.