Attenuation of Cross-Flow Fan Noise Using Porous Stabilizers

This paper presents a qualitative analysis of controlling the cross-flow fan noise by using porous stabilizers. The stabilizer was originally a folded plate. It is changed into a porous structure which has a plenum chamber and vent holes on the front wall. In order to investigate the influences of using the porous stabilizers, experiments are carried out to measure the cross-flow fan aerodynamic performances and sound radiation. Meanwhile, the internal flow field of the fan is numerically simulated. The results show that the porous stabilizers have not produced considerable effect on the cross-flow fan's performance curve, but the noise radiated from the fan is strongly affected. This indicates the feasibility of controlling the cross-flow fan noise by using the porous stabilizers with selected porosity

Quantitative thermal testing as a screening and follow-up tool for diabetic sensorimotor polyneuropathy in patients with type 2 diabetes and prediabetes

IntroductionThe diagnosis and assessment of neuropathy severity of diabetic sensorimotor polyneuropathy (DSPN) are mainly based on clinical neuropathy scores and electrophysiologic studies. This study aimed to determine whether quantitative thermal testing (QTT) can be used as a screening and follow-up tool for DSPN of prediabetes and type 2 diabetes at baseline and at 1-year follow-up.MethodsAll patients were assessed using the Toronto Clinical Neuropathy Score (TCNS) and underwent electrophysiological testing, including a nerve conduction study (NCS) and QTT, at baseline and at a 1-year follow-up. The TCNS and the composite scores of nerve conduction were used to assess the severity of DSPN. The DSPN status at the 1-year follow-up was classified as remaining no DSPN, remaining DSPN, regression to no DSPN, or progression to DSPN.ResultsDiabetic sensorimotor polyneuropathy was initially diagnosed in 89 patients with prediabetes and type 2 diabetes (22%). The regressed to no DSPN in 29 patients and progressed to DSPN in 20 patients at the 1-year follow-up. TCNS was significantly correlated with composite scores of nerve conduction, hand cold detection threshold (CDT), hand warm detection threshold (WDT), foot CDT, and foot WDT. Stepwise logistic regression demonstrated that the foot CDT (p < 0.0001) was independently associated with the presence of DSPN. The TCNS, composite scores of the nerve conduction, hand WDT, hand CDT, foot WDT, and foot CDT were all statistically significant among the four different DSPN status groups at two different time periods (baseline and the 1-year follow-up).ConclusionThe foot CDT can be used as an initial screening tool for DSPN alternatively. The characteristics of nerve damage after 1 year of DSPN can be progressive or reversible, and the neurological functions of large and small fibers have a parallel trend, which can be objectively measured by NCS and QTT

Fabrication of multianalyte CeO2 nanograin electrolyte–insulator–semiconductor biosensors by using CF4 plasma treatment

Multianalyte CeO2 biosensors have been demonstrated to detect pH, glucose, and urine concentrations. To enhance the multianalyte sensing capability of these biosensors, CF4 plasma treatment was applied to create nanograin structures on the CeO2 membrane surface and thereby increase the contact surface area. Multiple material analyses indicated that crystallization or grainization caused by the incorporation of flourine atoms during plasma treatment might be related to the formation of the nanograins. Because of the changes in surface morphology and crystalline structures, the multianalyte sensing performance was considerably enhanced. Multianalyte CeO2 nanograin electrolyte–insulator–semiconductor biosensors exhibit potential for use in future biomedical sensing device applications

Qiliqiangxin Rescues Mouse Cardiac Function by Regulating AGTR1/TRPV1-Mediated Autophagy in STZ-Induced Diabetes Mellitus

Background/Aims: To explore the potential role of qiliqiangxin (QLQX) A traditional Chinese medicine and the involvement of angiotensin II receptor type 1 (AGTR1) and transient receptor potential vanilloid 1 (TRPV1) in diabetic mouse cardiac function. Methods: Intragastric QLQX was administered for 5 weeks after streptozotocin (STZ) treatment. Additionally, Intraperitoneal injections of angiotensin II (Ang II) or intragastric losartan (Los) were administered to assess the activities of AGTR1 and TRPV1. Two-dimensional echocardiography and tissue histopathology were used to assess cardiac function Western blot was used to detect the autophagic biomarkers Such as light chain 3 P62 and lysosomal-associated membrane protein 2 And transmission electron microscopy was used to count the number of autophagosomes. Results: Decreased expression of TRPV1 and autophagic hallmarks and reduced numbers of autophagolysosomes as well as increased expression of angiotensin converting enzyme 1 and AGTR1 were observed in diabetic hearts. Blocking AGTR1 with Los mimicked the QLQX-mediated improvements in cardiac function Alleviated myocardial fibrosis and enabled autophagy Whereas Ang II abolished the beneficial effects of QLQX in wild type diabetic mice but not in TRPV1-/- diabetic mice. Conclusions: QLQX may improve diabetic cardiac function by regulating AGTR1/ TRPV1-mediated autophagy in STZ-induced diabetic mice

Prediction of Progression to Severe Stroke in Initially Diagnosed Anterior Circulation Ischemic Cerebral Infarction

Purpose: Accurate prediction of the progression to severe stroke in initially diagnosed nonsevere patients with acute–subacute anterior circulation nonlacuna ischemic infarction (ASACNLII) is important in making clinical decision. This study aimed to apply a machine learning method to predict if the initially diagnosed nonsevere patients with ASACNLII would progress to severe stroke by using diffusion-weighted images and clinical information on admission.Methods: This retrospective study enrolled 344 patients with ASACNLII from June 2017 to August 2020 on admission, and 108 cases progressed to severe stroke during hospitalization within 3–21 days. The entire data were randomized into a training set (n = 271) and an independent test set (n = 73). A U-Net neural network was employed for automatic segmentation and volume measurement of the ischemic lesions. Predictive models were developed and used for evaluating the progression to severe stroke using different feature sets (the volume data, the clinical data, and the combination) and machine learning methods (random forest, support vector machine, and logistic regression).Results: The U-Net showed high correlation with manual segmentation in terms of Dice coefficient of 0.806 and R2 value of the volume measurements of 0.960 in the test set. The random forest classifier of the volume + clinical combination achieved the best area under the receiver operating characteristic curve of 0.8358 (95% CI 0.7321–0.9269), and the accuracy, sensitivity, and specificity were 0.7780 (0.7397–0.7945), 0.7695 (0.6102–0.9074), and 0.8686 (0.6923–1.0), respectively. The Shapley additive explanation diagram showed the volume variable as the most important predictor.Conclusion: The U-Net was fully automatic and showed a high correlation with manual segmentation. An integrated approach combining clinical variables and stroke lesion volumes that were derived from the advanced machine learning algorithms had high accuracy in predicting the progression to severe stroke in ASACNLII patients

A novel nomogram to predict futile recanalization in patients with acute ischemic stroke undergoing mechanical thrombectomy

Background and objectiveFutile recanalization (FR) is defined as patients with acute ischemic stroke (AIS) due to large vessel occlusion who still exhibits functional dependence although undergoing successful mechanical thrombectomy (MT). We aimed to develop and validate a simple nomogram for predicting the probability of FR after MT treatment in AIS patients.MethodsClinical data of AIS patients in the Jrecan clinical trial in China from March 2018 to June 2019 were collected as the derivation set (n = 162). Meanwhile, clinical data of AIS patients who underwent MT in Baotou Central Hospital and Ningbo No.2 Hospital from 2019 to 2021 were collected as the validation set (n = 170). Multivariate logistic regression analysis was performed for all variables that had p < 0.2 in the univariate analysis in the derivation set. The independent risk factors of FR were further screened out and a nomogram was constructed. The performance of the nomogram was analyzed in the derivation and validation set using C-index, calibration plots, and decision curves.ResultsNo significant difference in FR rate was detected between the derivation set and the validation set [88/162 (54.32%) and 82/170 (48.23%), p = 0.267]. Multivariate logistic regression analysis showed that age ≥ 65 years old (OR = 2.096, 95%CI 1.024–4.289, p = 0.043), systolic blood pressure (SBP) ≥ 180 mmHg (OR = 5.624, 95%CI 1.141–27.717, p = 0.034), onset to recanalization time (OTR) ≥ 453 min (OR = 2.759, 95%CI 1.323–5.754, p = 0.007), 24 h intracerebral hemorrhage (ICH; OR = 4.029, 95%CI 1.844 ~ 8.803, p < 0.001) were independent risk factors for FR. The C-index of the nomogram of the derivation set and the verification set were 0.739 (95%CI 0.662~0.816) and 0.703 (95%CI 0.621~0.785), respectively.ConclusionThe nomogram composed of age, SBP, OTR, and 24 h ICH can effectively predict the probability of FR after MT in AIS patients

Phosphoproteomics reveals that Parkinson’s disease kinase LRRK2 regulates a subset of Rab GTPases

Mutations in Park8, encoding for the multidomain Leucine-rich repeat kinase 2 (LRRK2) protein, comprise the predominant genetic cause of Parkinson's disease (PD). G2019S, the most common amino acid substitution activates the kinase two- to threefold. This has motivated the development of LRRK2 kinase inhibitors; however, poor consensus on physiological LRRK2 substrates has hampered clinical development of such therapeutics. We employ a combination of phosphoproteomics, genetics, and pharmacology to unambiguously identify a subset of Rab GTPases as key LRRK2 substrates. LRRK2 directly phosphorylates these both in vivo and in vitro on an evolutionary conserved residue in the switch II domain. Pathogenic LRRK2 variants mapping to different functional domains increase phosphorylation of Rabs and this strongly decreases their affinity to regulatory proteins including Rab GDP dissociation inhibitors (GDIs). Our findings uncover a key class of bona-fide LRRK2 substrates and a novel regulatory mechanism of Rabs that connects them to PD

Risk groups defined by Recursive Partitioning Analysis of patients with colorectal adenocarcinoma treated with colorectal resection

<p>Abstract</p> <p>Background</p> <p>To define different prognostic groups of surgical colorectal adenocarcinoma patients derived from recursive partitioning analysis (RPA).</p> <p>Methods</p> <p>Ten thousand four hundred ninety four patients with colorectal adenocarcinoma underwent colorectal resection from Taiwan Cancer Database during 2003 to 2005 were included in this study. Exclusion criteria included those patients with stage IV disease or without number information of lymph nodes. For the definition of risk groups, the method of classification and regression tree was performed. Main primary outcome was 5-year cancer-specific survival.</p> <p>Results</p> <p>We identified six prognostic factors for cancer-specific survival, resulting in seven terminal nodes. Four risk groups were defined as following: Group 1 (mild risk, 1,698 patients), Group 2 (moderate risk, 3,129 patients), Group 3 (high risk, 4,605 patients) and Group 4 (very high risk, 1,062 patients). The 5-year cancer-specific survival for Group 1, 2, 3, and 4 was 86.6%, 62.7%, 55.9%, and 36.6%, respectively (p < 0.001). Hazard ratio of death was 2.13, 5.52 and 10.56 (95% confidence interval 1.74-2.60, 4.58-6.66 and 8.66-12.9, respectively) times for Group 2, 3, and 4 as compared to Group 1. The predictive capability of these grouping was also similar in terms of overall and progression-free survival.</p> <p>Conclusion</p> <p>The use of RPA offered an alternative grouping method that could predict the survival of patients who underwent surgery for colorectal adenocarcinoma.</p