Resting-state functional magnetic resonance imaging and support vector machines for the diagnosis of major depressive disorder in adolescents

BACKGROUND Research has found that the amygdala plays a significant role in underlying pathology of major depressive disorder(MDD).However,few studies have explored machine learning-assisted diagnostic biomarkers based on amygdala functional connectivity(FC).AIM To investigate the analysis of neuroimaging biomarkers as a streamlined approach for the diagnosis of MDD in adolescents.METHODS Forty-four adolescents diagnosed with MDD and 43 healthy controls were enrolled in the study.Using resting-state functional magnetic resonance imaging,the FC was compared between the adolescents with MDD and the healthy controls,with the bilateral amygdala serving as the seed point,followed by statistical analysis of the results.The support vector machine(SVM)method was then applied to classify functional connections in various brain regions and to evaluate the neurophysiological characteristics associated with MDD.RESULTS Compared to the controls and using the bilateral amygdala as the region of interest,patients with MDD showed significantly lower FC values in the left inferior temporal gyrus,bilateral calcarine,right lingual gyrus,and left superior occipital gyrus.However,there was an increase in the FC value in Vermis-10.The SVM analysis revealed that the reduction in the FC value in the right lingual gyrus could effectively differentiate patients with MDD from healthy controls,achieving a diagnostic accuracy of 83.91%,sensitivity of 79.55%,specificity of 88.37%,and an area under the curve of 67.65%.CONCLUSION The results showed that an abnormal FC value in the right lingual gyrus was effective as a neuroimaging biomarker to distinguish patients with MDD from healthy controls.

Dachaihu decoction ameliorates pancreatic fibrosis by inhibiting macrophage infiltration in chronic pancreatitis

AIM To explore the role of macrophages in chronic pancreatitis(CP) and the effect of Dachaihu decoction(DCHD) on pancreatic fibrosis in mice.METHODS Kun Ming mice were randomly divided into a control group, CP group, and DCHD group. In the CP and DCHD groups, mice were intraperitoneally injected with 20% L-arginine(3 g/kg twice 1 d/wk for 6 wk). Mice in the DCHD group were administered DCHD intragastrically at a dose of 14 g/kg/d 1 wk after CP induction. At 2 wk, 4 wk and 6 wk post-modeling, the morphology of the pancreas was observed using hematoxylin and eosin, and Masson staining. Interleukin-6(IL-6) serum levels were assayed using an enzyme-linked immunosorbent assay. Double immunofluorescence staining was performed to observe the co-expression of F4/80 and IL-6 in the pancreas. Inflammatory factors including monocyte chemoattractant protein-1(MCP-1), macrophage inflammatory protein-1α(MIP-1α) and IL-6 were determined using real time-polymerase chain reaction. Western blot analysis was used to detect fibronectin levels in the pancreas. RESULTS Compared with the control group, mice with 20% L-arginine-induced CP had obvious macrophage infiltration and a higher level of fibrosis. IL-6 serum concentrations were significantly increased. Double immunofluorescence staining showed that IL-6 and F4/80 were co-expressed in the pancreas. With the administration of DCHD, the infiltration of macrophages and degree of fibrosis in the pancreas were significantly attenuated; IL-6, MCP-1 and MIP-1α m RNA, and fibronectin levels were reduced. CONCLUSION The dominant role of macrophages in the development of CP was mainly related to IL-6 production. DCHD was effective in ameliorating pancreatic fibrosis by inhibiting macrophage infiltration and inflammatory factor secretion in the pancreas.

Pathophysiology of chronic pancreatitis induced by dibutyltin dichloride joint ethanol in mice

AIM: To search for a new chronic pancreatitis model in mice suitable for investigating the pathophysiological processes leading to pancreatic fibrosis.METHODS: The mice were randomly divided into 2 groups(n = 50), control group and model group. The mice in model group were given ethanol(10%) in drinking water after injection of dibutyltin dichloride(DBTC)(8 mg/kg BW) in tail vein. The mice in control group were injected with only solvent into tail vein( 60 % ethanol, 20% glycerine and 20% normal saline) and drank common water. At days 1, 7, 14, 28, and 56 after application of DBTC or solvent, 10 mice in one group were killed at each time point respectively. Blood was obtained by inferior vena cava puncture. The activity of amylase, concentration of bilirubin and hyaluronic acid in serum were assayed. The pancreas was taken to observe the pancreatic morphology by HE staining, and to characterize the pancreatic fibrosis by Masson staining. The expression of F4/80, CD3 and fibronectin(FN) were assayed by immuno-histochemistry or Immunofluorescence technique. Collagen typeⅠ(COL1A1) in pancreas were detected by Western blot. The expression of matrix metalloproteinase-1(MMP-1) and tissue inhibitor of metalloproteinases-1(TIMP-1) m RNA in the pancreas was assessed by real time PCR.RESULTS: DBTC induced an acute edematous pancreatitis within 1 d. The dilated acini, scattered acinar cell necrosis, and inflammatory cells were found at day 7. Extensive infiltration with inflammatory cells following deposition of connective tissue was observed at day 14. At day 28, level of pancreatic fibrosis was aggravated. The pancreatic tissue was replaced by an extended interstitial fibrosis at the end of 2 mo. There was significant difference in the level of amylase, bilirubin and hyaluronic acid in serum between control group and model group(P < 0.05). The level of COL1A1 and FN in pancreas increased. The expression of MMP-1 m RNA in pancreas decreased, but TIMP-1 m RNA increased at model group.CONCLUSION: DBTC joint Ethanol drinking can induce chronic pancreatitis in accordance with the pathophysiological modification of human. DBTC joint Ethanol-induced pancreatitis in mice is an effective and handy experimental method. The model is suitable to study the mechanism of pancreatic fibrosis in chronic pancreatitis.

Breviscapine attenuates acute pancreatitis by inhibiting expression of PKCα and NF-κB in pancreas

AIM:To study the effect of breviscapine (Bre) on activity of protein kinase Cα (PKCα) and nuclear factor (NF)-κB in pancreas,and the mechanism of Bre attenuating acute pancreatitis (AP). METHODS:One hundred and eight rats were randomly divided into acute necrotizing pancreatitis (ANP) group,Bre group (ANP + Bre group) and sham operation (SO) group,36 rats in each group. ANP model was induced by a retrograde injection of 4% sodium deoxycholate into the bilio-pancreatic duct. Fifteen minutes after the ANP model was induced,the rats in Bre group were intraperitoneally injected with Bre (0.4 mg/100 g body weight or 0.1 mL/100 g body weight). Survival time and mortality of rats were calculated. Serum amylase and malondialdehyde levels were measured,volume of ascites was recorded and morphology of pancreas and lung was evaluated at 1,5 and 10 h,after the ANP model was induced,respectively. Expressions of PKCα and subunit p65 of NF-κB in pancreas were detected by immunohistochemistry and Western blotting. RESULTS:The life span of rats was longer and the mortality was lower in Bre group than in ANP group 13.51 ± 5.46 vs 25.36 ± 8.11 (P < 0.05). The amylase and MDA levels as well as the volume of ascites were lower and the pathological changes in pancreas and lung were less in Bre group than ANP group (P < 0.05),indicating that the pancreatitis is less severe in Bre group than ANP group. The activation of PKCα and NF-κB p65 in pancreas was induced rapidly and reached their peak at 1 h or 5 h after ANP,but their activity in Bre group was significantly inhibited. CONCLUSION:Bre exerts its therapeutic effect on AP by inhibiting the activation of PKCα and NF-κB p65 in pancreas.

Modified Saint-Venant equations for flow simulation in tidal rivers

Flow in tidal rivers periodically propagates upstream or downstream under tidal influence. Hydrodynamic models based on the Saint-Venant equations （the SVN model） are extensively used to model tidal rivers. A force-corrected term expressed as the combination of flow velocity and the change rate of the tidal fevel was developed to represent tidal effects in the SVN model. A momentum equation incorporating with the corrected term was derived based on Newton＇s second law. By combing the modified momentum equation with the continuity equation, an improved SVN model for tidal rivers （the ISVN model） was constructed. The simulation of a tidal reach of the Qiantang River shows that the ISVN model performs better than the SVN model. It indicates that the corrected force derived for tidal effects is reasonable; the ISVN model provides an appropriate enhancement of the SVN model for flow simulation of tidal rivers.

Lung transplantation as therapeutic option in acute respiratory distress syndrome for coronavirus disease 2019-related pulmonary fibrosis

Background:Critical patients with the coronavirus disease 2019(COVID-19),even those whose nucleic acid test results had turned negative and those receiving maximal medical support,have been noted to progress to irreversible fatal respiratory failure.Lung transplantation(LT)as the sole therapy for end-stage pulmonary fibrosis related to acute respiratory distress syndrome has been considered as the ultimate rescue therapy for these patients.Methods:From February 10 to March 10,2020,three male patients were urgently assessed and listed for transplantation.After conducting a full ethical review and after obtaining assent from the family of the patients,we performed three LT procedures for COVID-19 patients with illness durations of more than one month and extremely high sequential organ failure assessment scores.Results:Two of the three recipients survived post-LT and started participating in a rehabilitation program.Pearls of the LT team collaboration and perioperative logistics were summarized and continually improved.The pathological results of the explanted lungs were concordant with the critical clinical manifestation,and provided insight towards better understanding of the disease.Government health affair systems,virology detection tools,and modern communication technology all play key roles towards the survival of the patients and their rehabilitation.Conclusions:LT can be performed in end-stage patients with respiratory failure due to COVID-19-related pulmonary fibrosis.If confirmed positive-turned-negative virology status without organ dysfunction that could contraindicate LT,LT provided the final option for these patients to avoid certain death,with proper protection of transplant surgeons and medical staffs.By ensuring instant seamless care for both patients and medical teams,the goal of reducing the mortality rate and salvaging the lives of patients with COVID-19 can be attained.

Advances in Deep Learning Methods for Visual Tracking:Literature Review and Fundamentals

Recently,deep learning has achieved great success in visual tracking tasks,particularly in single-object tracking.This paper provides a comprehensive review of state-of-the-art single-object tracking algorithms based on deep learning.First,we introduce basic knowledge of deep visual tracking,including fundamental concepts,existing algorithms,and previous reviews.Second,we briefly review existing deep learning methods by categorizing them into data-invariant and data-adaptive methods based on whether they can dynamically change their model parameters or architectures.Then,we conclude with the general components of deep trackers.In this way,we systematically analyze the novelties of several recently proposed deep trackers.Thereafter,popular datasets such as Object Tracking Benchmark(OTB)and Visual Object Tracking(VOT)are discussed,along with the performances of several deep trackers.Finally,based on observations and experimental results,we discuss three different characteristics of deep trackers,i.e.,the relationships between their general components,exploration of more effective tracking frameworks,and interpretability of their motion estimation components.

Identification of QTLs for yield and yield components of barley under different growth conditions

Waterlogging is a major abiotic stress limiting barley (Hordeum vulgare L.) yield and its stability in areas with excessive rainfall.Identification of genomic regions influencing the response of yield and its components to waterlogging stress will enhance our understanding of the genetics of waterlogging tolerance and the development of more tolerant barley cultivars.Quantitative trait loci (QTLs) for grain yield and its components were identified using 156 doubled haploid (DH) lines derived from a cross between the cultivars Yerong (waterlogging-tolerant) and Franklin (waterlogging-sensitive) grown under different conditions (waterlogged and well drained).A total of 31 QTLs were identified for the measured characters from two experiments with two growth environments.The phenotypic variation explained by individual QTLs ranged from 4.74% to 55.34%.Several major QTLs determining kernel weight (KW),grains per spike (GS),spikes per plant (SP),spike length (SL) and grain yield (GY) were detected on the same region of chromosome 2H,indicating close linkage or pleiotropy of the gene(s) controlling these traits.Some different QTLs were identified under waterlogging conditions,and thus different markers may have to be used in selecting cultivars suitable for high rainfall areas.

Identifying Conformation States of Polymer through Unsupervised Machine Learning

The study of the critical behavior is important for classifying different configuration states.Recently,machine learning is capable of discriminating polymer states in the presence of human supervision.Here,we introduce an unsupervised approach based on the self-organizing map(SOM)and the autoencoder network to locate critical phase transitions from raw configuration without the necessity for manual feature engineering.High-dimensional configuration data can be encoded to low-dimensional codes by employing neural network of multilayer restrictive Boltzmann machines and the intermediate code can also be reconstructed to high-dimensional input vector.And then the codes are used to cluster different configuration states for polymers adsorbed on the homogeneous and the stripe-patterned surface by the SOM network and K-Means method.This work presents an unusual tool to identify polymer configuration.

Computer Simulation Study on Adsorption and Conformation of Polymer Chains Driven by External Force

In this work,Monte Carlo simulations are used to study the critical adsorption behaviors of flexible polymer chains under the action of an external driving force F parallel to an attractive flat surface.The critical adsorption temperature Tc decreases linearly with increasing F,indicating that the driving force suppresses the adsorption of polymer.The conformation of polymer is also affected by the driving force.However,the effect of F is dependent on the competition between the driving force and temperature.Under strong force or at low temperature,the polymer is stretched along the direction of the force,while under weak force or at high temperature,the polymer is not stretched.When the force is comparable to the temperature,the polymer may be stretched perpendicular to the driving force,and below Tc,we observe conformational transitions from parallel to perpendicular and again to parallel by decreasing the temperature.We found that the perpendicular stretched conformation leads the polymer chain to synchronously move along the direction of the driving force.Moreover,the conformational transitions are attributed to the competition and cooperation between the driving force and the temperature.

Synthesis and Properties Investigation of Thiophene-aromatic Polyesters: Potential Alternatives for the 2,5-Furandicarboxylic Acid-based Ones

In order to explore new substitutes for 2,5 furandicarboxylic acid(FDCA)or poly(ethylene 2,5 furandicarboxylate)(PEF)and try to develop more ideal bio based polyesters,several thiophene aromatic polyesters(PETH,PPTH,PBTH,and PHTH)were synthesized from dimethyl thiophene 2,5-dicarboxylate(DMTD)and different diols,including ethylene glycol,1,3-propanediol,1,4-butanediol,and 1,6-hexanediol.The chemical structures of obtained polyesters were confirmed by nuclear magnetic resonance spectroscopy(H-NMR and 1'C-NMR).Determined by GPC measurement,their average molecular weight(M.)varied from 5.22 x 10*g/mol to 7.94 x 10*g/mol with the molar-mass dispersity of 1.50-2.00.Based on the DSC and TGA results,the synthesized polyesters PETH,PPTH,and PBTH displayed comparable or even better thermal properties when compared with their FDCA-based analogues.From PETH to PHTH,their Tg varied from 64.6°Cto-1°C while Tsm ranged from 409 C to 380°C in nitrogen atmosphere,PETH showed elongation at break as high as 378%,tensile strength of 67 MPa,and tensile modulus of 1800 MPa.Meanwhile,the CO2 and O2 barrier of PETH was 12.0 and 6.6 folds higher than those of PET,respectively,and similar to those of PEF.Considering the overall properties,the synthesized thiophene aromatic polyesters,especially PETH,showed great potential to be used as an excellent bio based packaging material in the future.