Lead remediation by geological fluorapatite combined with Penicillium Oxalicum and Red yeast.

Phosphate solubilizing fungi Penicillium oxalicum (POX) and Red yeast Rhodotorula mucilaginosa (Rho) have been applied in Pb remediation with the combination of fluorapatite (FAp), respectively. The secretion of oxalic acid by POX and the production of extracellular polymers (EPS) by Rho dominate the Pb remediation. In this study, the potential of Pb remediation by the fungal combined system (POX and Rho) with FAp was investigated. After six days of incubation, the combination of POX and Rho showed the highest Pb remove ratio (99.7%) and the lowest TCLP-Pb concentration (2.9 mg/L). The EPS combined with POX also enhanced Pb remediation, which has a 99.3% Pb removal ratio and 5.5 mg/L TCLP-Pb concentration. Meanwhile, Rho and EPS can also stimulate POX to secrete more oxalic acid, which reached 1510.1 and 1450.6 mg/L in six days, respectively. The secreted oxalic acid can promote FAp dissolution and the formation of lead oxalate and pyromorphite. Meanwhile, the EPS produced by Rho can combine with Pb to form EPS-Pb. In the combined system of POX + Rho and POX + EPS, all of the lead oxalate, pyromorphite, and EPS-Pb were observed. Our findings suggest that the combined application of POX and Rho with FAp is an effective approach for enhancing Pb remediation.

Early-onset and late-onset Parkinson's disease exhibit a different profile of gait and posture features based on the Kinect.

INTRODUCTION: Gait and posture abnormalities are the common disabling motor symptoms in Parkinson's disease (PD). This study aims to investigate the differential characteristics of gait and posture in early-onset PD (EOPD) and late-onset PD (LOPD) using the Kinect depth camera. METHODS: Eighty-eight participants, including two subgroups of 22 PD patients and two subgroups of 22 healthy controls (HC) matched for age, sex, and height, were enrolled. Gait and posture features were quantitatively assessed using a Kinect-based system. A two-way analysis of variance was used to compare the difference between different subgroups. RESULTS: EOPD had a significantly higher Gait score than LOPD (p = 0.031). Specifically, decreased swing phase (p = 0.034) was observed in the EOPD group. Although the Posture score was similar between the two groups, LOPD was characterized by an increased forward flexion angle of the trunk at the thorax (p = 0.042) and a decreased forward flexion angle of the head relative to the trunk (p = 0.009). Additionally, age-independent features were observed in both PD subgroups, and post hoc tests revealed that EOPD generally performed worse gait features. In comparison, LOPD was characterized by worse performance in posture features. CONCLUSIONS: EOPD and LOPD exhibit different profiles of gait and posture features. The phenotype-specific characteristics likely reflect the distinct neurodegenerative processes between them.

Kinect-based objective assessment of the acute levodopa challenge test in parkinsonism: a feasibility study.

INTRODUCTION: The acute levodopa challenge test (ALCT) is an important and valuable examination but there are still some shortcomings with it. We aimed to objectively assess ALCT based on a depth camera and filter out the best indicators. METHODS: Fifty-nine individuals with parkinsonism completed ALCT and the improvement rate (IR, which indicates the change in value before and after levodopa administration) of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was calculated. The kinematic features of the patients' movements in both the OFF and ON states were collected with an Azure Kinect depth camera. RESULTS: The IR of MDS-UPDRS III was significantly correlated with the IRs of many kinematic features for arising from a chair, pronation-supination movements of the hand, finger tapping, toe tapping, leg agility, and gait (rs = - 0.277 ~ - 0.672, P < 0.05). Moderate to high discriminative values were found in the selected features in identifying a clinically significant response to levodopa with sensitivity, specificity, and area under the curve (AUC) in the range of 50-100%, 47.22%-97.22%, and 0.673-0.915, respectively. The resulting classifier combining kinematic features of toe tapping showed an excellent performance with an AUC of 0.966 (95% CI = 0.922-1.000, P < 0.001). The optimal cut-off value was 21.24% with sensitivity and specificity of 94.44% and 87.18%, respectively. CONCLUSION: This study demonstrated the feasibility of measuring the effect of levodopa and objectively assessing ALCT based on kinematic data derived from an Azure Kinect-based system.

Kinect-based objective assessment for early frailty identification in patients with Parkinson's disease.

BACKGROUND: Frailty is common in Parkinson's disease (PD) and increases vulnerability to adverse outcomes. Early detection of this syndrome aids in early intervention. AIMS: To objectively identify frailty at an early stage during routine motor tasks in PD patients using a Kinect-based system. METHODS: PD patients were recruited and assessed with the Fried criteria to determine their frailty status. Each participant was recorded performing the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) extremity tasks with a Kinect-based system. Statistically significant kinematic parameters were selected to discriminate the pre-frail from the non-frail group. RESULTS: Of the fifty-two participants, twenty were non-frail and thirty-two were pre-frail. Decreased frequency in finger tapping (P = 0.005), hand grasping (P = 0.002), toe tapping (P = 0.002), and leg agility (P = 0.019) alongside reduced hand grasping speed (P = 0.030), lifting (P < 0.001) and falling speed (P < 0.001) in leg agility were observed in the pre-frail group. Amplitude in leg agility (P = 0.048) and amplitude decrement rate (P = 0.046) in hand grasping showed marginally significant differences between two groups. Moderate discriminative values were found in frequency and speed of the extremity tasks to identify pre-frailty with sensitivity, specificity, and area under the curve (AUC) in the range of 45.00-85.00%, 68.75-100%, and 0.701-0.836, respectively. The combination of frequency and speed in extremity tasks showed moderate to high discriminatory ability, with AUC of 0.775 (95% CI 0.637-0.913, P < 0.001) for upper limb tasks and 0.909 (95% CI 0.832-0.987, P < 0.001) for lower limb tasks. When combining these features in both upper and lower limb tasks, the AUC increased to 0.942 (95% CI 0.886-0.999, P < 0.001). CONCLUSIONS: Our findings demonstrated the promise of utilizing Kinect-based kinematic data from MDS-UPDRS III tasks as early indicators of frailty in PD patients.

Combination of mineral protection and molecular characteristics rather than alone to govern soil organic carbon stability in Qinghai-Tibetan plateau wetlands.

Wetlands in the Yarlung Tsangpo River Basin (YTR) on the Qinghai-Tibet Plateau provide immense soil organic carbon (SOC) storage, which is highly susceptible to climate warming and requires urgent deciphering SOC stabilization mechanisms of long-term protection of SOC against decomposition. Conflicting views exist regarding whether persistent SOC is controlled by molecular features or by mineral protection. As such, this study quantified SOC stability using two thermal indices (TG-T50, and DSC), described molecular features of SOC using pyrolysis-gas chromatography-mass spectrometry, and measured SOC protection by minerals using a chemical extraction method. Results indicated SOC of topsoils had higher thermal stability, with TG-T50 and DSC-T50 of 337.61 °C and 384.58 °C, than that of subsoils with TG-T50 and DSC-T50 of 337.32 and 382.67 °C, respectively. We found subsoils had significantly higher proportions of aliphatic and aromatic compounds, while existed higher SOC associated with minerals. It seemed SOC stabilization differed with soil depths, in which mineral protection dictated SOC thermal stability in topsoils while molecular features posed a more important constraint on SOC stabilization in subsoils. Overall, our findings support the hypothesis of physical and chemical protection but emphasized that SOC thermal stability largely depended on to extent of the combination between molecular features and mineral protection, which explained 55% in topsoils and 73% in subsoils, respectively.

Automated and accurate assessment for postural abnormalities in patients with Parkinson's disease based on Kinect and machine learning.

BACKGROUND: Automated and accurate assessment for postural abnormalities is necessary to monitor the clinical progress of Parkinson's disease (PD). The combination of depth camera and machine learning makes this purpose possible. METHODS: Kinect was used to collect the postural images from 70 PD patients. The collected images were processed to extract three-dimensional body joints, which were then converted to two-dimensional body joints to obtain eight quantified coronal and sagittal features (F1-F8) of the trunk. The decision tree classifier was carried out over a data set established by the collected features and the corresponding doctors' MDS-UPDRS-III 3.13 (the 13th item of the third part of Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale) scores. An objective function was implanted to further improve the human-machine consistency. RESULTS: The automated grading of postural abnormalities for PD patients was realized with only six selected features. The intraclass correlation coefficient (ICC) between the machine's and doctors' score was 0.940 (95%CI, 0.905-0.962), meaning the machine was highly consistent with the doctors' judgement. Besides, the decision tree classifier performed outstandingly, reaching 90.0% of accuracy, 95.7% of specificity and 89.1% of sensitivity in rating postural severity. CONCLUSIONS: We developed an intelligent evaluation system to provide accurate and automated assessment of trunk postural abnormalities in PD patients. This study demonstrates the practicability of our proposed method in the clinical scenario to help making the medical decision about PD.

Overexpression of human MX2 gene suppresses cell proliferation, migration, and invasion via ERK/P38/NF-κB pathway in glioblastoma cells.

In human, there are two myxovirus resistance genes-MX1 and MX2, which respectively encode MXA and MXB protein. For MXB, it was traditionally deemed to work in the progression of cell cycle and adjustment of nuclear import. Thus, we speculated that it might play important roles in tumor progression. The purpose of this study was to preliminarily explore the underlying functions and mechanism of the MX2 gene on glioblastoma multiforme. Quantitative reverse transcription polymerase chain reaction, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT), and transwell experiments were to detect the relative MX2 mRNA level and its biological functions on glioma cells, respectively. The data displayed that MX2 was obviously downregulated both in glioblastoma (GBM) and GBM cell lines, meanwhile, its overexpression could markedly reduce cell proliferation, migration, and invasion of glioma cells, implying that it was related with glioblastoma progression. In addition, the overall survival of patient with glioblastoma had a negative correlation with the MX2 expression. Then, Western blot indicated the potential mechanism of MX2 in glioblastoma. We found that MX2 overexpression could decrease the relative levels of phosphorylated-ERK1/2 (p-ERK1/2), p-p38, and nuclear factor-κB (NF-κB), while have no effects on extracellular signal-regulated kinase (ERK), p38, and lamin B1. Moreover, the influences of MX2 overexpression on cell proliferation, migration, and invasion could be weakened by the three inhibitors (PD98059, SB203580, and (pyridin-2-ylmethyl) dithiocarbamate [PDTC]). These results implied that MX2 might suppress the proliferation and metastasis of glioma cells by manipulating the ERK/P38/NF-κB signaling pathway. In conclusion, MX2 is potential to be a new marker used for glioblastoma prognosis or a new target for glioblastoma treatments.

RNA-Seq Expression Analysis of Enteric Neuron Cells with Rotenone Treatment and Prediction of Regulated Pathways.

The enteric nervous system (ENS) is involved in the initiation and development of the pathological process of Parkinson's disease (PD). The effect of rotenone on the ENS may trigger the progression of PD through the central nervous system (CNS). In this study, we used RNA-sequencing (RNA-seq) analysis to examine differential expression genes (DEGs) and pathways induced by in vitro treatment of rotenone in the enteric nervous cells isolated from rats. We identified 45 up-regulated and 30 down-regulated genes. The functional categorization revealed that the DEGs were involved in the regulation of cell differentiation and development, response to various stimuli, and regulation of neurogenesis. In addition, the pathway and network analysis showed that the Mitogen Activated Protein Kinase (MAPK), Toll-like receptor, Wnt, and Ras signaling pathways were intensively involved in the effect of rotenone on the ENS. Additionally, the quantitative real-time polymerase chain reaction result for the selected seven DEGs matched those of the RNA-seq analysis. Our results present a significant step in the identification of DEGs and provide new insight into the progression of PD in the rotenone-induced model.

The in vivo characterization of electrospun heparin-bonded polycaprolactone in small-diameter vascular reconstruction.

OBJECTIVE: To evaluate the possibility of using heparin-bonded polycaprolactone grafts to replace small-diameter arteries. METHODS: Polycaprolactone was bonded with heparin. The activated partial thromboplastin time of heparin-bonded polycaprolactone grafts was determined in vitro. Small-diameter grafts were electrospun with heparin-bonded polycaprolactone and polycaprolactone and were implanted in dogs to substitute part of the femoral artery. Angiography was used to investigate the patency and aneurysm of the grafts after transplantation. After angiography, the patent grafts were explanted for histology analysis. The degradation of the grafts and the collagen content of the grafts were measured. RESULTS: Activated partial thromboplastin time tests in vitro showed that heparin-bonded polycaprolactone grafts exhibit obvious anticoagulation. Arteriography showed that two heparin-bonded polycaprolactone and three polycaprolactone grafts were obstructed. Other grafts were patent, without aneurysm formation. Histological analysis showed that the tested grafts degraded evidently over the implantation time and that the luminal surface of the tested grafts had become covered by endothelial cells. Collagen deposition in heparin-bonded polycaprolactone increased with time. There were no calcifications in the grafts. Gel permeation chromatography showed the heparin-bonded polycaprolactone explants at 12 weeks lose about 32% for Mw and 24% for Mn. The collagen content on the heparin-bonded polycaprolactone grafts increased over time. CONCLUSION: This preliminary study demonstrates that heparin-bonded polycaprolactone is a suitable graft for small artery reconstruction. However, heparin-bonded polycaprolactone degrades more rapidly than polycaprolactone in vivo.

Multifactor analysis for risk factors involved in the fear of falling in patients with chronic stroke from mainland China.

OBJECTIVE: To analyze the risk factors involved in FOF in patients with chronic stroke from mainland China. METHODS: A cohort of 245 patients with chronic stroke were included in this study. Fear of falling severity was assessed using the Activities-specific Balance Confidence (ABC) Scale. Physical function was assessed using the Berg Balance Scale (BBS), the Timed Up and Go Test (TUGT), and the lower extremity of Fugl-Meyer Assessment. Psychosocial function was assessed with the Center for Epidemiologic Studies Depression (CES-D) Scale, the State-Trait Anxiety Inventory, and the Social Support Rating Scale, respectively. All factors related to FOF severity were analyzed by regression analysis. RESULTS: Statistically significant factors affecting FOF severity included age, history of falling, balance, functional mobility, economic burden, and depression. Participants with a history of falls (N = 81) were divided into high (score ≥ 70, N = 19) and low ABC score (score < 70, N = 62) groups. Compared with the low ABC score group, the high ABC score group had higher BBS scores, and lower CES-D scores. CONCLUSIONS: Our findings suggest that - in addition to age, economic burden, and a history of falls - balance, functional mobility, and depression are risk factors associated with FOF in patients with chronic stroke in mainland China.

Krüppel-like factor 5: a novel biomarker for lymph node metastasis and recurrence in supraglottic squamous cell laryngeal carcinoma.

Krüppel-like factor 5 (KLF5), a zinc finger-containing transcription factor, is involved in important biological processes including cell transformation, proliferation, and carcinogenesis. However, its clinical significance has remained largely unknown in laryngeal cancer. Here, specimens from 144 patients with laryngeal tumors were investigated by immunohistochemical staining for KLF5, integrin-linked kinase (ILK), and E-cadherin expressions. A clinicopathological study revealed that the KLF5 expression level in tumor cells was significantly correlated with lymph node metastasis (P < 0.05) and local recurrence (P < 0.05). In addition, KLF5, ILK, and E-cadherin (epithelial-mesenchymal transition (EMT) biomarker) expressions were correlated with each other. These findings suggest that KLF5 may be an epithelial-mesenchymal transition-associated biomarker in human laryngeal carcinomas and play important roles in the progression of laryngeal carcinomas. KLF5 immunoreactivity is therefore considered a potential lymph node metastasis and recurrence factor in human laryngeal cancers. In addition, the KLF5-mediated pathway is a potential target for elimination of laryngeal cancer in the future.

Construction and validation of a clinical prediction model for deep vein thrombosis in patients with digestive system tumors based on a machine learning.

This study developed a deep vein thrombosis (DVT) risk prediction model based on multiple machine learning methods for patients with digestive system tumors undergoing surgical treatment. Data of 1048 patients with digestive system tumors admitted to Shanxi Provincial People's Hospital (College of Shanxi Medical University) from January 2020 to January 2023 were retrospectively analyzed, and 845 cases were screened according to the inclusion and exclusion criteria. The patients were divided into a training group (586 patients), and a validation group (259 patients), then feature selection was performed using six models, including Lasso regression, XGBoost, Random Forest, Decision Tree, Support Vector Machine, and Logistics. Predictive models were subsequently constructed from column-line plots, and the predictive validity of the models was assessed using receiver operating characteristic curves, precision-recall curves, and decision-curve analysis. In the model comparison, the XGBoost model showed the largest area under the curve (AUC) on the validation set (P < 0.05), demonstrating excellent predictive performance and generalization ability. We selected the common characteristic factors in the six models to further develop the column line plots to assess the DVT risk. The model performed well in clinical validation and effectively differentiated high-risk and low-risk patients. The differences in BMI, procedure time, and D-dimer were statistically significant between patients in the thrombus group and those in the non-thrombus group (P < 0.05). However, the AUC of the Xgboost model was found to be greater than that of the column chart model by the Delong test (P < 0.05). BMI, procedure time, and D-dimer are critical predictors of DVT risk in patients with digestive system tumors. Our model is an adequate assessment tool for DVT risk, which can help improve the prevention and treatment of DVT.

Contrasting diversity patterns and drivers of aquatic macroinvertebrates in floodplain and non-floodplain wetlands.

Understanding diversity patterns and underlying drivers is one of the central topics in the fields of biogeography and community ecology. Aquatic macroinvertebrates are widely distributed in various wetlands and play vital ecological roles. Previous studies mainly have focused on macroinvertebrate diversity in a single type of wetland. Our understanding of the differences in diversity patterns and underlying drivers between different wetland types remains limited. Here, we compared diversity patterns and community assembly of floodplain wetlands (FWs) and non-floodplain wetlands (NWs) in the Sanjiang Plain, Northeast China. We found that the taxonomic richness and abundance were higher in NWs than those in FWs. Nineteen taxa were identified as habitat specialists in the NWs, whereas only four taxa were designated as habitat specialists in the FWs. In addition, the FW and NW assemblages exhibited contrasting compositions. Spatial and environmental variables explained the largest variations in the macroinvertebrate assemblages of NWs and FWs, respectively. Normalised stochasticity ratios and Sloan neutral models confirmed that the macroinvertebrate community assembly of both wetland types was driven largely by stochastic processes. Stochastic processes were more prominent in shaping macroinvertebrate communities of FWs, whereas a stronger dispersal limitation was detected in NWs. Our results revealed contrasting diversity patterns and assembly mechanisms of macroinvertebrate communities in FWs and NWs. We underscore the importance of flood disturbance in shaping wetland ecosystems in the Sanjiang Plain and highlight that conservation and restoration actions cover different types of wetland habitats.

VIOLET: Visual Analytics for Explainable Quantum Neural Networks.

With the rapid development of Quantum Machine Learning, quantum neural networks (QNN) have experienced great advancement in the past few years, harnessing the advantages of quantum computing to significantly speed up classical machine learning tasks. Despite their increasing popularity, the quantum neural network is quite counter-intuitive and difficult to understand, due to their unique quantum-specific layers (e.g., data encoding and measurement) in their architecture. It prevents QNN users and researchers from effectively understanding its inner workings and exploring the model training status. To fill the research gap, we propose VIOLET, a novel visual analytics approach to improve the explainability of quantum neural networks. Guided by the design requirements distilled from the interviews with domain experts and the literature survey, we developed three visualization views: the Encoder View unveils the process of converting classical input data into quantum states, the Ansatz View reveals the temporal evolution of quantum states in the training process, and the Feature View displays the features a QNN has learned after the training process. Two novel visual designs, i.e., satellite chart and augmented heatmap, are proposed to visually explain the variational parameters and quantum circuit measurements respectively. We evaluate VIOLET through two case studies and in-depth interviews with 12 domain experts. The results demonstrate the effectiveness and usability of VIOLET in helping QNN users and developers intuitively understand and explore quantum neural networks.

Investigation on Mechanism of Microstructure Evolution during Multi-Process Hot Forming of GH4169 Superalloy Forging.

Typically, in the manufacturing of GH4169 superalloy forgings, the multi-process hot forming that consists of pre-deformation, heat treatment and final deformation is required. This study focuses on the microstructural evolution throughout hot working processes. Considering that δ phase can promote nucleation and limit the growth of grains, a process route was designed, including pre-deformation, aging treatment (AT) to precipitate sufficient δ phases, high temperature holding (HTH) to uniformly heat the forging, and final deformation. The results show that the uneven strain distribution after pre-deformation has a significant impact on the subsequent refinement of the grain microstructure due to the complex coupling relationship between the evolution of the δ phase and recrystallization behavior. After the final deformation, the fine-grain microstructure with short rod-like δ phases as boundaries is easy to form in the region with a large strain of the pre-forging. However, necklace-like mixed grain microstructure is formed in the region with a small strain of the pre-forging. In addition, when the microstructure before final deformation consists of mixed grains, dynamic recrystallization (DRX) nucleation behavior preferentially depends on kernel average misorientation (KAM) values. A large KAM can promote the formation of DRX nuclei. When the KAM values are close, a smaller average grain size of mixed-grain microstructure is more conductive to promote the DRX nucleation. Finally, the interaction mechanisms between δ phase and DRX nucleation are revealed.

IGF-1 antibody prolongs the effective duration time of botulinum toxin in decreasing muscle strength.

Botulinum toxin type-A (Btx-A), a powerful therapeutic tool in various medical specialties, requires repeated injections to maintain its effect. Therefore, novel methods to prolong the effective duration time of Btx-A are highly needed. Rats were assigned to three major groups: control group (n = 30), Btx-A group (n = 30), and IGF-1 Ab groups. IGF-1 Ab groups were composed by sub-groups A1-A5 (each has 25 rats) for the subsequent IGF-1Ab dose-effect study. Muscle strength was determined by a survey system for rat lower limbs nerve and muscle function. Muscle-specific receptor tyrosine kinase (MuSK), Insulin-like growth factor binding protein-5 (IGFBP5), and growth-associated protein, 43-kDa (GAP43) were determined by real-time polymerase chain reactions (PCRs) and Western blot. We found that Btx-A decreased the muscle strength, with a paralysis maintained for 70 days. IGF-1Ab prolonged the effective duration time of Btx-A. Real-time PCRs and Western blot showed that IGF-1Ab delayed the increase of MuSK and IGFBP5 after Btx-A injection, without affecting GAP43. These results indicate that IGF-1Ab might prolong the effective duration time of Btx-A on muscle strength through delaying the increase of MuSK. It would be interesting to determine whether IGF-1Ab can be used as an auxiliary measure to the Btx-A treatment in the future.

[Special issues in endovascular treatment of lower extremities arteriosclerosis obliterans].

OBJECTIVE: To explore the clinical efficacy of endovascular treatment for lower extremity arteriosclerosis obliterans. METHODS: A total of 34 patients (43 limbs) with lower extremity arteriosclerosis obliterans undergoing endovascular treatment from July 2010 to July 2012 were analyzed. The cohort had Fontaine stage II b (n = 16), Fontaine stage III (n = 10) and Fontaine stage III (n = 8). Among them, the lesions were of TASC IIA (n = 4), TASC IIB (n = 8), TASC IIC (n = 9) and TASC IID (n = 13). All patients underwent percutaneous transluminal angioplasty (PTA) plus stents after computed tomographic angiography (CTA) or digital subtraction angiography (DSA). And 9 patients underwent femoral endarterectomy associated with endovascular treatment. RESULTS: The success rate of this technique was 100%. One iliac artery ruptured during endovascular surgery. One patient suffered intraoperatively from arterial perforation. One patient was amputated one week later. One patient had in-stent thrombosis at Week 3 post-treatment. One patient was amputated at Week 4 after endovascular treatment. Thirty patients (38 limbs) were followed up for 13.3 months. During the follow-up, 3, 4 and 4 limbs became occluded at Month 6, 12 and 24 post-treatment respectively. CONCLUSION: Endovascular treatment has an excellent early patency rate. Special issues should be properly handled during endovascular treatment.

QuantumEyes: Towards Better Interpretability of Quantum Circuits.

Quantum computing offers significant speedup compared to classical computing, which has led to a growing interest among users in learning and applying quantum computing across various applications. However, quantum circuits, which are fundamental for implementing quantum algorithms, can be challenging for users to understand due to their underlying logic, such as the temporal evolution of quantum states and the effect of quantum amplitudes on the probability of basis quantum states. To fill this research gap, we propose QuantumEyes, an interactive visual analytics system to enhance the interpretability of quantum circuits through both global and local levels. For the global-level analysis, we present three coupled visualizations to delineate the changes of quantum states and the underlying reasons: a Probability Summary View to overview the probability evolution of quantum states; a State Evolution View to enable an in-depth analysis of the influence of quantum gates on the quantum states; a Gate Explanation View to show the individual qubit states and facilitate a better understanding of the effect of quantum gates. For the local-level analysis, we design a novel geometrical visualization dandelion chart to explicitly reveal how the quantum amplitudes affect the probability of the quantum state. We thoroughly evaluated QuantumEyes as well as the novel dandelion chart integrated into it through two case studies on different types of quantum algorithms and in-depth expert interviews with 12 domain experts. The results demonstrate the effectiveness and usability of our approach in enhancing the interpretability of quantum circuits.

Differential distribution patterns and assembly processes of soil microbial communities under contrasting vegetation types at distinctive altitudes in the Changbai Mountain.

Diversity patterns and community assembly of soil microorganisms are essential for understanding soil biodiversity and ecosystem processes. Investigating the impacts of environmental factors on microbial community assembly is crucial for comprehending the functions of microbial biodiversity and ecosystem processes. However, these issues remain insufficiently investigated in related studies despite their fundamental significance. The present study aimed to assess the diversity and assembly of soil bacterial and fungal communities to altitude and soil depth variations in mountain ecosystems by using 16S and ITS rRNA gene sequence analyses. In addition, the major roles of environmental factors in determining soil microbial communities and assembly processes were further investigated. The results showed a U-shaped pattern of the soil bacterial diversity at 0-10 cm soil depth along altitudes, reaching a minimum value at 1800 m, while the fungal diversity exhibited a monotonically decreasing trend with increasing altitude. At 10-20 cm soil depth, the soil bacterial diversity showed no apparent changes along altitudinal gradients, while the fungal Chao1 and phylogenetic diversity (PD) indices exhibited hump-shaped patterns with increasing altitude, reaching a maximum value at 1200 m. Soil bacterial and fungal communities were distinctively distributed with altitude at the same depth of soil, and the spatial turnover rates in fungi was greater than in bacteria. Mantel tests suggested soil physiochemical and climate variables significantly correlated with the ß diversity of microbial community at two soil depths, suggesting both soil and climate heterogeneity contributed to the variation of bacterial and fungal community. Correspondingly, a novel phylogenetic null model analysis demonstrated that the community assembly of soil bacterial and fungal communities were dominated by deterministic and stochastic processes, respectively. The assembly processes of bacterial community were significantly related to the soil DOC and C:N ratio, while the fungal community assembly processes were significantly related to the soil C:N ratio. Our results provide a new perspective to assess the responses of soil microbial communities to variations with altitude and soil depth.

Kinect-based objective evaluation of bradykinesia in patients with Parkinson's disease.

Objective: To quantify bradykinesia in Parkinson's disease (PD) with a Kinect depth camera-based motion analysis system and to compare PD and healthy control (HC) subjects. Methods: Fifty PD patients and twenty-five HCs were recruited. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was used to evaluate the motor symptoms of PD. Kinematic features of five bradykinesia-related motor tasks were collected using Kinect depth camera. Then, kinematic features were correlated with the clinical scales and compared between groups. Results: Significant correlations were found between kinematic features and clinical scales (P < 0.05). Compared with HCs, PD patients exhibited a significant decrease in the frequency of finger tapping (P < 0.001), hand movement (P < 0.001), hand pronation-supination movements (P = 0.005), and leg agility (P = 0.003). Meanwhile, PD patients had a significant decrease in the speed of hand movements (P = 0.003) and toe tapping (P < 0.001) compared with HCs. Several kinematic features exhibited potential diagnostic value in distinguishing PD from HCs with area under the curve (AUC) ranging from 0.684-0.894 (P < 0.05). Furthermore, the combination of motor tasks exhibited the best diagnostic value with the highest AUC of 0.955 (95% CI = 0.913-0.997, P < 0.001). Conclusion: The Kinect-based motion analysis system can be applied to evaluate bradykinesia in PD. Kinematic features can be used to differentiate PD patients from HCs and combining kinematic features from different motor tasks can significantly improve the diagnostic value.