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"Jing, Zhang"
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Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson’s disease
Parkinson’s disease (PD) is a common, progressive, and currently incurable neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in the differential diagnosis of parkinsonism and in early PD detection. Due to the advantages of machine learning such as learning complex data patterns and making inferences for individuals, machine-learning techniques have been increasingly applied to the diagnosis of PD, and have shown some promising results. Machine-learning-based imaging applications have made it possible to help differentiate parkinsonism and detect PD at early stages automatically in a number of neuroimaging studies. Comparative studies have shown that machine-learning-based SPECT image analysis applications in PD have outperformed conventional semi-quantitative analysis in detecting PD-associated dopaminergic degeneration, performed comparably well as experts’ visual inspection, and helped improve PD diagnostic accuracy of radiologists. Using combined multi-modal (imaging and clinical) data in these applications may further enhance PD diagnosis and early detection. To integrate machine-learning-based diagnostic applications into clinical systems, further validation and optimization of these applications are needed to make them accurate and reliable. It is anticipated that machine-learning techniques will further help improve differential diagnosis of parkinsonism and early detection of PD, which may reduce the error rate of PD diagnosis and help detect PD at pre-motor stage to make it possible for early treatments (e.g., neuroprotective treatment) to slow down PD progression, prevent severe motor symptoms from emerging, and relieve patients from suffering.
Journal Article
Dynamic evolution of utilization efficiency of medical and health services in China
In order to optimize the Chinese medical and health system and improve people’s health level, the SFA Malmquist model, the spatial econometric model, and the standard deviation ellipse method were used to measure the efficiency of medical and health services in China’s 31 provinces between 2010 and 2020. Study results indicated that the average efficiency value of the 31 provinces generally exceeded 0.8. Specifically, the average efficiency values in the eastern and central regions increased from 0.852 to 0.875 and from 0.858 to 0.88, respectively. In the western and northeastern regions, these values rose from 0.804 to 0.835 and from 0.827 to 0.854, respectively. From the perspective of spatial distribution, there were high-high and low-low clusters in most provinces with significant spatial dependence among them. This analysis reveals that medical and health services efficiency in China demonstrates a spatial pattern extending from northeast to southwest.
Journal Article
Projection Profiling: A Data Compressing Strategy in Three-Dimensional Liquid Chromatography for Quality Control of Traditional Herbal Medicine
Chromatographic fingerprint technology has become the standard of quality control for traditional herbal medicines (THMs). But several issues are associated with the wavelength selection of the representative fingerprint, such as contradictory evaluation results at different wavelengths and the accurate quantification of each composition at one wavelength. These problems can be addressed by projection profiling. Projection profiling is a collection of all sample compositions at the maximum absorption wavelength after baseline correction. In this paper, eleven baseline correction algorithms are optimized by using the effective information factor (EI) as an indicator. The influence of different integration methods and wavelengths on analytical method validation and similarity analysis results are discussed in detail to clarify the advantages of the projection profiling. A total of 33 batches of Compound Licorice Tablets (CLTs) were used to show the influence of different wavelengths in a similarity evaluation. The results show that projection profiling is a better choice than any chromatogram at a certain wavelength, because projection profiling is more informative, accurate, and stable.
Journal Article
Error-mitigated quantum gates exceeding physical fidelities in a trapped-ion system
Various quantum applications can be reduced to estimating expectation values, which are inevitably deviated by operational and environmental errors. Although errors can be tackled by quantum error correction, the overheads are far from being affordable for near-term technologies. To alleviate the detrimental effects of errors on the estimation of expectation values, quantum error mitigation techniques have been proposed, which require no additional qubit resources. Here we benchmark the performance of a quantum error mitigation technique based on probabilistic error cancellation in a trapped-ion system. Our results clearly show that effective gate fidelities exceed physical fidelities, i.e., we surpass the break-even point of eliminating gate errors, by programming quantum circuits. The error rates are effectively reduced from (1.10 ± 0.12) × 10
−3
to (1.44 ± 5.28) × 10
−5
and from (0.99 ± 0.06) × 10
−2
to (0.96 ± 0.10) × 10
−3
for single- and two-qubit gates, respectively. Our demonstration opens up the possibility of implementing high-fidelity computations on a near-term noisy quantum device.
Quantum error mitigation promises to improve expectation values’ estimation without the resource overhead of quantum error correction. Here, the authors test probabilistic error cancellation using trapped ions, decreasing single- and two-qubit gates’ error rates by two and one order of magnitude respectively.
Journal Article
Triglyceride-glucose index predicts adverse cardiovascular events in patients with diabetes and acute coronary syndrome
Background
The triglyceride-glucose index (TyG index) has been regarded as a reliable alternative marker of insulin resistance and an independent predictor of cardiovascular outcomes. Whether the TyG index predicts adverse cardiovascular events in patients with diabetes and acute coronary syndrome (ACS) remains uncertain. The aim of this study was to investigate the prognostic value of the TyG index in patients with diabetes and ACS.
Methods
A total of 2531 consecutive patients with diabetes who underwent coronary angiography for ACS were enrolled in this study. Patients were divided into tertiles according to their TyG index. The primary outcomes included the occurrence of major adverse cardiovascular events (MACEs), defined as all-cause death, non-fatal myocardial infarction and non-fatal stroke. The TyG index was calculated as the ln (fasting triglyceride level [mg/dL] × fasting glucose level [mg/dL]/2).
Results
The incidence of MACE increased with TyG index tertiles at a 3-year follow-up. The Kaplan–Meier curves showed significant differences in event-free survival rates among TyG index tertiles (P = 0.005). Multivariate Cox hazards regression analysis revealed that the TyG index was an independent predictor of MACE (95% CI 1.201–1.746; P < 0.001). The optimal TyG index cut-off for predicting MACE was 9.323 (sensitivity 46.0%; specificity 63.6%; area under the curve 0.560; P = 0.001). Furthermore, adding the TyG index to the prognostic model for MACE improved the C-statistic value (P = 0.010), the integrated discrimination improvement value (P = 0.001) and the net reclassification improvement value (P = 0.019).
Conclusions
The TyG index predicts future MACE in patients with diabetes and ACS independently of known cardiovascular risk factors, suggesting that the TyG index may be a useful marker for risk stratification and prognosis in patients with diabetes and ACS.
Journal Article
Electrocatalysts for Hydrogen Evolution in Alkaline Electrolytes: Mechanisms, Challenges, and Prospective Solutions
Hydrogen evolution reaction (HER) in alkaline medium is currently a point of focus for sustainable development of hydrogen as an alternative clean fuel for various energy systems, but suffers from sluggish reaction kinetics due to additional water dissociation step. So, the state‐of‐the‐art catalysts performing well in acidic media lose considerable catalytic performance in alkaline media. This review summarizes the recent developments to overcome the kinetics issues of alkaline HER, synthesis of materials with modified morphologies, and electronic structures to tune the active sites and their applications as efficient catalysts for HER. It first explains the fundamentals and electrochemistry of HER and then outlines the requirements for an efficient and stable catalyst in alkaline medium. The challenges with alkaline HER and limitation with the electrocatalysts along with prospective solutions are then highlighted. It further describes the synthesis methods of advanced nanostructures based on carbon, noble, and inexpensive metals and their heterogeneous structures. These heterogeneous structures provide some ideal systems for analyzing the role of structure and synergy on alkaline HER catalysis. At the end, it provides the concluding remarks and future perspectives that can be helpful for tuning the catalysts active‐sites with improved electrochemical efficiencies in future. In this review, recent progress and solutions to the challenges associated with electrocatalysts for hydrogen evolution reaction (HER) in alkaline electrolytes are systematically explained. It further describes the reaction controlling factors and ambiguity of the alkaline HER process and outlines the possible ways to enhance the catalyst efficiency and stability. By modifying the electronic structure of catalysts through developing their heterostructures can overcome the water dissociation barrier to realize alkaline HER.
Journal Article
Bilateral Erector Spinae Plane Blocks for Open Posterior Lumbar Surgery
Erector spinae plane block (ESPB) is a newly reported interfascial plane block in pain management, and it can block the nerves exactly in line with the area of the posterior lumbar surgery. The objective of this research was to determine the effectiveness of pre-operative ESPB in enhancing recovery of posterior lumbar surgery.
A total of 60 patients undergoing open posterior lumbar decompression surgery under general anesthesia were randomized into two groups. T12 group was performed pre-operatively bilateral ESPB with ropivacaine at the T12 level, but control group did not receive the block. The primary outcome was the Modified Observer's Assessment of Alertness/Sedation (MOAA/S) score at 10 minutes after extubation. Secondary outcomes included intraoperative sufentanil consumption, postoperative morphine consumption, first time to ambulation after surgery and hospital length of stay after surgery. All participants were followed up to hospital discharge.
The mean (SD) MOAA/S scores at 10 minutes after extubation were 4.2 (95% CI, 4.0 to 4.4), and 3.4 (95% CI, 3.2 to 3.6) in the T12 and control groups (P <0.001), respectively. Intraoperative sufentanil consumption (P =0.007) and postoperative morphine consumption (P =0.003) were lower in the T12 group than in the control group. Although first time to ambulation after surgery was sooner in the T12 group than in the control group (P =0.003), hospital length of stay was similar (P=0.054).
Pre-operative bilateral ESPB at T12 can enhance recovery after posterior lumbar surgery and reduce perioperative opioid consumption.
Journal Article
Prospect for constraining holographic dark energy with gravitational wave standard sirens from the Einstein Telescope
We study the holographic dark energy (HDE) model by using the future gravitational wave (GW) standard siren data observed from the Einstein Telescope (ET) in this work. We simulate 1000 GW standard siren data based on a 10-year observation of the ET to make this analysis. We find that all the cosmological parameters in the HDE model can be tremendously improved by including the GW standard siren data in the cosmological fit. The GW data combined with the current cosmic microwave background anisotropies, baryon acoustic oscillations, and type Ia supernovae data will measure the cosmological parameters
Ω
m
,
H
0
, and
c
in the HDE model to be at the accuracies of 1.28%, 0.59%, and 3.69%, respectively. A comparison with the cosmological constant model and the constant-
w
dark energy model shows that, compared to the standard model, the parameter degeneracies will be broken more thoroughly in a dynamical dark energy model. We find that the GW data alone can provide a fairly good measurement for
H
0
, but for other cosmological parameters the GW data alone can only provide rather weak measurements. However, due to the fact that the parameter degeneracies can be broken by the GW data, the standard sirens can play an essential role in improving the parameter estimation.
Journal Article
The Chinese Society of Clinical Oncology (CSCO): clinical guidelines for the diagnosis and treatment of gastric cancer
China is one of the countries with the highest incidence of gastric cancer. There are differences in epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selection between gastric cancer patients from the Eastern and Western countries. Non-Chinese guidelines cannot specifically reflect the diagnosis and treatment characteristics for the Chinese gastric cancer patients. The Chinese Society of Clinical Oncology (CSCO) arranged for a panel of senior experts specializing in all sub-specialties of gastric cancer to compile, discuss, and revise the guidelines on the diagnosis and treatment of gastric cancer based on the findings of evidence-based medicine in China and abroad. By referring to the opinions of industry experts, taking into account of regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted experts’ consensus judgement on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes. This guideline uses tables and is complemented by explanatory and descriptive notes covering the diagnosis, comprehensive treatment, and follow-up visits for gastric cancer.
Journal Article