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Background Transcranial direct current stimulation (tDCS) has shown mixed results for depression treatment. The efficacies of tDCS combination therapies have not been investigated deliberately. This review aims to evaluate the clinical efficacy of tDCS as a monotherapy and in combination with medication, psychotherapy, and ECT for treating adult patients with major depressive disorder (MDD) and identified the factors influencing treatment outcome measures (i.e. depression score, dropout, response, and remission rates). Methods The systematic review was performed in PubMed/Medline, EMBASE, PsycINFO, Web of Sciences, and OpenGrey. Two authors performed independent literature screening and data extraction. The primary outcomes were the standardized mean difference (SMD) for continuous depression scores after treatment and odds ratio (OR) dropout rate; secondary outcomes included ORs for response and remission rates. Random effects models with 95% confidence intervals were employed in all outcomes. The overall effect of tDCS was investigated by meta-analysis. Sources of heterogeneity were explored via subgroup analyses, meta-regression, sensitivity analyses, and assessment of publication bias. Results Twelve randomised, sham-controlled trials (active group: N = 251, sham group: N = 204) were included. Overall, the integrated depression score of the active group after treatment was significantly lower than that of the sham group (g = − 0.442, p = 0.017), and further analysis showed that only tDCS + medication achieved a significant lower score (g = − 0.855, p p = 0.006), while the response rate remained unchanged for the other three therapies. Dropout and remission rates were similar in the active and sham groups for each therapy and also for the overall intervention. The meta-regression results showed that current intensity is the only predictor for the response rate. None of publication bias was identified. Conclusion The effect size of tDCS treatment was obviously larger in depression score compared with sham stimulation. The tDCS combined selective serotonin re-uptake inhibitors is the optimized therapy that is effective on depression score and response rate. tDCS monotherapy and combined psychotherapy have no significant effects. The most important parameter for optimization in future trials is treatment strategy.

Objective. Closed-loop deep brain stimulation (DBS) with neural feedback has shown great potential in improving the therapeutic effect and reducing side effects. However, the amplitude of stimulation artifacts is much larger than the local field potentials, which remains a bottleneck in developing a closed-loop stimulation strategy with varied parameters. Approach. We proposed an irregular sampling method for the real-time removal of stimulation artifacts. The artifact peaks were detected by applying a threshold to the raw recordings, and the samples within the contaminated period of the stimulation pulses were excluded and replaced with the interpolation of the samples prior to and after the stimulation artifact duration. This method was evaluated with both simulation signals and in vivo closed-loop DBS applications in Parkinsonian animal models. Main results. The irregular sampling method was able to remove the stimulation artifacts effectively with the simulation signals. The relative errors between the power spectral density of the recovered and true signals within a wide frequency band (2–150 Hz) were 2.14%, 3.93%, 7.22%, 7.97% and 6.25% for stimulation at 20 Hz, 60 Hz, 130 Hz, 180 Hz, and stimulation with variable low and high frequencies, respectively. This stimulation artifact removal method was verified in real-time closed-loop DBS applications in vivo, and the artifacts were effectively removed during stimulation with frequency continuously changing from 130 Hz to 1 Hz and stimulation adaptive to beta oscillations. Significance. The proposed method provides an approach for real-time removal in closed-loop DBS applications, which is effective in stimulation with low frequency, high frequency, and variable frequency. This method can facilitate the development of more advanced closed-loop DBS strategies.

Understanding the functional dynamics of neural oscillations in the sensory thalamus is essential for elucidating the perception and modulation of neuropathic pain. Local field potentials were recorded from the sensory thalamus of twelve neuropathic pain patients. Single and combinational neural states were defined by the activity state of a single or paired oscillations. Relationships between the duration or occurrence rate of neural state and pre-operative pain level or pain relief induced by deep brain stimulation were evaluated. Results showed that the occurrence rate of the single neural state of low-beta oscillation was significantly correlated with pain relief. The duration and occurrence rate of combinational neural states of the paired low-beta with delta, theta, alpha, high-beta or low-gamma oscillations were more significantly correlated with pain relief than the single neural states. Moreover, these significant combinational neural states formed a local oscillatory network with low-beta oscillation as a key node. The results also showed correlations between measures of combinational neural states and subjective pain level as well. The duration of combinational neural states of paired alpha with delta or theta oscillations and the occurrence rate of neural states of the paired delta with low-beta or low-gamma oscillations were significantly correlated with pre-operative pain level. In conclusion, this study revealed that the integration of oscillations and the functional dynamics of neural states were differentially involved in modulation and perception of neuropathic pain. The functional dynamics could be biomarkers for developing neural state-dependent deep brain stimulation for neuropathic pain.

Objective This study aims to discriminate the dynamic synchronization states from the subthalamic local field potentials and investigate their correlations with the motor symptoms in Parkinson’s Disease (PD). Methods The resting-state local field potentials of 10 patients with PD were recorded from the subthalamic nucleus. The dynamic neural states of multiple oscillations were discriminated and analyzed. The Spearman correlation was used to investigate the correlations between occurrence rate or duration of dynamic neural states and the severity of motor symptoms. Results The proportion of long low-beta and theta synchronized state was significantly correlated with the general motor symptom and tremor, respectively. The duration of combined low/high-beta state was significantly correlated with rigidity, and the duration of combined alpha/high-beta state was significantly correlated with bradykinesia. Conclusions This study provides evidence that motor symptoms are associated with the neural states coded with multiple oscillations in PD. Significance This study may advance the understanding of the neurophysiological mechanisms of the motor symptoms and provide potential biomarkers for closed-loop deep brain stimulation in PD.

Deep brain stimulation (DBS) in the basal ganglia has been introduced to treat movement disorders. The effects of pallidal DBS on the neural oscillations in the globus pallidus interna (GPi) and the subthalamic nucleus (STN) of the same subject remains unclear. In this study, the DBS electrodes were bilaterally implanted in the GPi and STN in patients with Tourette's syndrome (TS). The local field potentials were simultaneously recorded from the GPi and STN during pallidal DBS with 130 Hz, 60 microseconds, and 1V/2V/2.5V voltages. The time-frequency characteristics were analyzed across the conditions of resting, stimulation and post-stimulation. The results showed that alpha and beta oscillation existed in the basal ganglia and the beta oscillation was attenuated by pallidal stimulation. The attenuations are significantly different among 1V/2V/2.5V voltages. The results suggest that beta oscillations may have physiological function in resisting tics in TS. Thus, the oscillation- and symptom-guided intelligent DBS needs to be investigated.

Objective This study aims to use the activities recorded directly from the deep brain stimulation (DBS) electrode to address the focality and distinct nature of the local field potential (LFP) activities of different frequency. Methods Pre-operative and intra-operative magnetic resonance imaging (MRI) were acquired from patients with Parkinson’s disease (PD) who underwent DBS in the subthalamic nucleus and intra-operative LFP recording at rest and during cued movements. Images were reconstructed and 3-D visualized using Lead-DBS® toolbox to determine the coordinates of contact. The resting spectral power and movement-related power modulation of LFP oscillations were estimated. Results Both subthalamic LFP activity recorded at rest and its modulation by movement had focal maxima in the alpha, beta and gamma bands. The spatial distribution of alpha band activity and its modulation was significantly different to that in the beta band. Moreover, there were significant differences in the scale and timing of movement related modulation across the frequency bands. Conclusion Subthalamic LFP activities within specific frequency bands can be distinguished by spatial topography and pattern of movement related modulation. Significance Assessment of the frequency, focality and pattern of movement related modulation of subthalamic LFPs reveals a heterogeneity of neural population activity in this region. This could potentially be leveraged to finesse intra-operative targeting and post-operative contact selection.

The rapid economic development in emerging economies is deeply coupled with massive material use, which poses serious challenges to the environment. Thus, the desired transition towards sustainable society requires a more complete understanding of the interplay of material stock and economic development. To investigate how the productivity of materials evolves as the economy grows, we develop a modified Cobb-Douglas production function model by incorporating steel stock as one input factor and conduct a panel regression analysis based on China's provincial-level data from 1990 to 2016. Our empirical results indicate that steel stock plays a vital role, almost equivalent to labor and non-steel capital stock, in economic growth in China, and output elasticity of steel stock, which reflects its productivity, increases with economic development but might decline at a very developed stage. Potential factors leading to such variations in steel stock productivity are further explored by an extended model. It is found that industrialization and urbanization levels contribute positively to the output elasticity of steel stock while the existing stock level plays an opposite role. As industrialization and urbanization levels hit the upper limit when the economy matures, we predict that China's steel stock productivity will reach a plateau or start decreasing, depending on the future path of investment in materials.

Objectives Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been successfully used to treat both Parkinson’s disease (PD) and dystonia. Local field potentials (LFPs) recorded from the STN of PD patients demonstrate prominent beta frequency band activity. It is unclear whether such activity occurs in the STN in dystonia, and, if not, whether dystonia has another distinctive neural population activity in the STN. Methods Twelve patients with PD, and eight patients with dystonia underwent DBS electrode implantation targeting the STN. Seven dystonia patients were off medication and one was on aripiprazole and clonazepam. LFPs were recorded from the DBS electrodes in PD in the on/off medication states and in dystonia. Power spectra and temporal dynamics measured by the with Lempel-Ziv complexity of the LFPs were compared among these states. Results Normalised power spectra and Lempel-Ziv complexity of subthalamic LFPs differed between dystonia off and PD on/off, and between PD off and on over the low frequency, beta and high gamma bands. Patients with dystonia and off medication had lower beta power but higher low frequency and high gamma power than PD. Spectral power in the low beta frequency (11-20 Hz) range was attenuated in medicated PD. Conclusion The results suggest that dystonia and PD are characterized by different patterns of oscillatory activities even within the same nucleus, and exaggerated beta activity may relate to hypo-dopaminergic status.

Introduction Previous studies found subthalamic nucleus deep brain stimulation (STN‐DBS) has clinical effect on Parkinson's disease, dystonia, and obsessive compulsive disorder. It is noteworthy that only a few studies report the STN‐DBS for Tourette's syndrome (TS). Globus pallidus interna (GPi)‐DBS is the one of the most common targets for TS. So, this paper aims to investigate the neural oscillations in STN and GPi as well as the DBS effect between these two targets in same patients. Methods The local field potentials (LFPs) were simultaneously recorded from the bilateral GPi and STN in four patients with TS. The LFPs were decomposed into neural oscillations, and the frequency and time–frequency characteristics of the neural oscillations were analyzed across the conditions of resting, poststimulation, and movement. Results No difference of resting LFP was found between the two targets. The poststimulation period spectral power revealed the high beta and gamma oscillations were recovered after GPi‐DBS but remained attenuated after STN‐DBS. The STN beta oscillation has fewer changes during tics than voluntary movement, and the gamma oscillation was elevated when the tics appeared. Conclusion The high beta and gamma oscillations in GPi restored after GPi‐DBS, but not STN‐DBS. High beta and gamma oscillations may have physiological function in resisting tics in TS. The cortex compensation effect might be interfered by the STN‐DBS due to the influence on the hyper‐direct pathway but not GPi‐DBS., Distinct low‐frequency and high beta oscillations exist in the globus pallidus interna and subthalamic nucleus (STN). High beta and gamma oscillations might reflect potential physiological compensation effect in Tourette's syndrome (TS). The STN‐deep brain stimulation might interfere with the physiological compensation effect in TS.

Automatic recognition of electroencephalogram (EEG) signals plays a major role in epilepsy diagnosis and assessment. However, the recognition accuracy of conventional methods is usually not satisfactory because of the inconsistent distribution of training and testing data in practical applications. To overcome this problem, we used cross-domain mean joint approximation embedding (CMJAE) transductive transfer learning method to realize the knowledge transfer from the training data to the testing data by measuring the distribution difference between them. We combined the subspace learning and joint distribution to adapt the marginal and conditional distribution discrepancy. Our method was able to effectively learn a model for the testing data from training data with different distribution at a low computational complexity cost. On a public dataset, an ad-hoc cross-validation scheme of the proposed method exhibited that the average recognition accuracy, sensitivity, specificity of different states was 97.5%, 94.3%, 92.7% respectively, much better than conventional machine learning or deep learning methods, which may serve as a promising strategy for epileptic states recognition algorithms.

The ability to further stratify patients with esophageal carcinoma (EC) in the same stage into high-risk patients by the presence of lymphovascular invasion (LVI) may permit refinement of multi-modality therapy. However, the role of LVI in the prognosis of EC is not definite. A meta-analysis was conducted to investigate the relationship between LVI and EC prognosis. We searched PubMed, Embase, Web of Science, and Cochrane Library databases for studies on the association between LVI and prognosis of EC. Only studies with patient survival data related to LVI were included. The effect size for this analysis was the hazard ratio (HR) with 95% confidence intervals (CI) for overall survival (OS) and recurrence-free survival (RFS). Thirty-five studies with 9876 patients were included according to the defined inclusion and exclusion criteria. LVI was a poor indicator for the OS (HR = 1.64, 95% CI: 1.44-1.87, P < 0.001) and RFS (HR = 1.79, 95% CI: 1.38-2.34, P < 0.001). However, the heterogeneity was medium in OS (I2 = 61.2%, P < 0.001) and extreme in RFS (I2 = 77.5%, P < 0.001). In subgroup analysis, heterogeneity was originated from the staining method and proportion of early disease (stage (I + II)). We concluded that LVI was a poor prognostic indicator in patients with EC, especially in those studies with the IHC staining method and a high proportion of early disease (stage (I + II)).

The effect of deep brain stimulation(DBS)surgery treatment for Parkinson’s disease is determined by the accuracy of the electrodes placement and localization.The subthalamic nuclei(STN)as the implant target is small and has no clear boundary on the images.In addition,the intra-operative magnetic resonance images(MRI)have such a low resolution that the artifacts of the electrodes impact the observation.The three-dimensional(3D)visualization of STN and other nuclei nearby is able to provide the surgeons with direct and accurate localizing information.In this study,pre-and intra-operative MRIs of the Parkinson’s disease patients were used to realize the 3Dvisualization.After making a co-registration between the high-resolution pre-operative MRIs and the low-resolution intraoperative MRIs,we normalized the MRIs into a standard atlas space.We used a special threshold mask to search the lead trajectories in each axial slice.After checking the location of the electrode contacts with the coronal MRIs of the patients,we reconstructed the whole lead trajectories.Then the STN and other nuclei nearby in the standard atlas space were visualized with the grey images of the standard atlas,accomplishing the lead reconstruction and nerve nuclei visualization near STN of all patients.This study provides intuitive and quantitative information to identify the accuracy of the DBS electrode implantation,which could help decide the post-operative programming setting.

Objectives The nucleus accumbens (NAc) is known to regulate the motivation and underlie addictive behaviors, and the anterior limb of the internal capsule (ALIC) is involved in several psychiatric disorders. Our study aimed to explore the functions of NAc and ALIC electrophysiologically. Methods The local field potentials (LFPs) of the NAc and ALIC were recorded from 7 heroin addicts treated with deep brain stimulation. Correlation analysis was made between LFP powers in various frequency bands and the subjects’ neuropsychological test scores; coherence was calculated for the LFPs in NAc and ALIC. Results Both the NAc and ALIC exhibited prominent theta and alpha frequency band activity in the LFP power spectra. Additionally, a distinct beta band peak was detected in the power spectra of ALIC LFPs, which may represent the activity of striatal bridge cells. There was a significant negative correlation between the power of the theta frequency band of ALIC LFPs and visual analogue scale (VAS) scores indicative of cravings (Spearman’s ρ = −0.758, P = 0.002), and a significant positive correlation was found between the power of the alpha frequency band of NAc LFPs and subjects’ scores on the Hamilton depression inventory (ρ = 0.727, P = 0.005). LFPs of the NAc and ALIC exhibited higher coherence values in the theta and alpha frequency bands. Conclusions The results suggest that theta power in the ALIC/dorsal striatum and alpha power in the NAc may be associated with drug cravings and depressive symptoms, respectively, in heroin addicts. For these subjects, the neural activities in the dorsal and ventral striatum were mainly coordinated within the low-frequency band. Significance The study illustrates the neurophysiologic characteristics of heroin addiction and its comorbidities, providing a potential theoretical basis for optimizing deep brain stimulation (DBS) therapy.

China is the largest steel producer and consumer around the world. Quantifying the Chinese steel flow from cradle to grave can assist this industry to fully understand its historical status and future options on production route transformation, capacity planning, scrap availability, resource and energy consumption. With the help of the systematic methods combined dynamic MFA (material flow analysis) with scenario analysis, the Chinese steel cycle during the first half of the 21st century was quantified and several thought-provoking conclusions were draw. In the past decade, lots of pig iron or molten iron was fed into EAF (electric arc furnace) and the scrap usage of EAF fluctuated slightly. Thus, the real scrap-EAF route share is much lower than the EAF production share. On the other hand, we reconfirmed that the scrap supply in China will rise significantly in the future. Meanwhile, the secondary production route share will grow sharply and exceed primary production share before or after 2050 depending on our options. The scrap recycling rate and construction's lifetime play a vital role in this trend. In the end, an intensive discussion on production capacities’ adjustment and energy and resource consumption was conducted and relative policy suggestions were given. It is worth noting that scrap usage is crucial to future energy saving and emissions reduction of Chinese steel sector and its energy consumption might peak as early as 2015.

The dysfunction of subthalamic nucleus is the main cause of Parkinson's disease. Local field potentials in human subthalamic nucleus contain rich physiological information. The present study aimed to quantify the oscillatory and dynamic characteristics of local field potentials of subthalamic nucleus, and their modulation by the medication therapy for Parkinson's disease. The subthalamic nucleus local field potentials were recorded from patients with Parkinson's disease at the states of on and off medication. The oscillatory features were characterised with the power spectral analysis. Furthermore, the dynamic features were characterised with time-frequency analysis and the coefficient of variation measure of the time-variant power at each frequency. There was a dominant peak at low beta-band with medication off. The medication significantly suppressed the low beta component and increased the theta component. The amplitude fluctuation of neural oscillations was measured by the coefficient of variation. The coefficient of variation in 4-7 Hz and 60-66 Hz was increased by medication. These effects proved that medication had significant modulation to subthalamic nucleus neural oscillatory synchronization and dynamic features. The subthalamic nucleus neural activities tend towards stable state under medication. The findings would provide quantitative biomarkers for studying the mechanisms of Parkinson's disease and clinical treatments of medication or deep brain stimulation.

Pathological neural activity in subthalamic nucleus (STN) is closely related to the symptoms of Parkinson' s disease. Local field potentials (LFPs) recordings from subthalamic nucleus show that power spectral peaks exist at tremor, double tremor and tripble tremor frequencies, respectively. The interaction between these components in the multi-frequency tremor may be related to the generation of tremor. To study the linear and nonlinear relationship between those components, we analyzed STN LFPs from 9 Parkinson's disease patients using time frequency, cross correlation, Granger casuality and bi-spectral analysis. Results of the time-frequency analysis and cross-frequency correlation analysis demonstrated that the power density of those components significantly decreased as the alleviation of tremor and cross-correlation (0.18-0.50) exists during tremor period. Granger causality of the time-variant amplitude showed stronger contribution from tremor to double tremor components, and contributions from both tremor and double tremor components to triple tremor component. Quadratic phase couplings among these three components were detected by the bispectral approaches. The linear and nonlinear relationships existed among the multi-components and certainly confirmed that the dependence cross those frequencies and neurological mechanism of tremor involved complicate neural processes.

Background Multiple oscillations emerging from the same neuronal substrate serve to construct a local oscillatory network. The network usually exhibits complex behaviors of rhythmic, balancing and coupling between the oscillations, and the quantification of these behaviors would provide valuable insight into organization of the local network related to brain states. New method An integrated approach to quantify rhythmic, balancing and coupling neural behaviors based upon power spectral analysis, power ratio analysis and cross-frequency power coupling analysis was presented. Deep brain local field potentials (LFPs) were recorded from the thalamus of patients with neuropathic pain and dystonic tremor. t-Test was applied to assess the difference between the two patient groups. Results The rhythmic behavior measured by power spectral analysis showed significant power spectrum difference in the high beta band between the two patient groups. The balancing behavior measured by power ratio analysis showed significant power ratio differences at high beta band to 8–20 Hz, and 30–40 Hz to high beta band between the patient groups. The coupling behavior measured by cross-frequency power coupling analysis showed power coupling differences at (theta band, high beta band) and (45–55 Hz, 70–80 Hz) between the patient groups. Comparison with existing method The study provides a strategy for studying the brain states in a multi-dimensional behavior space and a framework to screen quantitative characteristics for biomarkers related to diseases or nuclei. Conclusions The work provides a comprehensive approach for understanding the complex behaviors of deep brain LFPs and identifying quantitative biomarkers for brain states related to diseases or nuclei.

Low-carbon power transition, key to combatting climate change, brings far-reaching effects on achieving Sustainable Development Goals (SDGs), in terms of resources use, environmental emissions, employment, and many more. Here we assess the potential impacts of power transition on multiple SDGs progress across 49 economies under six socio-economic-climate scenarios. We find that the low carbon power transition under Representative Concentration Pathway (RCP) 2.6 scenarios could lead to approximately 10% improvement in global SDG index score from 65.30 in 2015 to 71.62–71.64 in 2050. However, the improvement would be significantly decreased to 1.91%-4.98% and 3.42%-5.24% under RCP6.0 and RCP4.5 scenarios, respectively. Power transition could improve the overall SDG index in most developed economies under all scenarios while undermine their resources-related SDG scores. The power transition induced changes in international trade would improve developed economies’ SDG progress, but jeopardize that of developing economies which usually serve as resource hubs to meet the demand for low carbon power transition in developed economies.

Objectives: The inaccurate implantation of deep brain stimulation electrode could cause in-effective therapy and varied side-effects. This study aims to intra-operatively localise the subthalamic nucleus (STN) using voluntary movement related local field potentials (LFPs) to improve the electrode implantation accuracy. Methods: STN LFPs were recorded during auditory cued clicking motor task in twelve patients with Parkinson's disease. The neural oscillations were analysed using time-frequency analysis. The location of electrode contacts were verified with 3-D visualised MRI. Result: The beta oscillations (10-30Hz) attenuated during the movement and rebounded after the movement with excessive increase. The beta oscillations modulated over time period about 1 seconds. Beta oscillations including Parkinsonian excessive synchronisation and movement related responses were lacked outside the STN and were able to localise STN by recording LFPs around the nucleus. Conclusion: STN oscillations are alterable by the task of auditory cued movement. The movement varied beta oscillations are more robust for STN intraoperative localisation while low beta oscillation were attenuated by medication or high beta oscillation were not obviously synchronised in some patients.