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Based on the carbon emission database of the China Urban Greenhouse Gas Working Group, this paper analyzed the spatiotemporal evolution characteristics and main influencing factors of urban carbon dioxide emissions in China using ArcGIS spatial analysis and SPSS statistical analysis methods, in order to provide a reference for the formulation of the national "double-carbon" strategy and the construction of low-carbon urbanization. The results showed that (1) the urban carbon dioxide emissions in China exhibit a "point-line-area" spreading spatial grid. Carbon dioxide emissions form a planar emission pattern surrounded by the Beijing–Tianjin–Hebei urban agglomeration, Yangtze River Delta urban agglomeration, and Central Plains urban agglomeration. A high per capita and high-intensity emission belt from Xinjiang to Inner Mongolia has been formed. (2) The proportion of industrial emissions continues to decrease, and the range of high industrial emissions has gradually crossed the "Hu Huan-yong Line", spreading from eastern China to the whole country. The emissions from transportation, the service industry, and households have become new growth points, and high-value emissions from households have also shown a nationwide spreading trend. (3) The main factors influencing the spatial distribution of carbon dioxide emissions are urbanization, the economy, industry, investment, and household energy consumption. [ABSTRACT FROM AUTHOR]

Aim: Major depressive disorder (MDD) is associated with high suicidality, especially for those with suicide attempt (SA). Although impaired oscillatory activity has been previously reported in patients with SA, little is known about precise temporal–spatial variability of its neural dynamics. To solve this, the current study probed the spectral power and network interactions underlying SA in MDD. Methods: The present study recruited 104 subjects including 56 subjects with MDD (30 with SA and 26 without SA) and 48 healthy controls, who performed sad expressions recognition task during magnetoencephalography (MEG) recording. By investigating source‐reconstructed MEG‐data, brain states representing different task stages were estimated from a Hidden Markov model. Spectrum power and network connectivity were compared via Gaussian Mixture Models, and fractional occupancy (FO) of states were compared via an independent F‐test. Results: Brain states were corresponding to various frequencies (theta/beta/low gamma/ high gamma). In low gamma band (35–45 Hz), the early visual state exhibited increased activation and hyper inter‐network connectivity between visual regions and the limbic system, while the middle fronto‐parietal state exhibited attenuated activation and decreased intra‐network connectivity within fronto‐parietal regions in SA group. Crucially, FO values of these two states were significantly correlated with the suicide risks. Conclusions: Suicide behavior of patients with MDD was significantly associated with aberrant oscillations in low gamma band. Elevated oscillations in occipital cortices and attenuated oscillations in fronto‐parietal cortices were significantly associated with SA. Manifesting sadness indulging and reckless decision‐making, the hampered temporal characteristics could help explain the neural‐electric basis of SA. [ABSTRACT FROM AUTHOR]

Background: Combining genetic variants with neuroimaging phenotypes may facilitate understanding of the biological mechanisms for the etiology and pharmacology of antidepressant treatment of major depressive disorder (MDD).Purpose: To explore the latent pathway of dopamine gene-hierarchical brain network-antidepressant treatment.Study Type: Retrospective.Population: One hundred and sixty-eight MDD inpatients divided into responders (N = 98) or nonresponders (N = 70) based on the treatment outcome of antidepressant.Field Strength/sequence: Diffusion tensors imaging and resting-state functional magnetic resonance imaging at 3.0T using echo-planar sequence.Assessment: Four genetic variations of the dopamine receptor D1 (DRD1) were genotyped. Strengths of rich-club, feeder, and local connections were calculated based on the rich-club organizations of structural and functional brain networks at baseline and following 4 weeks of selective serotonin reuptake inhibitor (SSRI) therapy.Statistical Tests: Logistic and linear regressions were used to analyze the impact of DRD1 multilocus genetic profile score on the treatment response of SSRI, and their associations with strengths of rich-club, feeder, and local connections. Mediation models were developed to explore the mediation role of rich-club organizations on the relationship between DRD1 and SSRI therapy response. A P value <0.05 was considered to be statistically significant.Results: Multiple genetic variations of DRD1 were significantly related to the strengths of feeder connections both in structural and functional networks, and to the treatment response of SSRI. Furthermore, the strength of the structural feeder connection significantly modulated the effect of DRD1 variants on SSRI treatment outcome.Data Conclusion: DRD1 displayed close connections both with SSRI treatment outcome and rich-club organizations of structural and functional data. Moreover, structural feeder connection played a mediating role in the relationship between DRD1 and antidepressant therapy.Level Of Evidence: 3 TECHNICAL EFFICACY STAGE: 4. [ABSTRACT FROM AUTHOR]

Aims: The diversity of treatment outcomes for major depressive disorder (MDD) remains uncertain in neuropathology. The current study aimed at exploring electrophysiological biomarkers associated with treatment response. Methods: The present study recruited 130 subjects including 100 MDD patients and 30 healthy controls. All subjects participated in a sad expression recognition task while their magnetoencephalography data were recorded. Patients who had a reduction of at least 50% in disorder severity at endpoint (>2 weeks) were considered as responders. Within‐frequency power and phase‐amplitude coupling were measured for the brain regions involved in the emotional visual information processing pathways. Results: The significant alpha–gamma decoupling from the right thalamus to the right amygdala in unconscious processing and from right orbital frontal cortices to the right amygdala in conscious processing was found in non‐responders relative to responders and healthy controls. These kinds of dysregulation could also predict the potential treatment response. Conclusion: The attenuated alpha–gamma coupling in dual pathways indicated increased sensitivity to the negative emotional information and reduced moderated effect of the amygdala, which might cause insensitivity to antidepressant treatment and could be regarded as potential neural mechanisms for treatment response prediction. [ABSTRACT FROM AUTHOR]

This article, published in the British Journal of Haematology, discusses a case of a 43-year-old female patient who was diagnosed with classical Hodgkin lymphoma (cHL) of nodular sclerosis type. The patient underwent chemotherapy but developed a large pleural effusion. Analysis of the fluid showed a large number of Reed-Sternberg (R-S) cells, which are characteristic of Hodgkin lymphoma. The presence of such a large number of R-S cells in the pleural fluid is rare. The study was supported by the Scientific Research Project of Zhejiang Province and the 13th Five-year Plan of Haematology of Integrated Traditional Chinese and Western Medicine. The research was conducted with the approval of the Ethics Committees of the Tongde Hospital of Zhejiang Province, and informed consent was obtained from the patient for the publication of images. [Extracted from the article]