No abstract

The perceived inability of climate change mitigation goals alone to mobilize sufficient climate change mitigation efforts has, among other factors, led to growing research on the co-benefits of reducing greenhouse gas (GHG) emissions. This study conducts a systematic review (SR) of the literature on the co-benefits of mitigating GHG emissions resulting in 1554 papers. We analyze these papers using bibliometric analysis, including a keyword co-occurrence analysis. We then iteratively develop and present a typology of co-benefits, mitigation sectors, geographic scope, and methods based on the manual double coding of the papers resulting from the SR. We find that the co-benefits from GHG mitigation that have received the largest attention of researchers are impacts on ecosystems, economic activity, health, air pollution, and resource efficiency. The co-benefits that have received the least attention include the impacts on conflict and disaster resilience, poverty alleviation (or exacerbation), energy security, technological spillovers and innovation, and food security. Most research has investigated co-benefits from GHG mitigation in the agriculture, forestry and other land use (AFOLU), electricity, transport, and residential sectors, with the industrial sector being the subject of significantly less research. The largest number of co-benefits publications provide analysis at a global level, with relatively few studies providing local (city) level analysis or studying co-benefits in Oceanian or African contexts. Finally, science and engineering methods, in contrast to economic or social science methods, are the methods most commonly employed in co-benefits papers. We conclude that given the potential mobilizing power of understudied co-benefits (e.g. poverty alleviation) and local impacts, the magnitude of GHG emissions from the industrial sector, and the fact that Africa and South America are likely to be severely affected by climate change, there is an opportunity for the research community to fill these gaps.

Previous studies have shown that clock genes are expressed in the suprachiasmatic nucleus (SCN) of the hypothalamus, other brain regions, and peripheral tissues. Various peripheral oscillators can run independently of the SCN. However, no published studies have reported changes in the expression of clock genes in the rat central nervous system and peripheral blood mononuclear cells (PBMCs) after withdrawal from chronic morphine treatment. Rats were administered with morphine twice daily at progressively increasing doses for 7 days; spontaneous withdrawal signs were recorded 14 h after the last morphine administration. Then, brain and blood samples were collected at each of eight time points (every 3 h: ZT 9; ZT 12; ZT 15; ZT 18; ZT 21; ZT 0; ZT 3; ZT 6) to examine expression of rPER1 and rPER2 and rCLOCK. Rats presented obvious morphine withdrawal signs, such as teeth chattering, shaking, exploring, ptosis, and weight loss. In morphine-treated rats, rPER1 and rPER2 expression in the SCN, basolateral amygdala, and nucleus accumbens shell showed robust circadian rhythms that were essentially identical to those in control rats. However, robust circadian rhythm in rPER1 expression in the ventral tegmental area was completely phase-reversed in morphine-treated rats. A blunting of circadian oscillations of rPER1 expression occurred in the central amygdala, hippocampus, nucleus accumbens core, and PBMCs and rPER2 expression occurred in the central amygdala, prefrontal cortex, nucleus accumbens core, and PBMCs in morphine-treated rats compared with controls. rCLOCK expression in morphine-treated rats showed no rhythmic change, identical to control rats. These findings indicate that withdrawal from chronic morphine treatment resulted in desynchronization from the SCN rhythm, with blunting of rPER1 and rPER2 expression in reward-related neurocircuits and PBMCs.

The original English Morningness-Eveningness Questionnaire (MEQ) was translated into Chinese, and the circadian rhythmicity of 188 healthy Chinese subjects was tested using this version of the MEQ. We assessed the reliability and validity of the Chinese version and determined the cut-off points. In the Chinese version, 19 items were divided into two dimensions (i.e., sleep phase and time of greatest efficiency), and the cut-off points were determined to be the following: definitely evening type (14-46), moderately evening type (47-52), neither type (53-64), moderately morning type (65-69), and definitely morning type (70-86). Additionally, the Cronbach a coefficient was determined to be 0.769, which is satisfactory. The Chinese version of the MEQ has good psychometric properties, and its cut-off points can effectively differentiate between morningness and eveningness.