The growing impact of climate change and the global shift toward a carbon-neutral economy necessitate the development of sustainable technologies. Microbial electrochemical technologies (METs) innovatively utilize microorganisms to generate electricity and produce valuable chemicals from organic and inorganic materials. While METs have demonstrated significant potential in wastewater treatment and carbon recycling at the laboratory scale, the challenge remains in scaling the technologies for industrial applications. This transition could revolutionize clean energy production and environmental protection, laying the foundation for a sustainable future.

METs offer innovative solutions for pollution reduction and sustainable energy production. By integrating microbial metabolic processes with electrochemical systems, METs facilitate the conversion of organic and inorganic substrates into electricity, chemicals, or fuels. Research at the laboratory scale has demonstrated the substantial potential of METs in wastewater treatment, carbon resource utilization, and energy recovery. However, scaling METs from the lab to industrial applications involves challenges about system design, operational stability, economic feasibility, and technological integration. This review provides a comprehensive examination of the scaling up of METs, including microbial fuel cells, microbial electrolysis cells, and microbial electrosynthesis systems. It highlights recent advancements in reactor and electrode design, and operational conditions, and offers insights for future research and development aimed at successful industrial implementation.

Breakthrough in METs is set to revolutionize how we treat wastewater and recycle carbon. As METs move from the lab to large-scale applications, they have the potential to reshape industries and drive us closer to a carbon-neutral economy.

Studies of Internet gaming disorder (IGD) suggest an imbalanced relationship between cognitive control and reward processing in people with IGD. However, it remains unclear how these two systems interact with each other, and whether they could serve as neurobiological markers for IGD.

Fifty IGD subjects and matched individuals with recreational game use (RGU) were selected and compared when they were performing a cue-craving task. Regions of interests [anterior cingulate cortex (ACC), lentiform nucleus] were selected based on the comparison between brain responses to gaming-related cues and neutral cues. Directional connectivities among these brain regions were determined using Bayesian estimation. We additionally examined the posterior cingulate cortex (PCC) in a separate analysis based on data implicating the PCC in craving in addiction.

During fixed-connectivity analyses, IGD subjects showed blunted ACC-to-lentiform and lentiform-to-ACC connectivity relative to RGU subjects, especially in the left hemisphere. When facing gaming cues, IGD subjects trended toward lower left-hemispheric modulatory effects in ACC-to-lentiform connectivity than RGU subjects. Self-reported cue-related craving prior to scanning correlated inversely with left-hemispheric modulatory effects in ACC-to-lentiform connectivity.

The results suggesting that prefrontal-to-lentiform connectivity is impaired in IGD provides a possible neurobiological mechanism for difficulties in controlling gaming-cue-elicited cravings. Reduced connectivity ACC-lentiform connectivity may be a useful neurobiological marker for IGD.

Internet gaming disorder (IGD) is becoming a matter of concern around the world. However, the neural mechanism underlying IGD remains unclear. The purpose of this paper is to explore the differences between the neuronal network of IGD participants and that of recreational Internet game users (RGU).

Imaging and behavioral data were collected from 18 IGD participants and 20 RGU under a probability discounting task. The independent component analysis (ICA) and graph theoretical analysis (GTA) were used to analyze the data.

Behavioral results showed the IGD participants, compared to RGU, prefer risky options to the fixed ones and spent less time in making risky decisions. In imaging results, the ICA analysis revealed that the IGD participants showed stronger functional connectivity (FC) in reward circuits and executive control network, as well as lower FC in anterior salience network (ASN) than RGU; for the GTA results, the IGD participants showed impaired FC in reward circuits and ASN when compared with RGU.

These results suggest that IGD participants were more sensitive to rewards, and they were more impulsive in decision-making as they could not control their impulsivity effectively. This might explain why IGD participants cannot stop their gaming behaviors even when facing severe negative consequences.