Coprococcus eutactus screened from healthy adolescent attenuates chronic restraint stress-induced depression-like changes in adolescent mice: Potential roles in the microbiome and neurotransmitter modulation.

The onset of depression commonly occurs in adolescence; therefore, depressive prevention and intervention are pivotal during this period. It is becoming evident that neurotransmitter imbalance and gut microbiota dysbiosis are prominent causes of depression. However, the underlying links and mechanisms remain poorly understood. In this study, with 16S ribosomal RNA gene sequencing, genus Coprococcus markedly differentiated between the healthy and unmedicated depressive adolescents. Based on this, transplantation of Coprococcus eutactus (C.e.) was found to dramatically ameliorate the chronic restraint stress (CRS) induced depression-like changes and prevent synaptic loss and glial-stimulated neuroinflammation in mice. The Ultra-high performance liquid chromatography tandem mass spectrometry analysis (UHPLC-MS/MS) further showed that neurotoxic neurotransmitters in kynurenine pathway (KP) such as 3-hydroxykynurenine (3-HK) and 3-hydroxyanthranilic acid (3-HAA) decreased in mouse brains, mechanistically deciphering the transfer of the tryptophan metabolic pathway to serotonin metabolic signaling in the brain after C.e. treatment, which was also verified in the colon. Molecularly, blockage of KP activities mediated by C.e. was ascribed to the restraint of the limit-step enzymes responsible for kynurenine, 3-HK, and quinolinic acid generation. In the colon, C.e. treatment significantly recovered goblet cells and mucus secretion in CRS mice which may ascribe to the rebalance of the disordered gut microbiota, especially Akkermansia, Roseburia, Rikenella, Blautia, and Alloprevotella. Taken together, the current study reveals for the first time the beneficial effects and potential mechanisms of C.e. in ameliorating CRS-induced depression, unraveling the direct links between C.e. treatment and neurotransmitter rebalance, which may provide efficacious therapeutic avenues for adolescent depressive intervention.

High-precision time measurement electronics using the bandpass sampling method.

Waveform digitization at sampling rates up to several giga-samples per second is one of the approaches to achieve high-precision time measurements. In recent years, achieving high precision at lower sampling rates has emerged as a significant research topic. In this article, we focus on time measurement electronics, in which the bandpass sampling method is applied to obtain high precision at a sampling rate of roughly 100 MSps. An analog front-end circuit is designed, in which the input pulse signal is bandpass-filtered and amplified before sampling. A pipelined real-time time extraction algorithm is designed using the techniques of interpolation and cross correlation. A 1024-point fast Fourier transform algorithm is adopted to implement the cross correlation operation. Four time measurement channels are implemented in a mid-range field-programmable gate array, and the measurement rate of 116 kHz is achieved. Tests are conducted to evaluate the performance of the timing system. The typical RMS precision is better than 0.4 ps.

Bisphenol F exposure induces depression-like changes: Roles of the kynurenine metabolic pathway along the "liver-brain" axis.

Bisphenol F (BPF), one of the major alternatives of Bisphenol A (BPA), is becoming extensively used in industrial production with great harm to human beings and environment. Recent studies have revealed that environmental exposure is crucial to the initiation and development of depression. Thereby, the aim the present study is to ascertain the correlationship between the BPF exposure and depression occurrence. In the current study, BPF strikingly triggered depression-like changes in mice through the sucrose preference test (SPT), tail suspension test (TST) and forced swim test (FST), accompanied by the perturbation of the kynurenine (KYN) metabolic pathway along the "liver-brain" axis. Mechanistically, the neurotransmitters from the tryptophan metabolic pathway were converted to the toxic KYN pathway after BPF treatment. With the ELISA assay, it revealed that the toxic KYN metabolites, including KYN and 3-hydroxykynurenine (3-HK), were strikingly increased in the mouse brains which was ascribed to the enhanced expression of the rate-limiting enzymes Indoleamine 2,3-dioxygenase (IDO1) and Kynurenine 3-monooxygenase (KMO) respectively. Interestingly, the increased brain KYN induced by BPF was also validated partially from the periphery, since the ELISA and western blotting results indicated the significantly increased KYN in the serum and L-type amino acid transporter 1 (LAT1) in the brain, the key transporter responsible for KYN and 3-HK crossing the blood-brain barrier. Intriguingly, the liver-derived KYN metabolic pathway was the important source of the peripheral KYN and 3-HK, as BPF substantially enhanced hepatic IDO1, Tryptophan, 2, 3-dioxygenase (TDO2), and KMO levels indicated by western blotting. This study is the first to delineate previously unrecognized BPF-induced depression by regulating the KYN metabolic pathway along the "liver-brain" axis; therefore, targeting LAT1 or hepatic KYN signaling may provide a potentially unique therapeutic intervention in BPF-induced depression.

Solvent-Tailored Reversible Self-Assembly: Unveiling Ionic Transport Nanochannels in Block Copolymer Composite Electrolytes.

Block copolymer composite electrolytes have gained extensive attention for their promising performance in ionic conductivity and mechanical properties, making them valuable for future technologies. The control of the ionic conductivity through the self-assembly of block copolymers, however, remains a great challenge, especially in confined environments. In this study, we prepare block copolymer composite electrolytes using polystyrene-block-poly(ethylene oxide) (PS-b-PEO, SEO) as the polymer matrix and anodic aluminum oxide (AAO) templates as the ceramic skeleton. The self-assembly of SEO creates nanoscale ion transport pathways in the PEO regions through ionic interactions with lithium salts. The nanopores of the AAO templates provide a confined environment for complex phase separation of SEO controlled by selective solvent vapor annealing. Our findings demonstrate that transforming self-assembled SEO structures allows for precise control of ion transport pathways with cylindrical structures exhibiting 20 times higher ionic conductivities than those of helical structures. For AAO templates with pore diameters of 20 nm (SEO-LiTFSI@AAO-20), the ionic conductivities are approximately 410 times higher than those with pore diameters of 200 nm (SEO-LiTFSI@AAO-200), owing to the larger specific surface areas within the smaller nanopores. Utilizing the self-assembly of SEO not only enables the construction of vertically aligned ion transport channels on various scales but also offers a fascinating approach to tailor the conductive capabilities of composite electrolytes, enhancing the ion transport efficiency and allowing for the flexible design of block copolymer composite electrolytes.

Microbiome and tryptophan metabolomics analysis in adolescent depression: roles of the gut microbiota in the regulation of tryptophan-derived neurotransmitters and behaviors in human and mice.

BACKGROUND: Adolescent depression is becoming one of the major public health concerns, because of its increased prevalence and risk of significant functional impairment and suicidality. Clinical depression commonly emerges in adolescence; therefore, the prevention and intervention of depression at this stage is crucial. Recent evidence supports the importance of the gut microbiota (GM) in the modulation of multiple functions associated with depression through the gut-brain axis (GBA). However, the underlying mechanisms remain poorly understood. Therefore, in the current study, we aimed to screen the microbiota out from healthy and depressive adolescents, delineate the association of the targeted microbiota and the adolescent depression, address the salutary effects of the targeted microbiota on anti-depressive behaviors in mice involving the metabolism of the tryptophan (Trp)-derived neurotransmitters along the GBA. RESULTS: Here, we found the gut microbiota from healthy adolescent volunteers, first diagnosis patients of adolescent depression, and sertraline interveners after first diagnosis displayed significant difference, the relative abundance of Faecalibacterium, Roseburia, Collinsella, Blautia, Phascolarctobacterium, Lachnospiraceae-unclassified decreased in adolescent depressive patients, while restored after sertraline treatment. Of note, the Roseburia abundance exhibited a high efficiency in predicting adolescent depression. Intriguingly, transplantation of the fecal microbiota from healthy adolescent volunteers to the chronic restraint stress (CRS)-induced adolescent depressed mice significantly ameliorated mouse depressive behaviors, in which the Roseburia exerted critical roles, since its effective colonization in the mouse colon resulted in remarkably increased 5-HT level and reciprocally decreased kynurenine (Kyn) toxic metabolites quinolinic acid (Quin) and 3-hydroxykynurenine (3-HK) levels in both the mouse brain and colon. The specific roles of the Roseburia were further validated by the target bacteria transplantation mouse model, Roseburia intestinalis (Ri.) was gavaged to mice and importantly, it dramatically ameliorated CRS-induced mouse depressive behaviors, increased 5-HT levels in the brain and colon via promoting tryptophan hydroxylase-2 (TPH2) or -1 (TPH1) expression. Reciprocally, Ri. markedly restrained the limit-step enzyme responsible for kynurenine (indoleamine2,3-dioxygenase 1, IDO1) and quinolinic acid (3-hydroxyanthranilic acid 3,4-dioxygenase, 3HAO) generation, thereby decreased Kyn and Quin levels. Additionally, Ri. administration exerted a pivotal role in the protection of CRS-induced synaptic loss, microglial activation, and astrocyte maintenance. CONCLUSIONS: This study is the first to delineate the beneficial effects of Ri. on adolescent depression by balancing Trp-derived neurotransmitter metabolism and improving synaptogenesis and glial maintenance, which may yield novel insights into the microbial markers and therapeutic strategies of GBA in adolescent depression. Video Abstract.

Intraday adaptation to extreme temperatures in outdoor activity.

Linkages between climate and human activity are often calibrated at daily or monthly resolutions, which lacks the granularity to observe intraday adaptation behaviors. Ignoring this adaptation margin could mischaracterize the health consequences of future climate change. Here, we construct an hourly outdoor leisure activity database using billions of cell phone location requests in 10,499 parks in 2017 all over China to investigate the within-day outdoor activity rhythm. We find that hourly temperatures above 30 °C and 35 °C depress outdoor leisure activities by 5% (95% confidence interval, CI 3-7%) and by 13% (95% CI 10-16%) respectively. This activity-depressing effect is larger than previous daily or monthly studies due to intraday activity substitution from noon and afternoon to morning and evening. Intraday adaptation is larger for locations and dates with time flexibility, for individuals more frequently exposed to heat, and for parks situated in urban areas. Such within-day adaptation substantially reduces heat exposure, yet it also delays the active time at night by about half an hour, with potential side effect on sleep quality. Combining empirical estimates with outputs from downscaled climate models, we show that unmitigated climate change will generate sizable activity-depressing and activity-delaying effects in summer when projected on an hourly resolution. Our findings call for more attention in leveraging real-time activity data to understand intraday adaptation behaviors and their associated health consequences in climate change research.

Measuring daily-life fear perception change: A computational study in the context of COVID-19.

COVID-19, as a global health crisis, has triggered the fear emotion with unprecedented intensity. Besides the fear of getting infected, the outbreak of COVID-19 also created significant disruptions in people's daily life and thus evoked intensive psychological responses indirect to COVID-19 infections. In this study, we construct a panel expressed fear database tracking the universe of social media posts (16 million) generated by 536 thousand individuals between January 1st, 2019 and August 31st, 2020 in China. We employ deep learning techniques to detect expressions of fear emotion within each post, and then apply topic model to extract the major topics of fear expressions in our sample during the COVID-19 pandemic. Our unique database includes a comprehensive list of topics, not being limited to post centering around COVID-19. Based on this database, we find that sleep disorders ("nightmare" and "insomnia") take up the largest share of fear-labeled posts in the pre-pandemic period (January 2019-December 2019), and significantly increase during the COVID-19. We identify health and work-related concerns are the two major sources of non-COVID fear during the pandemic period. We also detect gender differences, with females having higher fear towards health topics and males towards monetary concerns. Our research shows how applying fear detection and topic modeling techniques on posts unrelated to COVID-19 can provide additional policy value in discerning broader societal concerns during this COVID-19 crisis.

Global evidence of expressed sentiment alterations during the COVID-19 pandemic.

The COVID-19 pandemic has created unprecedented burdens on people's physical health and subjective well-being. While countries worldwide have developed platforms to track the evolution of COVID-19 infections and deaths, frequent global measurements of affective states to gauge the emotional impacts of pandemic and related policy interventions remain scarce. Using 654 million geotagged social media posts in over 100 countries, covering 74% of world population, coupled with state-of-the-art natural language processing techniques, we develop a global dataset of expressed sentiment indices to track national- and subnational-level affective states on a daily basis. We present two motivating applications using data from the first wave of COVID-19 (from 1 January to 31 May 2020). First, using regression discontinuity design, we provide consistent evidence that COVID-19 outbreaks caused steep declines in expressed sentiment globally, followed by asymmetric, slower recoveries. Second, applying synthetic control methods, we find moderate to no effects of lockdown policies on expressed sentiment, with large heterogeneity across countries. This study shows how social media data, when coupled with machine learning techniques, can provide real-time measurements of affective states.

Encouraging the resumption of economic activity after COVID-19: Evidence from a large scale-field experiment in China.

As the COVID-19 pandemic comes to an end, governments find themselves facing a new challenge: motivating citizens to resume economic activity. What is an effective way to do so? We investigate this question using a field experiment in the city of Zhengzhou, China, immediately following the end of the city's COVID-19 lockdown. We assessed the effect of a descriptive norms intervention providing information about the proportion of participants' neighbors who have resumed economic activity. We find that informing individuals about their neighbors' plans to visit restaurants increases the fraction of participants visiting restaurants by 12 percentage points (37%), among those participants who underestimated the proportion of neighbors who resumed economic activity. Those who overestimated did not respond by reducing restaurant attendance (the intervention yielded no "boomerang" effect); thus, our descriptive norms intervention yielded a net positive effect. We explore the moderating role of risk preferences and the effect of the intervention on subjects' perceived risk of going to restaurants, as well as the contrast with an intervention for parks, which were already perceived as safe. All of these analyses suggest our intervention worked by reducing the perceived risk of going to restaurants.

Low-carbon innovation induced by emissions trading in China.

Emissions trading scheme (ETS) has been adopted by an increasing number of countries and regions for carbon mitigation, but its actual effect depends on specific program design and institutional context. Before launching the world largest ETS, China experimented with seven independent regional pilots, whose effects are only indirectly explored. Here we provide firm-level evidence of the innovation effect directly from China's pilot emissions trading, based on latest patenting information and a quasi-experimental design. China's pilots increase low-carbon innovation of ETS firms by 5-10% without crowding out their other technology innovation. The increase from ETS firms accounts for about 1% increase of the regional low-carbon patents, while a similar increase from large non-ETS firms is also induced by the ETS. Most importantly, the effect is not associated with permit price, auction, or firm characteristics, but is driven by mass-based allowance allocation. A rate-based approach, however, is adopted by China's national market.