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Over the past few decades, China has undergone the largest and fastest urbanization process in world history. By 2023, Chengdu’s urbanization rate had reached 80.5%, significantly higher than the national average of 66.16%. Studying the urbanization experience of Chengdu is of great significance for optimizing urban planning policies in Chengdu and other cities in China. Although much literature has explored the urbanization process from macro and micro perspectives, studies using a top-down approach to examine urban fringe expansion are relatively scarce. This study first applies the entropy weight method to analyze the spatial-temporal evolution trends of urban development, identifying areas of imbalanced development and prominent issues. Secondly, the K-means machine learning algorithm and nightlight data are used to reconstruct and classify urban regions, and a comparative analysis is conducted with administrative divisions to further identify unreasonable areas in urban spatial distribution and structure. Finally, POI data and the geographical detector method are used to analyze the micro-driving forces in areas of imbalanced development, identifying major limiting factors and solutions. The study found that the gap between urban and rural development in Chengdu is narrowing during the urbanization process, but there is severe differentiation in the second circle of Chengdu, where economic development is accelerating but residents’ happiness is declining. Moreover, analysis based on urban nightlight data and land-use data reveals that the expansion areas on the urban-rural fringe are mainly concentrated in the second circle of Chengdu. Micro-level driving factor analysis found that the western region of the second circle has many but small urban settlements, with a dense road network but scattered functional areas. The eastern region has inefficient and extensive use of construction land. Additionally, the mismatch between student status and household registration has resulted in relatively lagging educational resource development, and high entry barriers have hindered the progress of urbanization, leading to low per capita welfare expenditure. These reasons are the main factors causing the decline in residents’ happiness, and this impact shows significant differences at different temporal and spatial scales. Encouraging innovation in research and development or education can serve as a long-term and effective driving force for promoting sustainable urbanization. This study provides valuable insights for scientifically planning sustainable urban development and promoting the urbanization process.

Seeking innovative development has become a necessity for global cities because of the accelerating consumption of natural resources and the increasing need for urgent control of environmental pollution. However, few studies have reported on the effect of innovative development on the green economic growth of resource-based cities. Therefore, this study aimed to construct the SBM model of unexpected output to measure the efficiency of green economic growth using data of 108 resource-based cities in China from 2004 to 2018, and to analyze the impact of innovative development and resource endowment on green economic growth using the systematic Generalized Method of Moments (GMM) model. The following results were obtained: first, the green economic growth efficiency of resource-based cities exhibited a general trend of fluctuation and rise, but the efficiency of different resource-based cities was different in time and space. Second, although innovative development promoted the green economic growth of resource-based cities, the impact of different resource-based cities was heterogeneous. Innovative development promoted the green economic growth of resource-based cities in eastern China, comprehensive cities, metal cities, growth cities, and renewable cities. However, it had an inhibitory effect on the green economic growth of northeast China, west China, and oil–gas and nonmetal resource–based cities, but no significant effect on the green economic growth of other resource-based cities. Third, the nonlinear effect of resource endowment on the green economic growth of resource-based cities was not significant, but resource endowment had a “curse” effect on green economic growth. Meanwhile, heterogeneity analysis showed two effects of resource endowment on the green economic growth in different resource-based cities: curse and blessing. Fourth, the impact of innovative development on the green economic growth of resource-based cities was moderated by resource endowment. The impact of innovative development on green economic growth decreased with the increase in resource endowment. Therefore, resource-based cities should not only constantly increase innovation and improve resource utilization efficiency but also actively promote coordination and cooperation of regional resource-based industries so as to achieve green and sustainable development.

Wiring a complex brain requires many neurons with intricate cell specificity, generated by a limited number of neural stem cells. Drosophila central brain lineages are a predetermined series of neurons, born in a specific order. To understand how lineage identity translates to neuron morphology, we mapped 18 Drosophila central brain lineages. While we found large aggregate differences between lineages, we also discovered shared patterns of morphological diversification. Lineage identity plus Notch-mediated sister fate govern primary neuron trajectories, whereas temporal fate diversifies terminal elaborations. Further, morphological neuron types may arise repeatedly, interspersed with other types. Despite the complexity, related lineages produce similar neuron types in comparable temporal patterns. Different stem cells even yield two identical series of dopaminergic neuron types, but with unrelated sister neurons. Together, these phenomena suggest that straightforward rules drive incredible neuronal complexity, and that large changes in morphology can result from relatively simple fating mechanisms.

Long-term tobacco use causes nicotine dependence via the regulation of a wide range of genes and is accompanied by various health problems. Studies in mammalian systems have revealed some key factors involved in the effects of nicotine, including nicotinic acetylcholine receptors (nAChRs), dopamine and other neurotransmitters. Nevertheless, the signaling pathways that link nicotine-induced molecular and behavioral modifications remain elusive. Utilizing a chronic nicotine administration paradigm, we found that adult male fruit flies exhibited locomotor hyperactivity after three consecutive days of nicotine exposure, while nicotine-naive flies did not. Strikingly, this chronic nicotine-induced locomotor hyperactivity (cNILH) was abolished in Decapping Protein 2 or 1 (Dcp2 or Dcp1) -deficient flies, while only Dcp2-deficient flies exhibited higher basal levels of locomotor activity than controls. These results indicate that Dcp2 plays a critical role in the response to chronic nicotine exposure. Moreover, the messenger RNA (mRNA) level of Dcp2 in the fly head was suppressed by chronic nicotine treatment, and up-regulation of Dcp2 expression in the nervous system blocked cNILH. These results indicate that down-regulation of Dcp2 mediates chronic nicotine-exposure-induced locomotor hyperactivity in Drosophila. The decapping proteins play a major role in mRNA degradation; however, their function in the nervous system has rarely been investigated. Our findings reveal a significant role for the mRNA decapping pathway in developing locomotor hyperactivity in response to chronic nicotine exposure and identify Dcp2 as a potential candidate for future research on nicotine dependence.

Gene targeting is an incredibly valuable technique. Sometimes, however, it can also be extremely challenging for various intrinsic reasons (e.g. low target accessibility or nature/extent of gene modification). To bypass these barriers, we designed a transgenebased system in Drosophila that increases the number of independent gene targeting events while at the same time enriching for correctly targeted progeny. Unfortunately, with particularly challenging gene targeting experiments, our original design yielded numerous false positives. Here, we deliver a muchimproved technique, named Enhanced Golic+ (E-Golic+). E-Golic+ incorporates genetic modifications to tighten lethality-based selection while simultaneously boosting efficiency. With E-Golic+, we easily achieve previously unattainable gene targeting. Additionally, we built an E-Golic+-based, high-efficiency genetic pipeline for transgene swapping. We demonstrate its utility by transforming GAL4 enhancertrap lines into tissue-specific Cas9-expressing lines. Given the superior efficiency, specificity and scalability, E-Golic+ promises to expedite development of additional sophisticated genetic/genomic tools in Drosophila. [ABSTRACT FROM AUTHOR]

Macroglial cells in the central nervous system exhibit regional specialization and carry out region-specific functions. Diverse glial cells arise from specific progenitors in specific spatiotemporal patterns. This raises an interesting possibility that there exist glial precursors with distinct developmental fates, which govern region-specific gliogenesis. Here we mapped the glial progeny produced by the Drosophila type II neuroblasts, which, like vertebrate radial glia cells, yield both neurons and glia via intermediate neural progenitors (INPs). Distinct type II neuroblasts produce different characteristic sets of glia. A single INP can make both astrocyte-like and ensheathing glia, which co-occupy a relatively restrictive subdomain. Blocking apoptosis uncovers further lineage distinctions in the specification, proliferation, and survival of glial precursors. Both the switch from neurogenesis to gliogenesis and the subsequent glial expansion depend on Notch signaling. Taken together, lineage origins preconfigure the development of individual glial precursors with involvement of serial Notch actions in promoting gliogenesis. [ABSTRACT FROM AUTHOR]

In their classic experiments, Olds and Milner showed that rats learn to lever press to receive an electric stimulus in specific brain regions. This led to the identification of mammalian reward centers. Our interest in defining the neuronal substrates of reward perception in the fruit fly Drosophila melanogaster prompted us to develop a simpler experimental approach wherein flies could implement behavior that induces self-stimulation of specific neurons in their brains. The high-throughput assay employs optogenetic activation of neurons when the fly occupies a specific area of a behavioral chamber, and the flies' preferential occupation of this area reflects their choosing to experience optogenetic stimulation. Flies in which neuropeptide F (NPF) neurons are activated display preference for the illuminated side of the chamber. We show that optogenetic activation of NPF neuron is rewarding in olfactory conditioning experiments and that the preference for NPF neuron activation is dependent on NPF signaling. Finally, we identify a small subset of NPF-expressing neurons located in the dorsomedial posterior brain that are sufficient to elicit preference in our assay. This assay provides the means for carrying out unbiased screens to map reward neurons in flies. [ABSTRACT FROM AUTHOR]

A brain consists of numerous distinct neurons arising from a limited number of progenitors, called neuroblasts in Drosophila. Each neuroblast produces a specific neuronal lineage. To unravel the transcriptional networks that underlie the development of distinct neuroblast lineages, we marked and isolated lineage-specific neuroblasts for RNA sequencing. We labeled particular neuroblasts throughout neurogenesis by activating a conditional neuroblast driver in specific lineages using various intersection strategies. The targeted neuroblasts were efficiently recovered using a custom-built device for robotic single-cell picking. Transcriptome analysis of mushroom body, antennal lobe and type II neuroblasts compared with non-selective neuroblasts, neurons and glia revealed a rich repertoire of transcription factors expressed among neuroblasts in diverse patterns. Besides transcription factors that are likely to be pan-neuroblast, many transcription factors exist that are selectively enriched or repressed in certain neuroblasts. The unique combinations of transcription factors present in different neuroblasts may govern the diverse lineage-specific neuron fates. [ABSTRACT FROM AUTHOR]

Drosophila type II neuroblasts (NBs), like mammalian neural stem cells, deposit neurons through intermediate neural progenitors (INPs) that can each produce a series of neurons. Both type II NBs and INPs exhibit age-dependent expression of various transcription factors, potentially specifying an array of diverse neurons by combinatorial temporal patterning. Not knowing which mature neurons are made by specific INPs, however, conceals the actual variety of neuron types and limits further molecular studies. Here we mapped neurons derived from specific type II NB lineages and found that sibling INPs produced a morphologically similar but temporally regulated series of distinct neuron types. This suggests a common fate diversification program operating within each INP that is modulated by NB age to generate slightly different sets of diverse neurons based on the INP birth order. Analogous mechanisms might underlie the expansion of neuron diversity via INPs in mammalian brain. [ABSTRACT FROM AUTHOR]

Memory-retrieval processing of cross-modal sensory preconditioning is vital for understanding the plasticity underlying the interactions between modalities. As part of the sensory preconditioning paradigm, it has been hypothesized that the conditioned response to an unreinforced cue depends on the memory of the reinforced cue via a sensory link between the two cues. To test this hypothesis, we studied cross-modal memory-retrieval processing in a genetically tractable model organism, Drosophila melanogaster. By expressing the domi-nant temperature-sensitive shibiretsl (shitsl) transgene, which blocks synaptic vesicle recycling of specific neural subsets with the Gal4/ UAS system at the restrictive temperature, we specifically blocked visual and olfactory memory retrieval, either alone or in combination; memory acquisition remained intact for these modalities. Blocking the memory retrieval of the reinforced olfactory cues did not impair the conditioned response to the unreinforced visual cues or vice versa, in contrast to the canonical memory-retrieval processing of sensory preconditioning. In addition, these conditioned responses can be abolished by blocking the memory retrieval of the two modal-ities simultaneously. In sum, our results indicated that a conditioned response to an unreinforced cue in cross-modal sensory precondi-tioning can be recalled through parallel pathways. [ABSTRACT FROM AUTHOR]

Inflexible cognition and behavior are prominent features of prefrontal cortex damage and several neuropsychiatrie disorders. The ability to flexibly adapt cognitive processing and behavior to dynamically changing environmental contingencies has been studied using the reversal learning paradigm in mammals, but the complexity of the brain circuits precludes a detailed analysis of the underlying neural mechanism. Here we study the neural circuitry mechanism supporting flexible behavior in a genetically tractable model organism, Drosophila melanogaster. Combining quantitative behavior analysis and genetic manipulation, we found that inhibition from a single pair of giant GABAergic neurons, the anterior paired lateral (APL) neurons, onto the mushroom bodies (MBs) selectively facilitates behavioral flexibility during visual reversal learning. This effect was mediated by ionotropic GABAA receptors in the MB. Moreover, flies with perturbed MB output recapitulated the poor reversal performance of flies with dysfunctional APL neurons. Importantly, we observed that flies with dysfunctional APL-MB circuit performed normally in simple forms of visual learning, including initial learning, extinction, and differential conditioning. Finally, we showed that acute disruption of the APL-MB circuit is sufficient to impair visual reversal learning. Together, these data suggest that the APL-MB circuit plays an essential role in the resolution of conflicting reinforcement contingencies and reveals an inhibitory neural mechanism underlying flexible behavior in Drosophila. [ABSTRACT FROM AUTHOR]