Multiple interactive memory representations underlie the induction of false memory.

Theoretical and computational models such as transfer-appropriate processing (TAP) and global matching models have emphasized the encoding-retrieval interaction of memory representations in generating false memories, but relevant neural mechanisms are still poorly understood. By manipulating the sensory modalities (visual and auditory) at different processing stages (learning and test) in the Deese-Roediger-McDermott task, we found that the auditory-learning visual-test (AV) group produced more false memories (59%) than the other three groups (42∼44%) [i.e., visual learning visual test (VV), auditory learning auditory test (AA), and visual learning auditory test (VA)]. Functional imaging results showed that the AV group's proneness to false memories was associated with (i) reduced representational match between the tested item and all studied items in the visual cortex, (ii) weakened prefrontal monitoring process due to the reliance on frontal memory signal for both targets and lures, and (iii) enhanced neural similarity for semantically related words in the temporal pole as a result of auditory learning. These results are consistent with the predictions based on the TAP and global matching models and highlight the complex interactions of representations during encoding and retrieval in distributed brain regions that contribute to false memories

A Survey on In-context Learning

With the increasing ability of large language models (LLMs), in-context learning (ICL) has become a new paradigm for natural language processing (NLP), where LLMs make predictions only based on contexts augmented with a few examples. It has been a new trend to explore ICL to evaluate and extrapolate the ability of LLMs. In this paper, we aim to survey and summarize the progress and challenges of ICL. We first present a formal definition of ICL and clarify its correlation to related studies. Then, we organize and discuss advanced techniques, including training strategies, demonstration designing strategies, as well as related analysis. Finally, we discuss the challenges of ICL and provide potential directions for further research. We hope that our work can encourage more research on uncovering how ICL works and improving ICL.Comment: Papers collected until 2023/05/2

An inventory of invasive alien species in China

Invasive alien species (IAS) are a major global challenge requiring urgent action, and the Strategic Plan for Biodiversity (2011–2020) of the Convention on Biological Diversity (CBD) includes a target on the issue. Meeting the target requires an understanding of invasion patterns. However, national or regional analyses of invasions are limited to developed countries. We identified 488 IAS in China’s terrestrial habitats, inland waters and marine ecosystems based on available literature and field work, including 171 animals, 265 plants, 26 fungi, 3 protists, 11 procaryots, and 12 viruses. Terrestrial plants account for 51.6% of the total number of IAS, and terrestrial invertebrates (104 species) for 21.3%. Of the total numbers, 67.9% of plant IAS and 34.8% of animal IAS were introduced intentionally. All other taxa were introduced unintentionally despite very few animal and plant species that invaded naturally. In terms of habitats, 64.3% of IAS occur on farmlands, 13.9% in forests, 8.4% in marine ecosystems, 7.3% in inland waters, and 6.1% in residential areas. Half of all IAS (51.1%) originate from North and South America, 18.3% from Europe, 17.3% from Asia not including China, 7.2% from Africa, 1.8% from Oceania, and the origin of the remaining 4.3% IAS is unknown. The distribution of IAS can be divided into three zones. Most IAS are distributed in coastal provinces and the Yunnan province; provinces in Middle China have fewer IAS, and most provinces in West China have the least number of IAS. Sites where IAS were first detected are mainly distributed in the coastal region, the Yunnan Province and the Xinjiang Uyghur Autonomous Region. The number of newly emerged IAS has been increasing since 1850. The cumulative number of firstly detected IAS grew exponentially

Relating the composition of continental margin surface sediments from the Ross Sea to the Amundsen Sea, West Antarctica, to modern environmental conditions

Investigating the multiple proxies involving productivity, organic geochemistry, and trace element (TE) enrichment in surface sediments could be used as paleoenvironment archives to gain insights into past and future environmental conditions changes. We present redox-sensitive TEs (Mn, Ni, Cu, U, P, Mo, Co, V, Zn, and Cd), productivity-related proxies (total organic carbon and opal), and total nitrogen and CaCO3 contents of bulk surface sediments of this area. The productivity proxies from the shelf and coastal regions of the Ross and the Amundsen seas showed that higher productivity was affiliated with an area of nutrient-rich deep water upwelling. The upwelling of weakly corrosive deep water may be beneficial for preserving CaCO3, while highly corrosive dense water, if it forms on the shelf near the coastal region (coastal polynya), could limit the preservation of CaCO3 in modern conditions. There were no oxic or anoxic conditions in the study area, as indicated by the enrichment factors of redox-sensitive TEs (Mn, Co, and U). The enrichment factor of Cd, which is redox-sensitive, indicated suboxic redox conditions in sediment environments because of high primary productivity and organic matter preservation/decomposition. The enrichment factors of other redox-sensitive TEs (P, Ni, Cu, V, and Zn) and the correlations between the element/Ti ratio with productivity and nutrient proxies indicated that the organic matter decomposed, and there was massive burial of phytoplankton biomass. There was variation in the enrichment, such that sediments were enriched in P, Mo, and Zn, but depleted in Ni, Cu, and V

Risk factors for recurrent IgA nephropathy after renal transplantation: A meta-analysis

Recurrent glomerulonephritis after renal transplantation is the third most common cause of allograft loss, the most frequent of which is associated with IgA nephropathy (IgAN). This study aims to provide a systematic review of the risk factors associated with recurrent IgAN after renal transplantation. We searched English and Chinese databases, including PubMed, Embase, Web of Science, CNKI, and others, and included all case-control studies involving risk factors for recurrent IgAN after renal transplantation from the databases’ establishment to March 2022. Data were analyzed using the Stata 12.0. A total of 20 case–control studies were included in the meta-analysis, with 542 patients with recurrent IgAN and 1385 patients without recurrent IgAN. The results showed that donor age (standardized mean difference [SMD] -0.13 [95% CI -0.26, -0.001]; P = 0.048), patient age at transplantation (SMD -0.41 [95% CI -0.53, -0.29]; P < 0.001), time from diagnosis to end-stage renal disease (SMD -0.42 [95% CI -0.74, -0.10]; P = 0.010), previous transplantation (odds ratio [OR] 1.73 [95% CI 1.06, 2.81]; P = 0.027), living donor (OR 1.86 [95% CI 1.34, 2.58]; P < 0.001), related donor (OR 2.64, [95% CI 1.84, 3.79]; P < 0.001), tacrolimus use (OR 0.71 [95% CI 0.52, 0.98]; P = 0.035), basiliximab use (OR 0.39 [95% CI 0.27, 0.55]; P < 0.001), proteinuria (SMD 0.42 [95% CI 0.13, 0.71]; P = 0.005) and serum IgA level (SMD 0.48 [95% CI 0.27, 0.69]; P < 0.001) were associated with recurrent IgAN after renal transplantation. In general, tacrolimus and basiliximab use were protective factors against recurrent IgAN after renal transplantation, whereas donor age, patient age at transplantation, time from diagnosis to end-stage renal disease, previous transplantation, living donor, related donor, proteinuria, and serum IgA level were risk factors for recurrent IgAN after renal transplantation. Clinical decision making should warrant further consideration of these risk factors

Risk factors for recurrent IgA nephropathy after renal transplantation: A meta-analysis

Recurrent glomerulonephritis after renal transplantation is the third most common cause of allograft loss, the most frequent of which is associated with IgA nephropathy (IgAN). This study aims to provide a systematic review of the risk factors associated with recurrent IgAN after renal transplantation. We searched English and Chinese databases, including PubMed, Embase, Web of Science, CNKI, and others, and included all case-control studies involving risk factors for recurrent IgAN after renal transplantation from the databases’ establishment to March 2022. Data were analyzed using the Stata 12.0. A total of 20 case–control studies were included in the meta-analysis, with 542 patients with recurrent IgAN and 1385 patients without recurrent IgAN. The results showed that donor age (standardized mean difference [SMD] -0.13 [95% CI -0.26, -0.001]; P = 0.048), patient age at transplantation (SMD -0.41 [95% CI -0.53, -0.29]; P < 0.001), time from diagnosis to end-stage renal disease (SMD -0.42 [95% CI -0.74, -0.10]; P = 0.010), previous transplantation (odds ratio [OR] 1.73 [95% CI 1.06, 2.81]; P = 0.027), living donor (OR 1.86 [95% CI 1.34, 2.58]; P < 0.001), related donor (OR 2.64, [95% CI 1.84, 3.79]; P < 0.001), tacrolimus use (OR 0.71 [95% CI 0.52, 0.98]; P = 0.035), basiliximab use (OR 0.39 [95% CI 0.27, 0.55]; P < 0.001), proteinuria (SMD 0.42 [95% CI 0.13, 0.71]; P = 0.005) and serum IgA level (SMD 0.48 [95% CI 0.27, 0.69]; P < 0.001) were associated with recurrent IgAN after renal transplantation. In general, tacrolimus and basiliximab use were protective factors against recurrent IgAN after renal transplantation, whereas donor age, patient age at transplantation, time from diagnosis to end-stage renal disease, previous transplantation, living donor, related donor, proteinuria, and serum IgA level were risk factors for recurrent IgAN after renal transplantation. Clinical decision making should warrant further consideration of these risk factors

Employing machine learning using ferroptosis-related genes to construct a prognosis model for patients with osteosarcoma

Identifying effective biomarkers in osteosarcoma (OS) is important for predicting prognosis. We investigated the prognostic value of ferroptosis-related genes (FRGs) in OS. Transcriptome and clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus. FRGs were obtained from the ferroptosis database. Univariate COX regression and LASSO regression screening were performed and an FRG-based prognostic model was constructed, which was validated using the Gene Expression Omnibus cohort. The predictive power of the model was assessed via a subgroup analysis. A nomogram was constructed using clinical markers with independent prognostic significance and risk score results. The CIBERSORT algorithm was used to detect the correlation between prognostic genes and 22 tumor-infiltrating lymphocytes. The expression of prognostic genes in erastin-treated OS cell lines was verified via real-time PCR. Six prognostic FRGs (ACSL5, ATF4, CBS, CDO1, SCD, and SLC3A2) were obtained and used to construct the risk prognosis model. Subjects were divided into high- and low-risk groups. Prognosis was worse in the high-risk group, and the model had satisfactory prediction performance for patients younger than 18 years, males, females, and those with non-metastatic disease. Univariate COX regression analysis showed that metastasis and risk score were independent risk factors for patients with OS. Nomogram was built on independent prognostic factors with superior predictive power and patient benefit. There was a significant correlation between prognostic genes and tumor immunity. Six prognostic genes were differentially expressed in ferroptosis inducer-treated OS cell lines. The identified prognostic genes can regulate tumor growth and progression by affecting the tumor microenvironment