155 research outputs found

    The spatial-temporal patterns of Asian summer monsoon precipitation in response to Holocene insolation change: a model-data synthesis

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    Highlights: • Slice and transient simulations of Holocene climate change were performed. • Spatial–temporal patterns of Holocene Asian summer precipitation are investigated. • A tripole pattern of summer precipitation can be seen over monsoonal Asia. • Insolation change is a key factor for Holocene Asian summer monsoon change. • Internal feedbacks are important to Holocene Asian summer precipitation changes. Abstract: Paleoclimate proxy records of precipitation/effective moisture show spatial–temporal inhomogeneous over Asian monsoon and monsoon marginal regions during the Holocene. To investigate the spatial differences and diverging temporal evolution over monsoonal Asia and monsoon marginal regions, we conduct a series of numerical experiments with an atmosphere–ocean–sea ice coupled climate model, the Kiel Climate Model (KCM), for the period of Holocene from 9.5 ka BP to present (0 ka BP). The simulations include two time-slice equilibrium experiments for early Holocene (9.5 ka BP) and present-day (0 ka BP), respectively and one transient simulation (HT) using a scheme for model acceleration regarding to the Earth's orbitally driven insolation forcing for the whole period of Holocene (from 9.5 to 0 ka BP). The simulated summer precipitation in the equilibrium experiments shows a tripole pattern over monsoonal Asia as depicted by the first modes of empirical orthogonal function (EOF1) of H0K and H9K. The transient simulation HT exhibits a wave train pattern in the summer precipitation across the Asian monsoon region associated with a gradually decreased trend in the strength of Asian summer monsoon, as a result of the response of Asian summer monsoon system to the Holocene orbitally-forced insolation change. Both the synthesis of multi-proxy records and model experiments confirm the regional dissimilarity of the Holocene optimum precipitation/effective moisture over the East Asian summer monsoon region, monsoon marginal region, and the westerly-dominated areas, suggesting the complex response of the regional climate systems to Holocene insolation change in association with the internal feedbacks within climate system, such as the air-sea interactions associated with the El Nino/Southern Oscillation (ENSO) and shift of the Intertropical Convergence Zone (ITCZ) in the evolution of Asian summer monsoon during the Holocene

    The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks

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    The era post-2018 marked the advent of Large Language Models (LLMs), with innovations such as OpenAI's ChatGPT showcasing prodigious linguistic prowess. As the industry galloped toward augmenting model parameters and capitalizing on vast swaths of human language data, security and privacy challenges also emerged. Foremost among these is the potential inadvertent accrual of Personal Identifiable Information (PII) during web-based data acquisition, posing risks of unintended PII disclosure. While strategies like RLHF during training and Catastrophic Forgetting have been marshaled to control the risk of privacy infringements, recent advancements in LLMs, epitomized by OpenAI's fine-tuning interface for GPT-3.5, have reignited concerns. One may ask: can the fine-tuning of LLMs precipitate the leakage of personal information embedded within training datasets? This paper reports the first endeavor to seek the answer to the question, particularly our discovery of a new LLM exploitation avenue, called the Janus attack. In the attack, one can construct a PII association task, whereby an LLM is fine-tuned using a minuscule PII dataset, to potentially reinstate and reveal concealed PIIs. Our findings indicate that, with a trivial fine-tuning outlay, LLMs such as GPT-3.5 can transition from being impermeable to PII extraction to a state where they divulge a substantial proportion of concealed PII. This research, through its deep dive into the Janus attack vector, underscores the imperative of navigating the intricate interplay between LLM utility and privacy preservation

    Prevalence of cerebral palsy comorbidities in China: a systematic review and meta-analysis

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    ObjectivesThis systematic review aimed to comprehensively understand the comorbidity of cerebral palsy (CP) in China.MethodsWe searched through databases in both Chinese and English until December 2022 to gather cross-sectional studies on the comorbidity of CP in China. After two reviewers independently screened the articles, collected the data, and assessed the bias risk, a meta-analysis was conducted using the Stata 17.0 software.ResultsA total of 73 articles were included. Of these, 16 articles reported total comorbidity, with a prevalence of 79.7% (95% CI: 73.8–85.7%); 56 articles reported epilepsy, with a prevalence of 17.9% (95% CI: 15.4–20.4%); 48 articles reported intellectual disability, with a prevalence of 58.0% (95% CI: 51.8–64.3%); 32 articles reported speech disorders, with a prevalence of 48.0% (95% CI: 41.6–54.4%); 41 articles reported hearing disorders, with a prevalence of 17.2% (95% CI: 13.0–21.4%); and 35 articles reported vision disorders, with a prevalence of 23.1% (95% CI: 16.3–29.8%). The topographical type of CP was the primary source of heterogeneity in the prevalence of epilepsy. Diagnostic criteria for CP, clinical type of CP, GMFCS, publishing time, and topographical type of CP were the primary sources of heterogeneity in the prevalence of intellectual disability. Clinical type of CP and topographical type were the primary sources of heterogeneity in the prevalence of speech disorders. Finally, the region was the primary source of heterogeneity in the prevalence of hearing disorders.ConclusionThe prevalence of comorbidities in CP is high in China. Comorbidities are related to the characteristics, severity, and risk factors of brain insult and have a particular relationship with regional economic development and medical and health levels

    Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

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    <p>Abstract</p> <p>Background</p> <p>Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgV<sub>H</sub>) mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgV<sub>H</sub> status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgV<sub>H</sub> mutational status which can accurately predict the survival outcome are yet to be discovered.</p> <p>Results</p> <p>In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO) and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgV<sub>H</sub> mutation status from the ZAP70 co-expression network.</p> <p>Conclusions</p> <p>We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgV<sub>H</sub> mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.</p

    Multiomics integration reveals the effect of Orexin A on glioblastoma

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    Objectives: This study involved a multi-omics analysis of glioblastoma (GBM) samples to elaborate the potential mechanism of drug treatment.Methods: The GBM cells treated with or without orexin A were acquired from sequencing analysis. Differentially expressed genes/proteins/metabolites (DEGs/ DEPs/ DEMs) were screened. Next, combination analyses were conducted to investigate the common pathways and correlations between the two groups. Lastly, transcriptome-proteome-metabolome association analysis was carried out to determine the common pathways, and the genes in these pathways were analyzed through Kaplan-Meier (K-M) survival analysis in public databases. Cell and animal experiments were performed to investigate the anti-glioma activity of orexin A.Results: A total of 1,527 DEGs, 52 DEPs, and 153 DEMs were found. Moreover, the combination analyses revealed that 6, 4, and 1 common pathways were present in the transcriptome-proteome, proteome-metabolome, and transcriptome-metabolome, respectively. Certain correlations were observed between the two data sets. Finally, 11 common pathways were discovered in association analysis, and 138 common genes were screened out in these common pathways. Six genes showed significant differences in terms of survival in both TCGA and CGGA. In addition, orexin A inhibited the proliferation, migration, and invasion of glioma in vitro and in vivo.Conclusion: Eleven common KEGG pathways with six common genes were found among different omics participations, revealing the underlying mechanisms in different omics and providing theoretical basis and reference for multi-omics research on drug treatment

    The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies

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    Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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