In recent years, large language models (LLMs) have demonstrated significant potential across various natural language processing (NLP) tasks. However, their performance in domain-specific applications and non-English languages remains less explored. This study introduces a novel Romanian-language dataset for multiple-choice biology questions, carefully curated to assess LLM comprehension and reasoning capabilities in scientific contexts. Containing approximately 14,000 questions, the dataset provides a comprehensive resource for evaluating and improving LLM performance in biology. We benchmark several popular LLMs, analyzing their accuracy, reasoning patterns, and ability to understand domain-specific terminology and linguistic nuances. Additionally, we perform comprehensive experiments to evaluate the impact of prompt engineering, fine-tuning, and other optimization techniques on model performance. Our findings highlight both the strengths and limitations of current LLMs in handling specialized knowledge tasks in low-resource languages, offering valuable insights for future research and development.
In the article we establish the global well-posedness in W^{1,(6,2)}(R \times R+) of the integro-differential equation containing the cube of the one dimensional Laplacian and the transport term. Our proof relies on a fixed point technique. Furthermore, we formulate the condition leading to the existence of the nontrivial solution for our problem under the consideration. This problem is relevant to the cell population dynamics in the Mathematical Biology.
The work is devoted to the global well-posedness in W^{1, (4, 2)}(R\times R^{+}) of the integro-differential problem involving the square of the one dimensional Laplace operator along with the drift term. Our proof is based on a fixed point technique. Moreover, we provide the assumption leading to the existence of the nontrivial solution for the problem under the consideration. Such equation is relevant to the cell population dynamics in the Mathematical Biology.
ABSTRACT The field of soil science has seen significant advancements in recent years, largely due to the integration of computational tools and statistical methods. Among these resources, the programming language R has emerged as a powerful and versatile platform for soil scientists, aiding in a spectrum of tasks from data analysis and modeling to visualization. Nonetheless, the broader trends and specific patterns of R usage in soil research have not been thoroughly documented. Our study investigated the prevalence of R and its package usage in 25,888 research articles published in 10 leading soil science journals over a decade, from 2014 to 2023. A considerable number of these articles, 7899 (or 30.5%), named R as their primary data analysis tool. The use of R has followed a steady linear growth pattern, rising from 13.9% in 2014 to 46.5% in 2023. The most commonly used R packages were “vegan,” “ggplot2,” “lme4,” “nlme,” and “randomForest,” with each journal showcasing unique research focuses, resulting in varying frequencies of R package applications across different publications. Furthermore, there was a notable increase in the average number of R packages used per article throughout the study period. This research highlights the pivotal role of R, armed with its robust statistical and visualization capabilities, in enabling soil scientists to conduct comprehensive analyses and gain in‐depth insights into the complex dimensions of soil science.
Onella Athnaiel, Nicholas Davidson, Jaskaran Mangat
et al.
Chronic pain, pain that lasts beyond three months, is a common finding in the elderly. It is often due to musculoskeletal conditions but can be precipitated by other factors as well. While physiological systems decline with aging, chronic pain is influenced by changes in hormone profiles as men and women enter into andropause and menopause, respectively. Research on gonadal hormones is limited, especially when it comes to their relationship with chronic pain. Women tend to experience less pain with aging compared to their premenopausal years, and this is partially explained by the fact that estrogen enhances pain sensitivity and its decline during menopause decreases it. However, hormone replacement therapy (HRT) seems to increase pain tolerance post-menopause. There is some evidence that testosterone plays a protective factor in pain perception. Men on the other hand, have higher pain tolerance as testosterone is considered to be a protective factor. With aging and decreasing testosterone, older men tend to be less tolerant to pain. This paper explores how hormonal changes with aging impact pain perception in both men and women, highlighting several pain conditions influenced by hormones. Although research remains limited, the potential of HRT as a treatment for common pain conditions is examined.
We address the challenge of acquiring real-world manipulation skills with a scalable framework. We hold the belief that identifying an appropriate prediction target capable of leveraging large-scale datasets is crucial for achieving efficient and universal learning. Therefore, we propose to utilize 3D flow, which represents the future trajectories of 3D points on objects of interest, as an ideal prediction target. To exploit scalable data resources, we turn our attention to human videos. We develop, for the first time, a language-conditioned 3D flow prediction model directly from large-scale RGBD human video datasets. Our predicted flow offers actionable guidance, thus facilitating zero-shot skill transfer in real-world scenarios. We deploy our method with a policy based on closed-loop flow prediction. Remarkably, without any in-domain finetuning, our method achieves an impressive 81\% success rate in zero-shot human-to-robot skill transfer, covering 18 tasks in 6 scenes. Our framework features the following benefits: (1) scalability: leveraging cross-embodiment data resources; (2) wide application: multiple object categories, including rigid, articulated, and soft bodies; (3) stable skill transfer: providing actionable guidance with a small inference domain-gap. Code, data, and supplementary materials are available https://general-flow.github.io
Ribosomal DNA (rDNA), which encodes ribosomal RNA, is an essential but unstable genomic element due to its tandemly repeated nature. rDNA's repetitive nature causes spontaneous intrachromatid recombination, leading to copy number (CN) reduction, which must be counteracted by a mechanism that recovers CN to sustain cells' viability. Akin to telomere maintenance, rDNA maintenance is particularly important in cell types that proliferate for an extended time period, most notably in the germline that passes the genome through generations. In Drosophila, the process of rDNA CN recovery, known as 'rDNA magnification', has been studied extensively. rDNA magnification is mediated by unequal sister chromatid exchange (USCE), which generates a sister chromatid that gains the rDNA CN by stealing copies from its sister. However, much remains elusive regarding how germ cells sense rDNA CN to decide when to initiate magnification, and how germ cells balance between the need to generate DNA double-strand breaks (DSBs) to trigger USCE vs. avoiding harmful DSBs. Recently, we identified an rDNA-binding Zinc-finger protein Indra as a factor required for rDNA magnification, however, the underlying mechanism of action remains unknown. Here we show that Indra is a negative regulator of rDNA magnification, balancing the need of rDNA magnification and repression of dangerous DSBs. Mechanistically, we show that Indra is a repressor of RNA polymerase II (Pol II)-dependent transcription of rDNA: Under low rDNA CN conditions, Indra protein amount is downregulated, leading to Pol II-mediated transcription of rDNA. This results in the expression of rDNA-specific retrotransposon, R2, which we have shown to facilitate rDNA magnification via generation of DBSs at rDNA. We propose that differential use of Pol I and Pol II plays a critical role in regulating rDNA CN expansion only when it is necessary.
Maia Butsashvili, Lasha Gulbiani, Giorgi Kanchelashvili
et al.
Abstract Objective The objective of the study was to understand the role of self-reported drinking behavior on liver health after achieving sustained viral response (SVR) among HCV patients. Results The study was conducted in HCV treatment provider clinics in three cities in Georgia: Tbilisi, Batumi, and Telavi. Face-to-face interviews were conducted using a questionnaire developed specifically for this study. 9.5% considered themselves heavy drinkers, while 94.2% were aware that heavy alcohol consumption can progress liver fibrosis. During treatment, 97.8% abstained from alcohol, while 76.6% reported resuming drinking after achieving SVR. Additionally, 52.1% believed that moderate alcohol intake is normal for individuals with low fibrosis scores. Liver fibrosis improvement was more prevalent among individuals who abstained from alcohol after HCV diagnosis (85.4% vs. 71.4%, p < 0.01) and after achieving SVR (87.5% vs. 74.7% of those who resumed drinking after achieving SVR, p < 0.02). In conclusion, the majority of HCV patients abstain from alcohol during treatment but resume drinking after achieving SVR. Those who abstain from alcohol intake after HCV cure have a higher chance of liver fibrosis improvement.
Sleep disruption is common in older adults and has been linked to many negative health outcomes, including impaired cognitive, emotional, and interpersonal functioning and maladaptive metabolic changes. Sleep disturbance is the most common symptom in depressive patients, and it was formerly thought to be a major secondary manifestation of depression. Many longitudinal studies have identified insomnia as an independent risk factor for the development of emerging or recurrent depression in older adults, with bidirectional relationships between sleep quality and depression. This narrative review summarizes recent research or evidence on the sleep–depression association in older adults, as well as the potential common mechanisms underlying the comorbidity of sleep and depression disorders, focusing on the clock system, neurochemical substrates, and neurocircuits. A better understanding of the pathophysiological mechanisms underlying sleep disturbance and depression can assist psychiatrists in better managing this comorbidity.
The general relativistic Poynting-Robertson (PR) effect is a very important dissipative phenomenon occurring in high-energy astrophysics. Recently, it has been proposed a new model, which upgrades the two-dimensional (2D) description in the three-dimensional (3D) case in Kerr spacetime. The radiation field is considered as constituted by photons emitted from a rigidly rotating spherical source around the compact object. Such dynamical system admits the existence of a critical hypersurface, region where the gravitational and radiation forces balance and the matter reaches it at the end of its motion. Selected test particle orbits are displayed. We show how to prove the stability of these critical hypersurfaces within the Lyapunov theory. Then, we present how to study such effect under the Lagrangian formalism, explaining how to analytically derive the Rayleigh potential for the radiation force. In conclusion, further developments and future projects are discussed.
The prevalence of dementia has increased over time as global life expectancy improves and populations age. An individual's risk of developing dementia is influenced by various genetic, lifestyle, and environmental factors, among others. Predicting dementia risk may enable individuals to employ mitigation strategies or lifestyle changes to delay dementia onset. Current computational approaches to dementia prediction only return risk upon narrow categories of variables and do not account for interactions between different risk variables. The proposed framework utilizes a novel holistic approach to dementia risk prediction and is the first to incorporate various sources of tabular environmental pollution and lifestyle factor data with network systems biology-based genetic data. LightGBM gradient boosting was employed to ensure validity of included factors. This approach successfully models interactions between variables through an original weighted integration method coined Sysable. Multiple machine learning models trained the algorithm to reduce reliance on a single model. The developed approach surpassed all existing dementia risk prediction approaches, with a sensitivity of 85%, specificity of 99%, geometric accuracy of 92%, and AUROC of 91.7%. A transfer learning model was implemented as well. De-biasing algorithms were run on the model via the AI Fairness 360 Library. Effects of demographic disparities on dementia prevalence were analyzed to potentially highlight areas in need and promote equitable and accessible care. The resulting model was additionally integrated into a user-friendly app providing holistic predictions and personalized risk mitigation strategies. The developed model successfully employs holistic computational dementia risk prediction for clinical use.
Cultural General Intelligence Team, Avishkar Bhoopchand, Bethanie Brownfield
et al.
Cultural transmission is the domain-general social skill that allows agents to acquire and use information from each other in real-time with high fidelity and recall. In humans, it is the inheritance process that powers cumulative cultural evolution, expanding our skills, tools and knowledge across generations. We provide a method for generating zero-shot, high recall cultural transmission in artificially intelligent agents. Our agents succeed at real-time cultural transmission from humans in novel contexts without using any pre-collected human data. We identify a surprisingly simple set of ingredients sufficient for generating cultural transmission and develop an evaluation methodology for rigorously assessing it. This paves the way for cultural evolution as an algorithm for developing artificial general intelligence.
Hypertension has relatively large morbidity and mortality rates
throughout the world, including in Indonesia. The prevalence of hypertension
tends to be greater in patients with a family history of hypertension. This is
thought to be influenced by polymorphisms in the methylenetetrahydrofolate reductase
(MTHFR) gene. This study
aims to determine the relationship between the polymorphism of C677T and the A1298C MTHFR gene as a risk factor for essential hypertension. An
observational study with a case-control design was conducted involving 37 cases and 30 control people. Data obtained by PCR-RFLP. Data analysis was performed using chi-square and odds ratio calculations. The most common genotype for C677T
polymorphism is CC (94.6%) followed by CT and TT with 2.7% each (p = 0.001)
with OR of 0.099 (CI95% = 0.02-0.49). The most common genotype for the A1298C
polymorphism is AC (45.9%), followed by AA (35.1%) and CC (19%) (p = 0.001).
The C allele is present in 24 subjects in the case group (64.8%) and in 7
subjects in the control group (23.3%). The OR for the A1298C is 6.06 (CI 95% =
2.1-17.9). The C677T polymorphism showed statistical significance but did not
modify the risk factor of essential hypertension. Whereas the A1298C
polymorphism is statistically significant and has a 6-fold risk factor for
essential hypertension, polymorphism A1298C Methyltetrahydrofolate Reductase (MTHFR) gene is a risk factor of essential
hypertension.
Jing Zhang, Xiaojuan Cheng, Peter W. Fritsch
et al.
Species diversity is high in the Himalaya-Hengduan Mountains, particularly at the edges characterized by deep ravines and “sky islands”. Studies focused on sky-island species are sparse and the patterns observed in response to both geographic and climatic factors are inconsistent. Here phylogeographic and phylogenetic analyses of <i>Gaultheria nummularioides</i>, a species originating in the late Pliocene with its main distribution in the Himalaya-Hengduan Mountains, were conducted to reveal the pattern of genetic dynamics in response to physical geography, glacial fluctuations, and monsoons. We found that in this species genetic variation is higher among populations than within populations, with a significant phylogeographic boundary between the central Himalaya and the eastern Himalaya and the Hengduan Mountains. We also found a high incidence of private alleles, possibly associated with strong habitat isolation. The phylogeographic pattern recovered is consistent with populations in glacial refugia that have experienced expansion after glaciation. The divergence times of most haplotypes coincide with the time of the weakening of the Asian monsoon in these regions. Models of geographic range size showed a significant decrease from the Last Interglacial through the Last Glacial Maximum to the Current, and a predicted increase from the Current to the year 2070. Our study provides insights for understanding speciation among sky islands in this region.
In this study, we aimed to sequence and annotate the complete mtDNA genome sequence of Mystacoleucus lepturus, which were collected from Luosuojiang River in Menglun area, Yunnan Province, China. The mitochondrial genome was 16,592 bp in length, comprising 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs), and two non-coding regions (origin of L-strand replication and control region). The whole genome contained C (26.5%), A (32.5%), T (25.3%), and G (15.7%), with an obvious A + T bias (57.8%). Based on the concatenated amino acids sequences of 13 PCGs of M. lepturus and other 22 fishes, a phylogenetic tree was reconstructed using the maximum-likelihood method. The result of phylogenetic analysis supported a close relationship between M. lepturus and M. marginatus. The fundamental genetic data of M. lepturus would be useful for conservation and phylogeny.
Ruven Wilkens, Anne Hoffrichter, Karolina Kleinsimlinghaus
et al.
Abstract In humans, most neurons are born during embryonic development and have to persist throughout the entire lifespan of an individual. Thus, human neurons have to develop elaborate survival strategies to protect against accidental cell death. We set out to decipher the developmental adaptations resulting in neuronal resilience. We demonstrate that, during the time course of maturation, human neurons install a complex and complementary anti-apoptotic signaling network. This includes i.) a downregulation of central proteins of the intrinsic apoptosis pathway including several caspases, ii.) a shift in the ratio of pro- and anti-apoptotic BCL-2 family proteins, and iii.) an elaborate regulatory network resulting in upregulation of the inhibitor of apoptosis protein (IAP) XIAP. Together, these adaptations strongly increase the threshold for apoptosis initiation when confronted with a wide range of cellular stressors. Our results highlight how human neurons are endowed with complex and redundant preemptive strategies to protect against stress and cell death.
E. Lundberg, Linn Fagerberg, Daniel Klevebring
et al.
An essential question in human biology is how cells and tissues differ in gene and protein expression and how these differences delineate specific biological function. Here, we have performed a global analysis of both mRNA and protein levels based on sequence‐based transcriptome analysis (RNA‐seq), SILAC‐based mass spectrometry analysis and antibody‐based confocal microscopy. The study was performed in three functionally different human cell lines and based on the global analysis, we estimated the fractions of mRNA and protein that are cell specific or expressed at similar/different levels in the cell lines. A highly ubiquitous RNA expression was found with >60% of the gene products detected in all cells. The changes of mRNA and protein levels in the cell lines using SILAC and RNA ratios show high correlations, even though the genome‐wide dynamic range is substantially higher for the proteins as compared with the transcripts. Large general differences in abundance for proteins from various functional classes are observed and, in general, the cell‐type specific proteins are low abundant and highly enriched for cell‐surface proteins. Thus, this study shows a path to characterize the transcriptome and proteome in human cells from different origins.