Hasil untuk "Human anatomy"

Cynthia M. Baseman, Myeonghan Ryu, Nathaniel Swinger et al.

Psychotherapy delivery relies on a negotiation between patient self-reports and clinical intuition. Growing evidence for technological support of psychotherapy suggests opportunities to aid the mediation of this tension. To explore this prospect, we designed a prototype of a clinical decision support system (CDSS) for treating veterans with post-traumatic stress disorder in a Prolonged Exposure (PE) therapy intensive outpatient program. We conducted a two-phase interview study to collect perspectives from practicing PE clinicians and former PE patients who are United States veterans. Our analysis distills opportunities for a CDSS (e.g., offering homework review at a glance, aiding patient conceptualization) and larger challenges related to context and deployment (e.g., navigating Veterans Affairs). By reframing our findings through three human-centered perspectives (distributed cognition, situated learning, infrastructural inversion), we highlight the complexities of designing a CDSS for psychotherapists in this context and offer theory-aligned design considerations.

Lilian Baker, Hannah Jacobson, Amanda McGrosky et al.

Background Climate change is increasing temperatures, frequency of heatwaves, and erratic rainfall, which threatens human biology and health, particularly in already extreme environments. Therefore, it is important to understand how environmental heat stress measures are tied to human water needs and thermoregulation under increasingly hot conditions.Aim To test how ambient temperature, heat index, and wet bulb globe temperature (WBGT) relate to hydration status and thermal heat perception in a hot, semi-arid environment.Subjects and methods Urine samples, perceived heat stress, and anthropometrics were collected among Daasanach semi-nomadic pastoralists (n = 187 children, n = 231 adults) in northern Kenya. Environmental heat stress measures were recorded at sample collection; samples’ urine specific gravity (USG) was measured.Results Multiple linear and logistic regressions indicate that all environmental heat stress measures were associated with USG, odds of dehydration, and heat perception. Ambient temperature performed marginally better than WBGT, and both performed better than heat index. These associations were stronger among children than adults.Conclusion In a hot, semi-arid climate, ambient temperature and WBGT accurately predict human water needs and heat stress, with children more vulnerable to dehydration. To mitigate consequences of extreme heat, local bioculturally-appropriate hydration (e.g. tea) and cooling (e.g. shade) strategies should be encouraged.

Rachana Mehta, Ashok Kumar Balaraman, Muhammed Shabil et al.

Takashi Yamamoto, Kayoko Ueji, Haruno Mizuta et al.

The concept of ‘kokumi’, which refers to an enhanced and more delicious flavor of food, has recently generated considerable interest in food science. However, kokumi has not been well studied in gustatory physiology, and the underlying neuroscientific mechanisms remain largely unexplored. Our previous research demonstrated that ornithine (L-ornithine), which is abundant in shijimi clams, enhanced taste preferences in mice. The present study aimed to build on these findings and investigate the mechanisms responsible for kokumi in rats. In two-bottle preference tests, the addition of ornithine, at a low concentration that did not increase the favorability of this substance alone, enhanced the animals’ preferences for umami, sweet, fatty, salty, and bitter solutions, with the intake of monosodium glutamate showing the most significant increase. Additionally, a mixture of umami and ornithine synergistically induced significant responses in the chorda tympani nerve, which transmits taste information to the brain from the anterior part of the tongue. The observed preference enhancement and increase in taste-nerve response were abolished by antagonists of the G-protein-coupled receptor family C group 6 subtype A (GPRC6A). Furthermore, immunohistochemical analysis indicated that GPRC6A was expressed in a subset of type II taste cells in rat fungiform papillae. These results provide new insights into flavor-enhancement mechanisms, confirming that ornithine is a kokumi substance and GPRC6A is a novel kokumi receptor.

Guomiao Su, Yanxi Li, Juan Wang et al.

Abstract Hepatocellular carcinoma (HCC) represents the most prevalent histological subtype of primary liver cancer. This study aimed to establish a miRNA-related prognostic genes signature, providing a theoretical framework for prognosis and therapy in patients with HCC. The miRNA-correlated (MIRcor) genes were identified through correlation analysis of miRNA-mRNA relationships from three databases. Consensus clustering was then applied to HCC samples based on these MIRcor genes. Differentially expressed genes (DEGs) between HCC and normal samples, as well as between subtypes with the most significant survival differences, were extracted. Subtype-and-tumor common DEGs were identified by intersecting these DEGs. Prognostic genes were derived using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. A risk model was developed with the The Cancer Genome Atlas-Hepatocellular Carcinoma (TCGA-HCC) dataset and validated in the International Cancer Genome Consortium-Hepatocellular Carcinoma (ICGC-HCC) dataset, while independent prognostic predictors were confirmed through Cox analysis. Additionally, an immune microenvironment analysis was conducted to compare high- and low-risk groups. From the subtype-and-tumor common DEGs, five prognostic genes were identified and used to construct a prognostic gene signature. Expression of these genes was further validated at both protein and mRNA levels via Western blotting and Reverse Transcription Polymerase Chain Reaction (RT-PCR). The risk score and T stage emerged as reliable independent prognostic predictors. We observed significant differences in the abundance of 11 types of immune cells between the high-risk and low-risk groups. All five prognostic genes were expressed at significantly higher levels in normal liver tissues than in HCC tumor tissues. A risk model based on these genes offers a theoretical basis and valuable reference for HCC management.

Aron Emmi, Giulia Bonato, Aleksandar Tushevski et al.

Abstract Objective Primary Familial Brain Calcification (PFBC) is a rare neurodegenerative disorder characterized by small vessel calcifications in the basal ganglia. PFBC is caused by pathogenic variants in different genes and its physiopathology is still largely unknown. Skin vascular calcifications have been detected in single PFBC cases, suggesting that calcium deposition may not be limited to the brain, but it is unknown whether this is a hallmark of all PFBC genetic and clinical subtypes. This work aims at assessing anatomical and subcellular localization of calcium‐phosphate deposits in skin biopsies from PFBC patients to ascertain the accuracy of histological calcium staining in differentiating PFBC from healthy controls (HC) and Parkinson's Disease (PD). Methods Histopathology and light microscopy of skin biopsy from 20 PFBC, 7 HC and 10 PD subjects (3 mm ø–5 mm deep punch biopsies, Hematoxylin–Eosin and vonKossa staining, immunoperoxidase CD31 staining); clinical, genetic and radiological assessment. Results Unlike HC and PD subjects, the majority of PFBC patients (17/20) showed a consistent pattern of granular argyrophilic calcium‐phosphate deposits in the basal lamina and the cytoplasm of CD31+ endothelial cells and pericytes of dermal capillaries, and the basement membrane of sweat glands. This pattern was unrelated to the underlying mutated gene or clinical status. Interpretation Skin biopsy may be a novel PFBC diagnostic tool and a potential biomarker for future therapies, and a tool to investigate PFBC disease mechanisms. Different findings in some patients could be due to skin sampling variability and biological consequences of specific PFBC gene variants.

Kei Kanari, Moe Kikuchi

Pupil responses and optokinetic nystagmus (OKN) are known to vary with the brightness and direction of motion of attended stimuli, as well as gaze position. However, whether these processes are controlled by a common mechanism remains unclear. In this study, we investigated how OKN latency relates to pupil response latency under two conditions: gaze shifts (eye movement) and attention shifts (covert attention without eye movement). As a result, while OKN showed consistent temporal changes across both gaze and attention conditions, pupillary responses exhibited distinct patterns. Moreover, the results revealed no significant correlation between pupil latency and OKN latency in either condition. These findings suggest that, although OKN and pupillary responses are influenced by similar attentional processes, their underlying mechanisms may differ.

Joseph M. Hoolachan, Rekha Balakrishnan, Erika M. McCown et al.

ABSTRACT Background Mitochondrial homeostasis is vital for optimal skeletal muscle integrity. Mitochondrial quality control (MQC) mechanisms that are essential for maintaining proper functions of mitochondria include mitochondrial biogenesis, dynamics and mitophagy. Previously, Syntaxin 4 (STX4), traditionally considered a cell surface protein known for glucose uptake in skeletal muscle, was also identified at the outer mitochondrial membrane. STX4 enrichment was sufficient to reverse Type 2 diabetes–associated mitochondrial damage in skeletal muscle by inactivation of mitochondrial fission. However, whether STX4 could modulate skeletal muscle mitochondrial homeostasis through MQC mechanisms involving mitochondrial biogenesis or mitophagy remains to be determined. Methods To determine the requirements of STX4 in mitochondrial structure, function and MQC processes of biogenesis and mitophagy, we implemented our in‐house generated inducible skeletal muscle‐specific STX4‐knockout (skmSTX4‐iKO) mice (Stx4fl/fl; Tg (HSA‐rtTA/TRE‐Cre)/B6) and STX4‐depleted immortalized L6.GLUT4myc myotubes via siRNA knockdown (siSTX4). Results We found that non‐obese skmSTX4‐iKO male mice (> 50% reduced STX4 abundance, soleus and gastrocnemius ***p < 0.001, tibialis anterior (TA) ****p < 0.0001) developed insulin resistance (**p < 0.01), together with reduced energy expenditure (AUC *p < 0.05), respiratory exchange ratio (AUC **p < 0.01) and grip strength (*p < 0.05). STX4 ablation in muscle also impaired mitochondrial oxygen consumption rate (****p < 0.0001). Mitochondrial morphological damage was heterogenous in STX4‐depleted muscle, presenting with small fragmented mitochondria (****p < 0.0001) and decreased electron transport chain (ETC) abundance (CI ***p < 0.001, CII *p < 0.05, CIV **p < 0.01) in oxidative soleus muscle, whereas glycolytic‐rich TA fibres displayed enlarged swollen mitochondria (****p < 0.0001) with no change in ETC abundance. Notably, > 60% reduction of STX4 in siSTX4 L6.GLUT4myc myotubes (****p < 0.0001) also decreased ETC abundance (CI **p < 0.01, CII ***p < 0.001, CIV **p < 0.01) without changes in mitochondrial glucose metabolism, as shown by [U‐13C]glucose isotope tracing. For MQC, both skmSTX4‐iKO male mice (*p < 0.05) and siSTX4 L6.GLUT4myc myotubes (*p < 0.05) showed decreased mitochondrial DNA levels alongside reduced mRNA expression of mitochondrial biogenesis genes Ppargc1a (PGC1‐α, *p < 0.05) and Tfam (*p < 0.05) in skmSTX4‐iKO soleus muscle and PGC1‐α (mRNA **p < 0.01, protein *p < 0.05), NRF1 (mRNA **p < 0.01 and protein *p < 0.05) and Tfam (mRNA *p < 0.05) in siSTX4 L6.GLUT4myc myotubes. Furthermore, live cell imaging using the mt‐Keima mitophagy biosensor in siSTX4 L6.GLUT4myc cells revealed significantly impaired mitochondrial turnover by mitophagy (*p < 0.05) and mitochondria–lysosome colocalization (*p < 0.05). STX4 depletion also reduced canonical mitophagy markers, PINK1 and PARKIN in both skmSTX4‐iKO muscle (PARKIN *p < 0.05, PINK1 **p < 0.01) and siSTX4 L6.GLUT4myc myotubes (PARKIN **p < 0.01, PINK1 *p < 0.05). Conclusions Our study demonstrated STX4 as a key mitochondrial regulator required for mitochondrial homeostasis in skeletal muscle.

Qudusia Sultana, Amith Ramos, Meera Jacob et al.

Background and Aim: In forensic medicine, accurate gender determination from skeletal remains is crucial. In addition to the pelvic bone, the mastoid process is commonly utilized for this purpose. This study investigates various mastoid measurements for precise gender determination in the South Indian population and the development of a discriminant function equation (DFE) based on these measurements. Materials and Methods: Conducted in the Department of Anatomy between March and May 2021, this cross-sectional study involved 85 human skulls. Mastoid measurements, including mastoid length (ML), mastoid breadth (MB), anterior–posterior diameter (APD), and overall mastoid size, were recorded. Qualitative data were presented as frequency and percentage, whereas quantitative data were expressed as mean ± standard deviation Student’s t-test was used to compare means between genders, with statistical significance set at P < 0.05. Results: The findings revealed that males consistently displayed significantly greater mean values for ML, APD, and size compared to females on both sides of the skull (P < 0.05). In addition, on the right side of the skull, males exhibited a significantly larger mean MB (1.39 ± 0.25 cm) than females (1.28 ± 0.22 cm) (P < 0.05). The derived DFE accurately identified 78.7% of males and 85.7% of females. Conclusion: The mastoid process exhibits sexual dimorphism, with males consistently having larger mastoid measurements than females. This underscores its utility as a valuable tool for gender determination in forensic contexts.

Zhuoer Yin, Calvin Yeung, Tomohiro Suzuki et al.

Recent transformer based approaches have demonstrated impressive performance in solving real-world 3D human pose estimation problems. Albeit these approaches achieve fruitful results on benchmark datasets, they tend to fall short of sports scenarios where human movements are more complicated than daily life actions, as being hindered by motion blur, occlusions, and domain shifts. Moreover, due to the fact that critical motions in a sports game often finish in moments of time (e.g., shooting), the ability to focus on momentary actions is becoming a crucial factor in sports analysis, where current methods appear to struggle with instantaneous scenarios. To overcome these limitations, we introduce KASportsFormer, a novel transformer based 3D pose estimation framework for sports that incorporates a kinematic anatomy-informed feature representation and integration module. In which the inherent kinematic motion information is extracted with the Bone Extractor (BoneExt) and Limb Fuser (LimbFus) modules and encoded in a multimodal manner. This improved the capability of comprehending sports poses in short videos. We evaluate our method through two representative sports scene datasets: SportsPose and WorldPose. Experimental results show that our proposed method achieves state-of-the-art results with MPJPE errors of 58.0mm and 34.3mm, respectively. Our code and models are available at: https://github.com/jw0r1n/KASportsFormer

Vaclav Knapp, Matyas Bohacek

Recent pose-transfer methods aim to generate temporally consistent and fully controllable videos of human action where the motion from a reference video is reenacted by a new identity. We evaluate three state-of-the-art pose-transfer methods -- AnimateAnyone, MagicAnimate, and ExAvatar -- by generating videos with actions and identities outside the training distribution and conducting a participant study about the quality of these videos. In a controlled environment of 20 distinct human actions, we find that participants, presented with the pose-transferred videos, correctly identify the desired action only 42.92% of the time. Moreover, the participants find the actions in the generated videos consistent with the reference (source) videos only 36.46% of the time. These results vary by method: participants find the splatting-based ExAvatar more consistent and photorealistic than the diffusion-based AnimateAnyone and MagicAnimate.

Maxence Grand, Damien Pellier, Francis Jambon

The primary objective of the dataset is to provide a better understanding of the coupling between human actions and gaze in a shared working environment with a cobot, with the aim of signifcantly enhancing the effciency and safety of humancobot interactions. More broadly, by linking gaze patterns with physical actions, the dataset offers valuable insights into cognitive processes and attention dynamics in the context of assembly tasks. The proposed dataset contains gaze and action data from approximately 80 participants, recorded during simulated industrial assembly tasks. The tasks were simulated using controlled scenarios in which participants manipulated educational building blocks. Gaze data was collected using two different eye-tracking setups -head-mounted and remote-while participants worked in two positions: sitting and standing.

Xiangrong, Zhu, Yuan Xu et al.

Human cognition is constrained by processing limitations, leading to cognitive overload and inefficiencies in knowledge synthesis and decision-making. Large Language Models (LLMs) present an opportunity for cognitive augmentation, but their current reactive nature limits their real-world applicability. This position paper explores the potential of context-aware cognitive augmentation, where LLMs dynamically adapt to users' cognitive states and task environments to provide appropriate support. Through a think-aloud study in an exhibition setting, we examine how individuals interact with multi-modal information and identify key cognitive challenges in structuring, retrieving, and applying knowledge. Our findings highlight the need for AI-driven cognitive support systems that integrate real-time contextual awareness, personalized reasoning assistance, and socially adaptive interactions. We propose a framework for AI augmentation that seamlessly transitions between real-time cognitive support and post-experience knowledge organization, contributing to the design of more effective human-centered AI systems.

Agnia Sergeyuk, Ilya Zakharov, Ekaterina Koshchenko et al.

The integration of Artificial Intelligence (AI) into Integrated Development Environments (IDEs) is reshaping software development, fundamentally altering how developers interact with their tools. This shift marks the emergence of Human-AI Experience in Integrated Development Environment (in-IDE HAX), a field that explores the evolving dynamics of Human-Computer Interaction in AI-assisted coding environments. Despite rapid adoption, research on in-IDE HAX remains fragmented, which highlights the need for a unified overview of current practices, challenges, and opportunities. To provide a structured overview of existing research, we conduct a systematic literature review of 90 studies, summarizing current findings and outlining areas for further investigation. We organize key insights from reviewed studies into three aspects: Impact, Design, and Quality of AI-based systems inside IDEs. Impact findings show that AI-assisted coding enhances developer productivity but also introduces challenges, such as verification overhead and over-reliance. Design studies show that effective interfaces surface context, provide explanations and transparency of suggestion, and support user control. Quality studies document risks in correctness, maintainability, and security. For future research, priorities include productivity studies, design of assistance, and audit of AI-generated code. The agenda calls for larger and longer evaluations, stronger audit and verification assets, broader coverage across the software life cycle, and adaptive assistance under user control.

Ruican Zhong, Donghoon Shin, Rosemary Meza et al.

This paper explores the integration of causal pathway diagrams (CPD) into human-centered design (HCD), investigating how these diagrams can enhance the early stages of the design process. A dedicated CPD plugin for the online collaborative whiteboard platform Miro was developed to streamline diagram creation and offer real-time AI-driven guidance. Through a user study with designers (N=20), we found that CPD's branching and its emphasis on causal connections supported both divergent and convergent processes during design. CPD can also facilitate communication among stakeholders. Additionally, we found our plugin significantly reduces designers' cognitive workload and increases their creativity during brainstorming, highlighting the implications of AI-assisted tools in supporting creative work and evidence-based designs.

Luca Castri, Gloria Beraldo, Sariah Mghames et al.

Deploying robots in human-shared spaces requires understanding interactions among nearby agents and objects. Modelling cause-and-effect relations through causal inference aids in predicting human behaviours and anticipating robot interventions. However, a critical challenge arises as existing causal discovery methods currently lack an implementation inside the ROS ecosystem, the standard de facto in robotics, hindering effective utilisation in robotics. To address this gap, this paper introduces ROS-Causal, a ROS-based framework for onboard data collection and causal discovery in human-robot spatial interactions. An ad-hoc simulator, integrated with ROS, illustrates the approach's effectiveness, showcasing the robot onboard generation of causal models during data collection. ROS-Causal is available on GitHub: https://github.com/lcastri/roscausal.git.

Takahiro Tsumura, Seiji Yamada

As anthropomorphic agents (AI and robots) are increasingly used in society, empathy and trust between people and agents are becoming increasingly important. A better understanding of agents by people will help to improve the problems caused by the future use of agents in society. In the past, there has been a focus on the importance of self-disclosure and the relationship between agents and humans in their interactions. In this study, we focused on the attributes of self-disclosure and the relationship between agents and people. An experiment was conducted to investigate hypotheses on trust and empathy with agents through six attributes of self-disclosure (opinions and attitudes, hobbies, work, money, personality, and body) and through competitive and cooperative relationships before a robotic agent performs a joint task. The experiment consisted of two between-participant factors: six levels of self-disclosure attributes and two levels of relationship with the agent. The results showed that the two factors had no effect on trust in the agent, but there was statistical significance for the attribute of self-disclosure regarding a person's empathy toward the agent. In addition, statistical significance was found regarding the agent's ability to empathize with a person as perceived by the person only in the case where the type of relationship, competitive or cooperative, was presented. The results of this study could lead to an effective method for building relationships with agents, which are increasingly used in society.

Luca Castri, Gloria Beraldo, Sariah Mghames et al.

Deploying robots in human-shared environments requires a deep understanding of how nearby agents and objects interact. Employing causal inference to model cause-and-effect relationships facilitates the prediction of human behaviours and enables the anticipation of robot interventions. However, a significant challenge arises due to the absence of implementation of existing causal discovery methods within the ROS ecosystem, the standard de-facto framework in robotics, hindering effective utilisation on real robots. To bridge this gap, in our previous work we proposed ROS-Causal, a ROS-based framework designed for onboard data collection and causal discovery in human-robot spatial interactions. In this work, we present an experimental evaluation of ROS-Causal both in simulation and on a new dataset of human-robot spatial interactions in a lab scenario, to assess its performance and effectiveness. Our analysis demonstrates the efficacy of this approach, showcasing how causal models can be extracted directly onboard by robots during data collection. The online causal models generated from the simulation are consistent with those from lab experiments. These findings can help researchers to enhance the performance of robotic systems in shared environments, firstly by studying the causal relations between variables in simulation without real people, and then facilitating the actual robot deployment in real human environments. ROS-Causal: https://lcastri.github.io/roscausal

Fantu Mamo Aragaw, Dagmawi Chilot, Daniel Gashaneh Belay et al.

Abstract Background In low-and-middle-income, including Ethiopia, high-risk fertility behavior is a major public health concern. High-risk fertility behavior has an adverse influence on maternal and child health, which hampered efforts to reduce maternal and child morbidity and mortality in Ethiopia. Therefore, this study aimed to assess the spatial distribution and associated factors of high-risk fertility behavior among reproductive-age women in Ethiopia using recent nationally representative data. Methods Secondary data analysis was done with a total weighted sample of 5865 reproductive-aged women using the latest mini EDHS 2019. The spatial distribution of high-risk fertility behavior in Ethiopia was determined using spatial analysis. Multilevel multivariable regression analysis was used to identify predictors of high-risk fertility behavior in Ethiopia. Results The prevalence of high-risk fertility behavior among reproductive-age women in Ethiopia was 73.50% (95% CI 72.36%, 74.62%). Women with primary education [AOR = 0.44; 95%CI; 0.37, 0.52], women with secondary and above education [AOR = 0.26; 95%CI; 0.20, 0.34], being Protestant religion followers [AOR = 1.47; 95%CI; 1.15, 1.89], being Muslim religion follower [AOR = 1.56; 95%CI; 1.20, 2.01], having television [AOR = 2.06; 95%CI; 1.54, 2.76], having ANC visit [AOR = 0.78; 95%CI; 0.61, 0.99], using contraception [AOR = 0.77; 95%CI; 0.65, 0.90], living in rural areas [AOR = 1.75; 95%CI; 1.22, 2.50] were significantly associated with high-risk fertility behavior. Significant hotspots of high-risk fertility behavior were detected in Somalia, SNNPR, Tigray region, and Afar regions of Ethiopia. Conclusions A significant proportion of women in Ethiopia engaged in high-risk fertility behavior. High-risk fertility behavior was distributed non-randomly across Ethiopian regions. Policymakers and stakeholders should design interventions that take into account the factors that predispose women to have high-risk fertility behaviors and women who reside in areas with a high proportion of high-risk fertility behaviors to reduce the consequences of high-risk fertility behaviors.

Muhammad Shahbaz, Huachun Miao, Zeeshan Farhaj et al.

Abstract Objectives This study aims to use the three‐dimensional (3D) mixed‐reality model of liver, entailing complex intrahepatic systems and to deeply study the anatomical structures and to promote the training, diagnosis and treatment of liver diseases. Methods Vascular perfusion human specimens were used for thin‐layer frozen milling to obtain liver cross‐sections. The 104‐megapixel‐high‐definition cross sectional data set was established and registered to achieve structure identification and manual segmentation. The digital model was reconstructed and data was used to print a 3D hepatic model. The model was combined with HoloLens mixed reality technology to reflect the complex relationships of intrahepatic systems. We simulated 3D patient specific anatomy for identification and preoperative planning, conducted a questionnaire survey, and evaluated the results. Results The 3D digital model and 1:1 transparent and colored model of liver established truly reflected intrahepatic vessels and their complex relationships. The reconstructed model imported into HoloLens could be accurately matched with the 3D model. Only 7.7% participants could identify accessory hepatic veins. The depth and spatial‐relationship of intrahepatic structures were better understandable for 92%. The 100%, 84.6%, 69% and 84% believed the 3D models were useful in planning, safer surgical paths, reducing intraoperative complications and training of young surgeons respectively. Conclusions A detailed 3D model can be reconstructed using the higher quality cross‐sectional anatomical data set. When combined with 3D printing and HoloLens technology, a novel hybrid‐reality navigation‐training system for liver surgery is created. Mixed Reality training is a worthy alternative to provide 3D information to clinicians and its possible application in surgery. This conclusion was obtained based on a questionnaire and evaluation. Surgeons with extensive experience in surgical operations perceived in the questionnaire that this technology might be useful in liver surgery, would help in precise preoperative planning, accurate intraoperative identification, and reduction of hepatic injury.