Estimating metabolic rate for butadiene at steady state using a Bayesian physiologically-based pharmacokinetic model

In a study of 133 volunteer subjects, demographic, physiologic and pharmacokinetic data through exposure to 1,3-Butadiene (BD) were collected in order to estimate the percentage of BD concentration metabolized at steady state, and to determine whether this percentage varies across gender, racial, and age groups. During the 20 min of continuous exposure to 2 parts per million (ppm) of BD, five measurements of exhaled concentration were made on each subject. In the following 40 min washout period, another five measurements were collected. A Bayesian hierarchical compartmental physiologically-based pharmacokinetic model (PKPB) was used. Using prior information on the model parameters, Markov Chain Monte Carlo (MCMC) simulation was conducted to obtain posterior distributions. The overall estimate of the mean percent of BD metabolized at steady state was 12.7% (95% credible interval: 7.7–17.8%). There was no significant difference in gender with males having a mean of 13.5%, and females 12.3%. Among the racial groups, Hispanic (13.9%), White (13.0%), Asian (12.1%), and Black (10.9%), the significant difference came from the difference between Black and Hispanic with a 95% credible interval from −5.63 to −0.30%. Those older than 30 years had a mean of 12.2% versus 12.9% for the younger group; although this was not a statistically significant difference. Given a constant inhalation input of 2 ppm, at steady state, the overall mean exhaled concentrationwas estimated to be 1.75ppm (95% credible interval: 1.64–1.84).An equivalent parameter, first-order metabolic rate constant, was also estimated and found to be consistent with the percent of BD metabolized at steady state across gender, race, and age strata

Properties of traditional bamboo carrying poles have implications for user interactions

Compliant bamboo poles have long been used for load carriage in Asian cultures. Although this custom differs from Western conventions of rigid body attachments (e.g. backpack), potential benefits include reduced peak shoulder forces as well as metabolic transport cost savings. Evidence that carrying a flexible pole benefits locomotion remains mixed, perhaps in part because the properties of pole design (e.g. bamboo material, structural geometry, etc.) have largely been neglected. These properties influence vibrational forces and consequently, the energy required by the user to manage the oscillations. We collected authentic bamboo poles from northern Vietnam and characterized their design parameters. Four poles were extensively studied in the lab (load-deflection testing, resonance testing, and computed tomography scans of three-dimensional geometry), and 10 others were tested at a rural Vietnamese farm site (basic measures of form and resonance). A mass-spring-damper model was used to characterize a relationship between resonant frequency (which affects the energetics of the pole-carrier system) and pole properties concerning stiffness, damping, etc. Model predictions of resonant frequencies agreed well with empirical data. Although measured properties suggest the poles are not optimally designed to reduce peak oscillation forces, resonant frequencies are within range of a typical human walking cadence, and this is likely to have a consequence on locomotion energetics

An Approximation Algorithm for the Matrix Tree Multiplication Problem

We consider the Matrix Tree Multiplication problem. This problem is a generalization of the classic Matrix Chain Multiplication problem covered in the dynamic programming chapter of many introductory algorithms textbooks. An instance of the Matrix Tree Multiplication problem consists of a rooted tree with a matrix associated with each edge. The output is, for each leaf in the tree, the product of the matrices on the chain/path from the root to that leaf. Matrix multiplications that are shared between various chains need only be computed once, potentially being shared between different root to leaf chains. Algorithms are evaluated by the number of scalar multiplications performed. Our main result is a linear time algorithm for which the number of scalar multiplications performed is at most 15 times the optimal number of scalar multiplications

A Vision- and Life-threatening Case of Peripheral Ulcerative Keratitis

Background: Peripheral ulcerative keratitis (PUK) is a rare but severe ocular manifestation most commonly associated with rheumatoid arthritis amongst other autoimmune diseases. Quick diagnosis and co-management with corneal specialist and rheumatologist are crucial to preserve vision and life. A rare case of PUK associated with rheumatoid arthritis (RA) is presented with updates on current understanding and co-management of this condition. Case Report: A 76 year-old Caucasian male presented to the eye clinic on a Friday as a new patient, with a chief complaint of a red right eye started two weeks ago and was treated with erythromycin ointment, but it got worse with moderate pain so he was referred over from the urgent care clinic. His BCVA OD, OS was 20/80 PHNI and PH20/25, respectively. Anterior segment evaluation showed severe conjunctival chemosis and injection, a superior temporal circular infiltrate and an inferior temporal linear infiltrate across the cornea with moderate corneal edema. Chart review confirmed the patient has been treated for rheumatoid arthritis with hydroxychloroquine and leflunomide for several years. The patient was diagnosed with PUK with mild scleritis associated with (RA) and initially treated with tobradex topical drops OD qid. His rheumatologist was contacted for co-management, and the patient was to return to clinic after the weekend. On the follow up visit, the patient felt better but the linear infiltrate persisted so oral prednisone 60mg/day was started with ofloxacin qid instead of Tobradex qid. The condition continued to improve over the next few follow up however the linear thinning of the cornea was not fully resolved so the patient was referred to a local corneal specialist. His rheumatologist continued to manage his RA closely and the patient confirmed that he was doing better overall at the latest visit. Conclusion: In cases of PUK with stromal thinning and scleritis, autoimmune diseases such as RA and systemic lupus erythema often are the underlying systemic cause. Prompt diagnosis and co-management with other specialists are essential to minimize irreversible vision loss and save lives

Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback

A key technology for the development of large language models (LLMs) involves instruction tuning that helps align the models' responses with human expectations to realize impressive learning abilities. Two major approaches for instruction tuning characterize supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF), which are currently applied to produce the best commercial LLMs (e.g., ChatGPT). To improve the accessibility of LLMs for research and development efforts, various instruction-tuned open-source LLMs have also been introduced recently, e.g., Alpaca, Vicuna, to name a few. However, existing open-source LLMs have only been instruction-tuned for English and a few popular languages, thus hindering their impacts and accessibility to many other languages in the world. Among a few very recent work to explore instruction tuning for LLMs in multiple languages, SFT has been used as the only approach to instruction-tune LLMs for multiple languages. This has left a significant gap for fine-tuned LLMs based on RLHF in diverse languages and raised important questions on how RLHF can boost the performance of multilingual instruction tuning. To overcome this issue, we present Okapi, the first system with instruction-tuned LLMs based on RLHF for multiple languages. Okapi introduces instruction and response-ranked data in 26 diverse languages to facilitate the experiments and development of future multilingual LLM research. We also present benchmark datasets to enable the evaluation of generative LLMs in multiple languages. Our experiments demonstrate the advantages of RLHF for multilingual instruction over SFT for different base models and datasets. Our framework and resources are released at https://github.com/nlp-uoregon/Okapi

The Effect of Manual Therapy on Muscle Stiffness in Healthy Individuals

The purpose of this study was to evaluate the immediate and delayed changes in muscle stiffness (in a resting and contracted state) related to DN of the gastrocnemius compared to a sham DN condition. To further investigate this relationship, we investigated these changes at the site of the TP, as well as at a standard site (medial head of the gastrocnemius). We hypothesize that gastrocnemius DN reduces muscle stiffness in individuals with TP

CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Along with the progress in natural language processing, LLMs have been frequently made accessible to the public to foster deeper investigation and applications. However, when it comes to training datasets for these LLMs, especially the recent state-of-the-art models, they are often not fully disclosed. Creating training data for high-performing LLMs involves extensive cleaning and deduplication to ensure the necessary level of quality. The lack of transparency for training data has thus hampered research on attributing and addressing hallucination and bias issues in LLMs, hindering replication efforts and further advancements in the community. These challenges become even more pronounced in multilingual learning scenarios, where the available multilingual text datasets are often inadequately collected and cleaned. Consequently, there is a lack of open-source and readily usable dataset to effectively train LLMs in multiple languages. To overcome this issue, we present CulturaX, a substantial multilingual dataset with 6.3 trillion tokens in 167 languages, tailored for LLM development. Our dataset undergoes meticulous cleaning and deduplication through a rigorous pipeline of multiple stages to accomplish the best quality for model training, including language identification, URL-based filtering, metric-based cleaning, document refinement, and data deduplication. CulturaX is fully released to the public in HuggingFace to facilitate research and advancements in multilingual LLMs: https://huggingface.co/datasets/uonlp/CulturaX.Comment: Ongoing Wor

Post-Acute Sequelae of COVID-19 (PASC) in Pediatrics: Factors That Impact Symptom Severity and Referral to Treatment.

The post-acute sequelae of COVID-19 (PASC) is a complex condition. While there are emerging studies on its effects in adults, there is scarce research regarding the long-term effects of COVID-19 infection among youth. Several researchers have likened long-haul COVID-19 to chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) and postural orthostatic tachycardia syndrome (POTS). In adults, the prognosis for these diagnoses is less promising than that in youth; however, there is currently very little information available on the presentation of youth with PASC. A better understanding of the specific symptom presentation for youth diagnosed with PASC is necessary. Retrospective chart reviews were conducted collecting demographic data, COVID-19 symptoms and disease progression, and vaccination status. Additional data on referrals to a PASC treatment program and appointments attended were collected. Overall, data suggested that youth present with less severe PASC symptoms than adults, and the role of vaccination is unclear. These youth are often not referred to treatment programs. More exploration is necessary to continue to build an understanding of how best to aid youth diagnosed with PASC