Hemoadsorption: Consensus report of the 30th Acute Disease Quality Initiative workgroup.

Adsorption-based extracorporeal therapies have been subject to technical developments and clinical application for close to five decades. More recently, new technological developments in membrane and sorbent manipulation have made it possible to deliver more biocompatible extracorporeal adsorption therapies to patients with a variety of conditions. There are several key rationales based on physicochemical principles and clinical considerations that justify the application and investigation of such therapies as evidenced by multiple ex-vivo, experimental, and clinical observations. Accordingly, unspecific adsorptive extracorporeal therapies have now been applied to the treatment of a wide array of conditions from poisoning to drug overdoses, to inflammatory states and sepsis, and acute or chronic liver and kidney failure. In response to the rapidly expanding knowledge base and increased clinical evidence, we convened an Acute Disease Quality Initiative (ADQI) consensus conference dedicated to such treatment. The data show that hemoadsorption has clinically acceptable short-term biocompatibility and safety, technical feasibility, and experimental demonstration of specified target molecule removal. Pilot studies demonstrate potentially beneficial effects on physiology and larger studies of endotoxin-based hemoadsorption have identified possible target phenotypes for larger randomized controlled trials (RCTs). Moreover, in a variety of endogenous and exogenous intoxications, removal of target molecules has been confirmed in vivo. However, some studies have raised concerns about harm or failed to deliver benefits. Thus, despite many achievements, modern hemoadsorption remains a novel and experimental intervention with limited data, and a large research agenda.

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study.

BACKGROUND: Although patients have easy access to their electronic health records and laboratory test result data through patient portals, laboratory test results are often confusing and hard to understand. Many patients turn to web-based forums or question-and-answer (Q&A) sites to seek advice from their peers. The quality of answers from social Q&A sites on health-related questions varies significantly, and not all responses are accurate or reliable. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to have their questions answered. OBJECTIVE: We aimed to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to laboratory test-related questions asked by patients and identify potential issues that can be mitigated using augmentation approaches. METHODS: We collected laboratory test result-related Q&A data from Yahoo! Answers and selected 53 Q&A pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from 5 LLMs: GPT-4, GPT-3.5, LLaMA 2, MedAlpaca, and ORCA_mini. We assessed the similarity of their answers using standard Q&A similarity-based evaluation metrics, including Recall-Oriented Understudy for Gisting Evaluation, Bilingual Evaluation Understudy, Metric for Evaluation of Translation With Explicit Ordering, and Bidirectional Encoder Representations from Transformers Score. We used an LLM-based evaluator to judge whether a target model had higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. We performed a manual evaluation with medical experts for all the responses to 7 selected questions on the same 4 aspects. RESULTS: Regarding the similarity of the responses from 4 LLMs; the GPT-4 output was used as the reference answer, the responses from GPT-3.5 were the most similar, followed by those from LLaMA 2, ORCA_mini, and MedAlpaca. Human answers from Yahoo data were scored the lowest and, thus, as the least similar to GPT-4-generated answers. The results of the win rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all 4 aspects (relevance, correctness, helpfulness, and safety). LLM responses occasionally also suffered from lack of interpretation in one's medical context, incorrect statements, and lack of references. CONCLUSIONS: By evaluating LLMs in generating responses to patients' laboratory test result-related questions, we found that, compared to other 4 LLMs and human answers from a Q&A website, GPT-4's responses were more accurate, helpful, relevant, and safer. There were cases in which GPT-4 responses were inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses, including prompt engineering, prompt augmentation, retrieval-augmented generation, and response evaluation.

Future proofing of chondroitin sulphate production: Importance of sustainability and quality for the end-applications.

Chondroitin sulphates (CSs) are the most well-known glycosaminoglycans (GAGs) found in any living organism, from microorganisms to invertebrates and vertebrates (including humans), and provide several health benefits. The applications of CSs are numerous including tissue engineering, osteoarthritis treatment, antiviral, cosmetics, and skincare applications. The current commercial production of CSs mostly uses animal, bovine, porcine, and avian tissues as well as marine organisms, marine mammals, sharks, and other fish. The production process consists of tissue hydrolysis, protein removal, and purification using various methods. Mostly, these are chemical-dependent and are complex, multi-step processes. There is a developing trend for abandonment of harsh extraction chemicals and their substitution with different green-extraction technologies, however, these are still in their infancy. The quality of CSs is the first and foremost requirement for end-applications and is dependent on the extraction and purification methodologies used. The final products will show different bio-functional properties, depending on their origin and production methodology. This is a comprehensive review of the characteristics, properties, uses, sources, and extraction methods of CSs. This review emphasises the need for extraction and purification processes to be environmentally friendly and gentle, followed by product analysis and quality control to ensure the expected bioactivity of CSs.

Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study.

Background: Even though patients have easy access to their electronic health records and lab test results data through patient portals, lab results are often confusing and hard to understand. Many patients turn to online forums or question and answering (Q&A) sites to seek advice from their peers. However, the quality of answers from social Q&A on health-related questions varies significantly, and not all the responses are accurate or reliable. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. Objective: We aim to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to lab test-related questions asked by patients and to identify potential issues that can be mitigated with augmentation approaches. Methods: We first collected lab test results related question and answer data from Yahoo! Answers and selected 53 Q&A pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from four LLMs including GPT-4, Meta LLaMA 2, MedAlpaca, and ORCA_mini. We first assessed the similarity of their answers using standard QA similarity-based evaluation metrics including ROUGE, BLEU, METEOR, BERTScore. We also utilized an LLM-based evaluator to judge whether a target model has higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. Finally, we performed a manual evaluation with medical experts for all the responses of seven selected questions on the same four aspects. Results: Regarding the similarity of the responses from 4 LLMs, where GPT-4 output was used as the reference answer, the responses from LLaMa 2 are the most similar ones, followed by LLaMa 2, ORCA_mini, and MedAlpaca. Human answers from Yahoo data were scored lowest and thus least similar to GPT-4-generated answers. The results of Win Rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all the four aspects (relevance, correctness, helpfulness, and safety). However, LLM responses occasionally also suffer from lack of interpretation in one's medical context, incorrect statements, and lack of references. Conclusions: By evaluating LLMs in generating responses to patients' lab test results related questions, we find that compared to other three LLMs and human answer from the Q&A website, GPT-4's responses are more accurate, helpful, relevant, and safer. However, there are cases that GPT-4 responses are inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses including prompt engineering, prompt augmentation, retrieval augmented generation, and response evaluation.

Phase-3 trial of recombinant human alkaline phosphatase for patients with sepsis-associated acute kidney injury (REVIVAL).

PURPOSE: Ilofotase alfa is a human recombinant alkaline phosphatase with reno-protective effects that showed improved survival and reduced Major Adverse Kidney Events by 90 days (MAKE90) in sepsis-associated acute kidney injury (SA-AKI) patients. REVIVAL, was a phase-3 trial conducted to confirm its efficacy and safety. METHODS: In this international double-blinded randomized-controlled trial, SA-AKI patients were enrolled < 72 h on vasopressor and < 24 h of AKI. The primary endpoint was 28-day all-cause mortality. The main secondary endpoint was MAKE90, other secondary endpoints were (i) days alive and free of organ support through day 28, (ii) days alive and out of the intensive care unit (ICU) through day 28, and (iii) time to death through day 90. Prior to unblinding, the statistical analysis plan was amended, including an updated MAKE90 definition. RESULTS: Six hundred fifty patients were treated and analyzed for safety; and 649 for efficacy data (ilofotase alfa n = 330; placebo n = 319). The observed mortality rates in the ilofotase alfa and placebo groups were 27.9% and 27.9% at 28 days, and 33.9% and 34.8% at 90 days. The trial was stopped for futility on the primary endpoint. The observed proportion of patients with MAKE90A and MAKE90B were 56.7% and 37.4% in the ilofotase alfa group vs. 64.6% and 42.8% in the placebo group. Median [interquartile range (IQR)] days alive and free of organ support were 17 [0-24] and 14 [0-24], number of days alive and discharged from the ICU through day 28 were 15 [0-22] and 10 [0-22] in the ilofotase alfa and placebo groups, respectively. Adverse events were reported in 67.9% and 75% patients in the ilofotase and placebo group. CONCLUSION: Among critically ill patients with SA-AKI, ilofotase alfa did not improve day 28 survival. There may, however, be reduced MAKE90 events. No safety concerns were identified.

Recommendations for clinical trial design in acute kidney injury from the 31st acute disease quality initiative consensus conference. A consensus statement.

PURPOSE: Novel interventions for the prevention or treatment of acute kidney injury (AKI) are currently lacking. To facilitate the evaluation and adoption of new treatments, the use of the most appropriate design and endpoints for clinical trials in AKI is critical and yet there is little consensus regarding these issues. We aimed to develop recommendations on endpoints and trial design for studies of AKI prevention and treatment interventions based on existing data and expert consensus. METHODS: At the 31st Acute Disease Quality Initiative (ADQI) meeting, international experts in critical care, nephrology, involving adults and pediatrics, biostatistics and people with lived experience (PWLE) were assembled. We focused on four main areas: (1) patient enrichment strategies, (2) prevention and attenuation studies, (3) treatment studies, and (4) innovative trial designs of studies other than traditional (parallel arm or cluster) randomized controlled trials. Using a modified Delphi process, recommendations and consensus statements were developed based on existing data, with > 90% agreement among panel members required for final adoption. RESULTS: The panel developed 12 consensus statements for clinical trial endpoints, application of enrichment strategies where appropriate, and inclusion of PWLE to inform trial designs. Innovative trial designs were also considered. CONCLUSION: The current lack of specific therapy for prevention or treatment of AKI demands refinement of future clinical trial design. Here we report the consensus findings of the 31st ADQI group meeting which has attempted to address these issues including the use of predictive and prognostic enrichment strategies to enable appropriate patient selection.

Exploring Microorganisms from Plastic-Polluted Sites: Unveiling Plastic Degradation and PHA Production Potential.

The exposure of microorganisms to conventional plastics is a relatively recent occurrence, affording limited time for evolutionary adaptation. As part of the EU-funded project BioICEP, this study delves into the plastic degradation potential of microorganisms isolated from sites with prolonged plastic pollution, such as plastic-polluted forests, biopolymer-contaminated soil, oil-contaminated soil, municipal landfill, but also a distinctive soil sample with plastic pieces buried three decades ago. Additionally, samples from Arthropoda species were investigated. In total, 150 strains were isolated and screened for the ability to use plastic-related substrates (Impranil dispersions, polyethylene terephthalate, terephthalic acid, and bis(2-hydroxyethyl) terephthalate). Twenty isolates selected based on their ability to grow on various substrates were identified as Streptomyces, Bacillus, Enterococcus, and Pseudomonas spp. Morphological features were recorded, and the 16S rRNA sequence was employed to construct a phylogenetic tree. Subsequent assessments unveiled that 5 out of the 20 strains displayed the capability to produce polyhydroxyalkanoates, utilizing pre-treated post-consumer PET samples. With Priestia sp. DG69 and Neobacillus sp. DG40 emerging as the most successful producers (4.14% and 3.34% of PHA, respectively), these strains are poised for further utilization in upcycling purposes, laying the foundation for the development of sustainable strategies for plastic waste management.