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Background: End-of-life care (EOLC) is a critical aspect of healthcare, yet accessing reliable information remains challenging, particularly in culturally diverse contexts like India. Objective: This study investigates the potential of artificial intelligence (AI) in addressing the informational gap by analyzing patient information leaflets (PILs) generated by AI chatbots on EOLC. Methodology: Using a comparative research design, PILs generated by ChatGPT and Google Gemini were evaluated for readability, sentiment, accuracy, completeness, and suitability. Readability was assessed using established metrics, sentiment analysis determined emotional tone, accuracy, and completeness were rated by subject experts, and suitability was evaluated using the Patient Education Materials Assessment Tool (PEMAT). Results: Google Gemini PILs exhibited superior readability and actionability compared to ChatGPT PILs. Both conveyed positive sentiments and high levels of accuracy and completeness, with Google Gemini PILs showing slightly lower accuracy scores. Conclusion: The findings highlight the promising role of AI in enhancing patient education in EOLC, with implications for improving care outcomes and promoting informed decision-making in diverse cultural settings. Ongoing refinement and innovation in AI-driven patient education strategies are needed to ensure compassionate and culturally sensitive EOLC. How to cite this article: Gondode PG, Khanna P, Sharma P, Duggal S, Garg N. End-of-life Care Patient Information Leaflets-A Comparative Evaluation of Artificial Intelligence-generated Content for Readability, Sentiment, Accuracy, Completeness, and Suitability: ChatGPT vs Google Gemini. Indian J Crit Care Med 2024;28(6):561-568.
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This article describes intracellular zinc-induced excimer emission and tuning of self-assembly from L-tryptophan-pyrene conjugate (1). The zinc-guided excimer formation is due to the interaction of the pyrene moiety in an excited state. AFM studies show the structural modification in the supramolecular nano-assembly of 1 from dome-shaped to porous surface after complexation with zinc ions. Further, the interaction of 1 with Zn(II) ion is also studied using DFT, Job's plot, NMR titration and HRMS. The results of Zn(II) ion determination in natural water samples and RAW 264.7 cells demonstrate the practical utility of 1.
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Solving certain combinatorial optimization problems like Max-Cut becomes challenging once the graph size and edge connectivity increase beyond a threshold, with brute-force algorithms which solve such problems exactly on conventional digital computers having the bottleneck of exponential time complexity. Hence currently, such problems are instead solved approximately using algorithms like Goemans-Williamson (GW) algorithm, run on conventional computers with polynomial time complexity. Phase binarized oscillators (PBOs), also often known as oscillator Ising machines (OIM), have been proposed as an alternative to solve such problems. In this paper, restricting ourselves to the combinatorial optimization problem Max-Cut solved on three kinds of graphs (Mobius Ladder, random cubic, Erdos Renyi) up to 100 nodes, we empirically show that computation time/ time to solution (TTS) for PBOs (captured through Kuramoto model) grows at a much lower rate (logarithmically: O(log(N)), with respect to graph size N) compared to GW algorithm, for which TTS increases as square of graph size (O(N2). However, Kuramoto model being a physics-agnostic mathematical model, this time complexity/ TTS trend for PBOs is a general trend and is device-physics agnostic. So for more specific results, we choose spintronic oscillators, known for their high operating frequency (in GHz), and model them through Slavin's model which captures the physics of their coupled magnetization oscillation dynamics. We thereby empirically show that TTS of spintronic oscillators also grows logarithmically with graph size (O(log(N)), while their accuracy is comparable to that of GW. So spintronic oscillators have improved time complexity over GW algorithm. For large graphs, they are expected to compute Max-Cut values much faster than GW algorithm, as well as other oscillators operating at lower frequencies, while maintaining the same level of accuracy. .
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BACKGROUND: Transoral robotic surgery (TORS) lingual tonsillectomy and hypoglossal nerve stimulation (HGNS) are effective surgical interventions for well-selected patients with obstructive sleep apnea (OSA) intolerant to continuous positive airway pressure (CPAP) therapy. Previous publications have demonstrated that HGNS patients have a lower postoperative apnea-hypopnea index (AHI) and length of hospital stay than TORS patients. No prior study has investigated the differences in costs between HGNS and TORS. OBJECTIVES: This study aims to compare surgery-related costs in patients undergoing HGNS versus TORS lingual tonsillectomy for OSA intolerant to CPAP. METHODS: A retrospective study on OSA patients intolerant to CPAP that underwent HGNS or TORS from 2015 to 2022 at a tertiary care center. Cost was defined as the dollar amount associated with providing a specific service prior to the application of insurance. RESULTS: This study included 395 patients (375 UAS and 20 TORS). Average total cost was significantly higher in the UAS group than the TORS group (UAS: $25,582.60; TORS: $5832.60; p < 0.001). Operating room costs were also significantly higher in the UAS group (UAS: $1978.20; TORS: $1490.90; p = 0.001). The TORS cohort averaged higher costs for pharmacy (UAS: $201.30; TORS: $416.60; p < 0.001) and anesthesia (UAS: $139.00; TORS: $307.60; p < 0.001). DISCUSSION: The total cost was significantly higher in the UAS group compared to the TORS group. When making management decisions, it is important to consider the cost of care provided as well as patient-centered outcomes to optimize the value of care. LEVEL OF EVIDENCE: N/A Laryngoscope, 2024.
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Background: Viscoelastic tests are now routinely used for coagulopathy correction in patients with cirrhosis. Thromboelastography (TEG®) and rotational thromboelastometry (RoTEM®) are the most widely studied tests in this population. However, they have not been compared with each other in critically ill patients with liver disease presenting with nonvariceal bleed. Hence, we aimed to compare these tests for coagulopathy correction in patients with liver disease presenting with nonvariceal bleeding. Methods: Sixty adult patients with liver cirrhosis presented to the liver intensive care unit, presenting with a nonvariceal upper gastrointestinal (GI) bleed (diagnosed by doing upper GI endoscopy which revealed bleeding from a nonvariceal source) oral or nasal bleed were enrolled. The patients were allocated to the TEG® group (Group T) or RoTEM® group (Group R) depending on the immediate availability of the viscoelastic test. Coagulopathy correction was done in each group as per established protocols and the results were compared. Results: There was a significant difference in the fresh frozen plasma (FFP) transfusion between the groups. The TEG® group received more FFP when compared to the RoTEM® group (P = 0.001). Conclusion: RoTEM®-based coagulopathy correction leads to lesser use of blood products with similar control of bleeding when compared to TEG, in critically ill patients with cirrhosis.
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Background and Aims: Artificial intelligence (AI) chatbots like Conversational Generative Pre-trained Transformer (ChatGPT) have recently created much buzz, especially regarding patient education. Such informed patients understand and adhere to the management and get involved in shared decision making. The accuracy and understandability of the generated educational material are prime concerns. Thus, we compared ChatGPT with traditional patient information leaflets (PILs) about chronic pain medications. Methods: Patients' frequently asked questions were generated from PILs available on the official websites of the British Pain Society (BPS) and the Faculty of Pain Medicine. Eight blinded annexures were prepared for evaluation, consisting of traditional PILs from the BPS and AI-generated patient information materials structured similar to PILs by ChatGPT. The authors performed a comparative analysis to assess materials' readability, emotional tone, accuracy, actionability, and understandability. Readability was measured using Flesch Reading Ease (FRE), Gunning Fog Index (GFI), and Flesch-Kincaid Grade Level (FKGL). Sentiment analysis determined emotional tone. An expert panel evaluated accuracy and completeness. Actionability and understandability were assessed with the Patient Education Materials Assessment Tool. Results: Traditional PILs generally exhibited higher readability (P values < 0.05), with [mean (standard deviation)] FRE [62.25 (1.6) versus 48 (3.7)], GFI [11.85 (0.9) versus 13.65 (0.7)], and FKGL [8.33 (0.5) versus 10.23 (0.5)] but varied emotional tones, often negative, compared to more positive sentiments in ChatGPT-generated texts. Accuracy and completeness did not significantly differ between the two. Actionability and understandability scores were comparable. Conclusion: While AI chatbots offer efficient information delivery, ensuring accuracy and readability, patient-centeredness remains crucial. It is imperative to balance innovation with evidence-based practice.
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Background: ChatGPT and Google Bard™ are popular artificial intelligence chatbots with utility for patients, including those undergoing aesthetic facial plastic surgery. Objective: To compare the accuracy and readability of chatbot-generated responses to patient education questions regarding aesthetic facial plastic surgery using a response accuracy scale and readability testing. Method: ChatGPT and Google Bard™ were asked 28 identical questions using four prompts: none, patient friendly, eighth-grade level, and references. Accuracy was assessed using Global Quality Scale (range: 1-5). Flesch-Kincaid grade level was calculated, and chatbot-provided references were analyzed for veracity. Results: Although 59.8% of responses were good quality (Global Quality Scale ≥4), ChatGPT generated more accurate responses than Google Bard™ on patient-friendly prompting (p < 0.001). Google Bard™ responses were of a significantly lower grade level than ChatGPT for all prompts (p < 0.05). Despite eighth-grade prompting, response grade level for both chatbots was high: ChatGPT (10.5 ± 1.8) and Google Bard™ (9.6 ± 1.3). Prompting for references yielded 108/108 of chatbot-generated references. Forty-one (38.0%) citations were legitimate. Twenty (18.5%) provided accurately reported information from the reference. Conclusion: Although ChatGPT produced more accurate responses and at a higher education level than Google Bard™, both chatbots provided responses above recommended grade levels for patients and failed to provide accurate references.
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Pseudopeptides are emerging next-generation soft bioinspired materials for biological applications. Therefore, a new class of C2-symmetric L-valine-derived pseudopeptides has been designed and developed. The newly developed pseudopeptides exhibit intracellular Cu(II) ion detection in live-cell fluorescence studies on RAW264.7 cells. We find that the changes in the amino acid side chain in desired pseudopeptidic moieties lead to a drastic change in their selectivity towards different metal ions. The L-valine-derived pseudopeptides exhibit selectivity towards Cu(II) ions through turn-off fluorescence, and the L-phenylalanine-derived pseudopeptides exhibit selectivity towards Zn(II) ions through turn-on fluorescence. In addition, the L-valine-derived pseudopeptides show an increase in spherical-shaped structures upon incubation with Cu(II) ions during supramolecular nano-assembly formation. In contrast, the L-phenylalanine-derived pseudopeptides show a decrease in spherical-shaped structures upon adding Zn(II) ions. The judiciously designed L-valine-derived and L-phenylalanine-derived bioinspired pseudopeptides are promising for exploring similar effects in various peptidomimetics in advanced biological applications.
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Copper , Peptides , Copper/chemistry , Mice , Animals , Peptides/chemistry , Peptides/chemical synthesis , Nanostructures/chemistry , RAW 264.7 Cells , Phenylalanine/chemistry , Valine/chemistryABSTRACT
This paper considers the problem of estimation of the population total under probability proportional to size (PPS) sampling scheme when complete data is not available due to the presence of missing observations or non-response. The suggested estimators are developed based on available multi-auxiliary information for the response group and non-response group utilizing the calibration approach. The variances of the suggested estimators have been derived up to the first order of approximation. A simulation study done on a real dataset using R software also supports the performance of the suggested estimators. The empirical percentage absolute relative biases (%ARB) and percentage relative root mean squared errors (%RRMSE) are computed for the suggested estimators. The developed estimators are compared with the estimators of the population total due to the design-based Horvitz and Thompson (HT) estimator and calibration HT type estimator obtained on the available complete response units along with the design-based Hansen and Hurwitz (HH) estimator in the presence of non-response.
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The recycling of spent lithium-ion batteries (LIBs) is crucial to sustainably manage resources and protect the environment as the use of portable electronics and electric vehicles (EVs) increases. However, the safe recycling of spent LIBs is challenging, as they often contain residual energy. Left untreated, this can trigger a thermal runaway and result in disasters during the recycling process. For efficient recycling, it is important to withdraw any leftover energy from LIBs, regardless of the processing method that follows the discharge. The electrochemical discharge method is a quick and inexpensive method to eliminate this hazard. This method works by immersing batteries in an aqueous inorganic salt solution to discharge LIBs completely and efficiently. Previously, research focus has been on different inorganic salt solutions that release toxic or flammable gaseous products during discharge. In contrast, we present an entirely new approach for electrochemical discharge - the utilization of an Fe(ii)-Fe(iii) redox couple electrolyte. We show that this medium can be used for efficient LIB deep discharge to a voltage of 2.0 V after rebound, a level that is low enough for safe discharge. To accomplish this, periodic discharge methods were used. In addition, no corrosion on the battery casing was observed. The pH behavior at the poles was also investigated, and it was found that without convection, gas evolution during discharge cannot be avoided. Finally, it was discovered that the battery casing material plays a vital role in electrochemical discharge, and its industrial standardization would facilitate efficient recycling.
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Untargeted tandem mass spectrometry (MS/MS) has become a high-throughput method to measure small molecules in complex samples. One key goal is the transformation of these MS/MS spectra into chemical structures. Computational techniques such as MS/MS library search have enabled the reidentification of known compounds. Analog library search and molecular networking extend this identification to unknown compounds. While there have been advancements in metrics for the similarity of MS/MS spectra of structurally similar compounds, there is still a lack of automated methods to provide site specific information about structural modifications. Here we introduce ModiFinder which leverages the alignment of peaks in MS/MS spectra between structurally related known and unknown small molecules. Specifically, ModiFinder focuses on shifted MS/MS fragment peaks in the MS/MS alignment. These shifted peaks putatively represent substructures of the known molecule that contain the site of the modification. ModiFinder synthesizes this information together and scores the likelihood for each atom in the known molecule to be the modification site. We demonstrate in this manuscript how ModiFinder can effectively localize modifications which extends the capabilities of MS/MS analog searching and molecular networking to accelerate the discovery of novel compounds.
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The role of noncoding RNA has made remarkable progress in understanding progression, metastasis, and metastatic castration-resistant prostate cancer (mCRPC). A better understanding of the miRNAs has enhanced our knowledge of their targeting mainly at the therapy level in solid tumors, such as prostate cancer (PCa). microRNAs (miRNAs) belong to a class of endogenous RNA that deficit encoded proteins. Therefore, the role of miRNAs has been well-coined in the progression and development of PCa. miR-21 has a dual nature in its work both as a tumor suppressor and oncogenic role, but most of the recent studies showed that miR-21 is a tumor promoter and also is involved in castration-resistant prostate cancer (CRPC). Upregulation of miR-21 suppresses programmed cell death and inducing metastasis and castration resistant in PCa. miR-21 is involved in the different stages, such as proliferation, angiogenesis, migration, and invasion, and plays an important role in the progression, metastasis, and advanced stages of PCa. Recently, various studies directly linked the role of high levels of miR-21 with a poor therapeutic response in the patient of PCa. In the present review, we have explained the molecular mechanisms/pathways of miR-21 in PCa progression, metastasis, and castration resistant and summarized the role of miR-21 in diagnosis and therapeutic levels in PCa. In addition, we have spotlighted the recent therapeutic strategies for targeting different stages of PCa.
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Disease Progression , MicroRNAs , Prostatic Neoplasms , Humans , MicroRNAs/genetics , Male , Prostatic Neoplasms/pathology , Prostatic Neoplasms/genetics , Prostatic Neoplasms/metabolism , Prostatic Neoplasms, Castration-Resistant/pathology , Prostatic Neoplasms, Castration-Resistant/genetics , Prostatic Neoplasms, Castration-Resistant/metabolism , Neoplasm Metastasis , Gene Expression Regulation, Neoplastic , PrognosisABSTRACT
The existence of measurement errors cannot be avoided in practice. It is a prominent fact that the existence of measurement errors diminishes conventional properties of the estimators. A modified correlated measurement errors model has been proposed. Shalabh and Tsai (Commun Stat Simul Comput 46(7):5566-5593. 10.1080/03610918.2016.1165845, 2017) correlated measurement errors model is a particular member of the suggested modified model. In this article, we have tackled the estimation of population mean utilizing auxiliary information under modified correlated measurement errors model. We have developed ratio and product estimators and studied their properties in case of simple random sampling without replacement (SRSWOR) up to first order of approximation. It has been illustrated that suggested ratio and product estimators are more efficient than the conventional unbiased estimator as well as Shalabh and Tsai (Commun Stat Simul Comput 46(7):5566-5593. 10.1080/03610918.2016.1165845, 2017) ratio and product estimators under very realistic situations. An empirical study has also been performed to demonstrate the merits of the recommended estimators over other estimators.
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Ferroptosis is a novel type of controlled cell death resulting from an imbalance between oxidative harm and protective mechanisms, demonstrating significant potential in combating cancer. It differs from other forms of cell death, such as apoptosis and necrosis. Molecular therapeutics have hard time playing the long-acting role of ferroptosis induction due to their limited water solubility, low cell targeting capacity, and quick metabolism in vivo. To this end, small molecule inducers based on biological factors have long been used as strategy to induce cell death. Research into ferroptosis and advancements in nanotechnology have led to the discovery that nanomaterials are superior to biological medications in triggering ferroptosis. Nanomaterials derived from iron can enhance ferroptosis induction by directly releasing large quantities of iron and increasing cell ROS levels. Moreover, utilizing nanomaterials to promote programmed cell death minimizes the probability of unfavorable effects induced by mutations in cancer-associated genes such as RAS and TP53. Taken together, this review summarizes the molecular mechanisms involved in ferroptosis along with the classification of ferroptosis induction. It also emphasized the importance of cell organelles in the control of ferroptosis in cancer therapy. The nanomaterials that trigger ferroptosis are categorized and explained. Iron-based and noniron-based nanomaterials with their characterization at the molecular and cellular levels have been explored, which will be useful for inducing ferroptosis that leads to reduced tumor growth. Within this framework, we offer a synopsis, which traverses the well-established mechanism of ferroptosis and offers practical suggestions for the design and therapeutic use of nanomaterials.
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Ferroptosis , Nanostructures , Neoplasms , Ferroptosis/drug effects , Humans , Neoplasms/drug therapy , Neoplasms/pathology , Neoplasms/metabolism , Animals , Molecular Dynamics Simulation , Iron/metabolism , Antineoplastic Agents/pharmacology , Antineoplastic Agents/therapeutic use , Reactive Oxygen Species/metabolismABSTRACT
OBJECTIVE: Assess the safety of ambulatory surgery performed for obstructive sleep apnea. STUDY DESIGN: Retrospective chart review. SETTING: Tertiary care hospital. METHODS: Demographic data including age, gender, race, body mass index, insurance status, socioeconomic status, and distance traveled for surgery was collected, as well as comorbidities, and apnea-hypopnea index (AHI). Outcome variables included continuous positive airway pressure reinitiation, planned/unplanned postoperative admission, emergency department (ED) presentation, or readmission within 7 and 14 days of surgery. RESULTS: A total of 601 patients were included, who underwent sleep surgery between 2017 and 2022. The median age was 55 years [interquartile range: 19]. A total of 437 patients (73%) were male, 502 (84%) were Caucasian, and the median distance traveled was 20 miles [27]. The median AHI was 27.1 [26]. A total of 286 hypoglossal nerve stimulators, 12 tonsillectomies, 160 expansion sphincteroplasties (ESP), and 201 nasal procedures were performed. There were 9 (1%) planned and 23 (4%) total admissions postoperatively. Sixteen patients (2%) presented to ED within 7 days, and 22 (3%) within 14 days. Nine (1%) were readmitted within 7 days, and 12 (2%) within 14 days. There were significantly more planned admissions, unplanned admissions, ED presentations, and readmissions for ESP. There were no significant differences in demographic or clinical data between patients who underwent single versus multiple surgeries. CONCLUSION: Outpatient sleep surgery is generally safe. Close postoperative monitoring is necessary and overnight observation should be considered in those with very severe sleep apnea and/or significant comorbidities. The distance a patient travels should also be considered for overnight admission.
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Ambulatory Surgical Procedures , Sleep Apnea, Obstructive , Humans , Sleep Apnea, Obstructive/surgery , Male , Retrospective Studies , Middle Aged , Female , Patient Safety , Adult , Postoperative Complications/epidemiology , Patient Readmission/statistics & numerical data , AgedABSTRACT
KEY POINTS: Silent sinus syndrome (SSS) and chronic maxillary atelectasis (CMA) represent an overlapping clinical entity, both likely lying on the spectrum of one disease process. There is widespread inconsistency of diagnosis in the literature of reported cases of SSS and CMA. We propose a novel, comprehensive staging system to simplify diagnosis and inform management.
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Maxillary Sinus , Humans , Chronic Disease , Maxillary Sinus/pathology , Syndrome , Paranasal Sinus Diseases/pathology , Paranasal Sinus Diseases/diagnosis , Male , Female , Middle AgedABSTRACT
An Adaptive activation Functions with Deep Kronecker Neural Network optimized with Bear Smell Search Algorithm (BSSA) (ADKNN-BSSA-CSMANET) is proposed for preventing MANET Cyber security attacks. The mobile users are enrolled with Trusted Authority Using a Crypto Hash Signature (SHA-256). Every mobile user uploads their finger vein biometric, user ID, latitude and longitude for confirmation. The packet analyser checks if any attack patterns are identified. It is implemented using adaptive density-based spatial clustering (ADSC) that deems information from packet header. Geodesic filtering (GF) is used as a pre-processing method for eradicating the unsolicited content and filtering pertinent data. Group Teaching Algorithm (GTA)-based feature selection is utilized for ideal collection of features and Adaptive Activation Functions along Deep Kronecker Neural Network (ADKNN) is used to categorizing normal and attack packets (DoS, Probe, U2R, and R2L). Then BSSA is utilized for optimizing the weight parameters of ADKNN classifier for optimal classification. The proposed technique is executed in python and its efficiency is evaluated by several performances metrics, such as Accuracy, Attack Detection Rate, Detection Delay, Packet Delivery Ratio, Throughput, and Energy Consumption. The proposed technique provides 36.64%, 33.06%, and 33.98% lower Detection Delay on NSL-KDD dataset compared with the existing methods.