Use of Machine Learning to Predict Onset of NAFLD in an All-Comers Cohort-Development and Validation in 2 Large Asian Cohorts.

Background and Aims: Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases. There are no universally accepted models that accurately predict time to onset of NAFLD. Machine learning (ML) models may allow prediction of such time-to-event (ie, survival) outcomes. This study aims to develop and independently validate ML-derived models to allow personalized prediction of time to onset of NAFLD in individuals who have no NAFLD at baseline. Methods: The development dataset comprised 25,599 individuals from a South Korean NAFLD registry. A random 70:30 split divided it into training and internal validation sets. ML survival models (random survival forest, extra survival trees) were fitted, with time to NAFLD diagnosis in months as the target variable and routine anthropometric and laboratory parameters as predictors. The independent validation dataset comprised 16,173 individuals from a Chinese open dataset. Models were evaluated using the concordance index (c-index) and Brier score on both the internal and independent validation sets. Results: The datasets (development vs independent validation) had 1,331,107 vs 543,874 person months of follow-up, NAFLD incidence of 25.7% (6584 individuals) vs 14.4% (2322 individuals), and median time to NAFLD onset of 60 (interquartile range 38-75) vs 24 (interquartile range 13-37) months, respectively. The ML models achieved a good c-index of >0.7 in the validation cohort-random survival forest 0.751 (95% confidence interval 0.742-0.759), extra survival trees 0.752 (95% confidence interval 0.744-0.762). Conclusion: ML models can predict time-to-onset of NAFLD based on routine patient data. They can be used by clinicians to deliver personalized predictions to patients, which may facilitate patient counseling and clinical decision making on interval imaging timing.

Targeted aggregation of PETase towards surface of Stenotrophomonas pavanii for degradation of PET microplastics.

Polyethylene terephthalate (PET) is one of the most widely used plastics, but its fragmentation into microplastics poses significant environmental challenges. The recycling of PET microplastics is hindered by their low solubility and widespread dispersion in the environment, making microbial in-situ degradation a promising solution. However, existing PET-degrading strains exhibited the limited effectiveness, primarily due to the diffusion of secreted hydrolases away from the PET surface. In this study, Stenotrophomonas pavanii JWG-G1 was engineered to achieve the targeted aggregation of PET hydrolase PETase on the cell surface by fusing it with an endogenous anchor protein. This approach aims to maximise the local concentration of PETase around PET, thereby increasing the overall rate of PET degradation. The PETase surface-aggregated system, S. pavanii/PaL-PETase, demonstrated the highest degradation efficiency, achieving 63.3 % degradation of low-crystallinity PET (lcPET) and 27.3 % degradation of high-crystallinity PET bottles (hcPET) at 30 °C. This represents the highest degradation rate reported for a displayed whole-cell system at ambient temperature. Furthermore, this system exhibited broad-spectrum degradation activity against various polyesters. These findings suggest that this system offers a promising, eco-friendly solution to PET and other polyester pollution, with potential implications for environmental bioremediation strategies.

Preclinical Evaluation of STI-8811, a Novel Antibody Drug Conjugate Targeting BCMA for the Treatment of Multiple Myeloma.

Treatment for patients with Multiple Myeloma (MM) has experienced rapid development and improvement in recent years, however, patients continue to experience relapse and MM remains largely incurable. B cell maturation antigen (BCMA) has been widely recognized as a promising target for treatment of MM due to its exclusive expression in B cell linage cells and its critical role in the growth and survival of malignant plasma cells. Here, we introduce STI-8811, a BCMA-targeting antibody drug conjugate linked to an auristatin-derived duostatin payload via an enzymatically cleavable peptide linker, using our proprietary C-lock technology. STI-8811 exhibits target specific binding activity and rapid internalization, leading to G2/M cell cycle arrest, caspase 3/7 activation and apoptosis in BCMA-expressing tumor cells in vitro. Soluble BCMA (sBCMA) is shed by MM cells into the blood and increases with disease progression, competing for ADC binding and reducing its efficacy. We report enhanced cytotoxic activity in the presence of high levels of sBCMA compared to a belantamab mafodotin biosimilar (J6M0-mcMMAF). STI-8811 demonstrated greater in vivo activity than J6M0-mcMMAF in solid and disseminated multiple myeloma models, including tumor models with low BCMA expression and/or in large solid tumors representing soft tissue plasmacytomas. In Cynomolgus monkeys, STI-8811 was well tolerated, with toxicities consistent with other BCMA targeting ADCs with auristatin payloads in clinical studies. STI-8811 has the potential to outperform current clinical candidates with lower toxicity and higher activity under conditions found in patients with advanced disease.

Anti-liver cancer effects and mechanisms and its application in nano DDS of polysaccharides: A review.

Liver cancer is the third leading cause of cancer death, with high incidence and poor treatment effect. In recent years, polysaccharides have attracted more and more attention in the research field of anti-liver cancer because of their high efficiency, low toxicity, good biocompatibility, wide sources and low cost. Polysaccharides have been proven to have good anti-liver cancer activity. In this paper, the pathways and molecular mechanisms of polysaccharides against liver cancer were reviewed in detail. Polysaccharides exert anti-liver cancer activity by blocking cell cycle, inducing apoptosis, regulating immunity, inhibiting cancer cell metastasis, inhibiting tumor angiogenesis and so on. The primary structure and chain conformation of polysaccharides have an important influence on their anti-liver cancer activity. Structural modification enhanced the anti-liver cancer activity of polysaccharides. Polysaccharides have good attenuated and synergistic effects on chemotherapy drugs. Polysaccharides can be used as functional carriers to construct intelligent nano drug delivery systems (DDS) targeting liver cancer. This review can provide theoretical support for the further development and application of polysaccharides in the field of anti-liver cancer, and provide theoretical reference and clues for relevant researchers in food, nutrition, medicine and other fields.

Establishing a nomogram for predicting necrotizing enterocolitis in premature infants: A retrospective multicenter cohort study.

BACKGROUND: To construct a nomogram for predicting necrotizing enterocolitis (NEC) in preterm infants. METHODS: A total of 4,724 preterm infants who were admitted into 8 hospitals between April 2019 and September 2020 were initially enrolled this retrospective multicenter cohort study. Finally, 1,092 eligible cases were divided into training set and test set based on a 7:3 ratio. A univariate logistic regression analysis was performed to compare the variables between the two groups. Stepwise backward regression, LASSO regression, and Boruta feature selection were utilized in the multivariate analysis to identify independent risk factors. Then a nomogram model was constructed based on the identified risk factors. RESULTS: Risk factors for NEC included gestational diabetes mellitus, gestational age, small for gestational age, patent ductus arteriosus, septicemia, red blood cell transfusion, intravenous immunoglobulin, severe feeding intolerance, and absence of breastfeeding. The nomogram model developed based on these factors showed well discriminative ability. Calibration and decision curve analysis curves confirmed the good consistency and clinical utility of the model. CONCLUSIONS: We developed a nomogram model with strong discriminative ability, consistency, and clinical utility for predicting NEC. This model could be valuable for the early prediction of preterm infants at risk of developing NEC.

Gubi decoction mitigates knee osteoarthritis via promoting chondrocyte autophagy through METTL3-mediated ATG7 m6A methylation.

Knee osteoarthritis (KOA) is a chronic joint disease that significantly affects the health of the elderly. As an herbal remedy, Gubi decoction (GBD) has been traditionally used for the treatment of osteoarthritis-related syndromes. However, the anti-KOA efficacy and mechanism of GBD remain unclear. This study aimed to experimentally investigate the anti-KOA efficacy and the underlying mechanism of GBD. The medial meniscus (DMM) mice model and IL-1ß-stimulated chondrocytes were, respectively, constructed as in vivo and in vitro models of KOA to evaluate the osteoprotective effect and molecular mechanism of GBD. The UPLC-MS/MS analysis showed that GBD mainly contained pinoresinol diglucoside, rehmannioside D, hesperidin, liquiritin, baohuoside I, glycyrrhizic acid, kaempferol and tangeretin. Animal experiment showed that GBD could alleviate articular cartilage destruction and recover histopathological alterations in DMM mice. In addition, GBD inhibited chondrocyte apoptosis and restored DMM-induced dysregulated autophagy evidenced by the upregulation of ATG7 and LC3 II/LC3 I but decreased P62 level. Mechanistically, METTL3-mediated m6A modification decreased the expression of ATG7 in DMM mice, as it could be significantly attenuated by GBD. METTL3 overexpression significantly counteracted the protective effect of GBD on chondrocyte autophagy. Further research showed that GBD promoted proteasome-mediated ubiquitination degradation of METLL3. Our findings suggest that GBD could act as a protective agent against KOA. The protective effect of GBD may result from its promotion on chondrocyte autophagy by suppressing METTL3-dependent ATG7 m6A methylation.

Nanofiber-reinforced chitosan/gelatine hydrogel with photothermal, antioxidant and conductive capabilities promotes healing of infected wounds.

The wound healing process was often accompanied by bacterial infection and inflammation. The combination of electrically conductive nanomaterials and wound dressings could accelerate cell proliferation through endogenous electrical signaling, effectively promoting wound healing. In this study, polypyrrole was modified with dopamine hydrochloride by an in situ polymerization to form dopamine-polypyrrole (DA-Ppy) conductive nanofibers which successfully enhanced the water dispersibility and biocompatibility of polypyrrole. The DA-Ppy nanofibers were dispersed in an aqueous solution for >48 h and still maintained good stability. In addition, the DA-Ppy nanofibers showed good photothermal properties, and the temperature could reach 59.7 °C by 1.5 W/cm2 near-infrared light irradiation (NIR) for 10 min. DA-Ppy conductive nanofibres could be well dispersed in 3,4-dihydroxyphenylpropionic acid modified chitosan-carboxymethylated ß-cyclodextrin modified gelatin (CG) hydrogel due to the presence of DA, which endowed CG/DA-Ppy hydrogel with good adhesion properties, and the hydrogel adhered to the pigskin would not be dislodged by washing with running water. Under NIR, the CG/DA-Ppy hydrogel showed significant antimicrobial properties. Moreover, the CG/DA-Ppy hydrogel had excellent biocompatibility. In addition, CG/DA-Ppy hydrogel was effective in scavenging ROS, inducing macrophage polarization towards the M2 phenotype, and modulating the level of wound inflammation in vitro. Finally, it was confirmed in rat-infected wounds that the tissue regeneration effect and collagen deposition in the CG/DA-Ppy + NIR group were significantly better than the other groups in the repair of infected wounds, indicating better repair of infected wounds. The results suggested that the photothermal, antioxidant DA-Ppy conductive nanofiber had great potential for application in infected wound healing.

Trimethylsilane Plasma-Nanocoated Silver Nanowires for Improved Stability.

The objective of this study was to evaluate the effectiveness of trimethylsilane (TMS) plasma nanocoatings in protecting silver nanowires (AgNWs) from degradation and thus to improve their stability. TMS plasma nanocoatings at various thicknesses were deposited onto AgNWs that were prepared on three different substrates, including glass, porous styrene-ethylene-butadiene-styrene (SEBS), and poly-L-lactic acid (PLLA). The experimental results showed that the application of TMS plasma nanocoatings to AgNWs induced little increase, up to ~25%, in their electrical resistance but effectively protected them from degradation. Over a two-month storage period in summer (20-22 °C, 55-70% RH), the resistance of the coated AgNWs on SEBS increased by only ~90%, compared to a substantial increase of ~700% for the uncoated AgNWs. On glass, the resistance of the coated AgNWs increased by ~30%, versus ~190% for the uncoated ones. When stored in a 37 °C phosphate-buffered saline (PBS) solution for 2 months, the resistance of the coated AgNWs on glass increased by ~130%, while the uncoated AgNWs saw a ~970% rise. Increasing the TMS plasma nanocoating thickness further improved the conductivity stability of the AgNWs. The nanocoatings also transformed the AgNWs' surfaces from hydrophilic to hydrophobic without significantly affecting their optical transparency. These findings demonstrate the potential of TMS plasma nanocoatings in protecting AgNWs from environmental and aqueous degradation, preserving their electrical conductivity and suitability for use in transparent electrodes and wearable electronics.

Use of a large language model with instruction-tuning for reliable clinical frailty scoring.

BACKGROUND: Frailty is an important predictor of health outcomes, characterized by increased vulnerability due to physiological decline. The Clinical Frailty Scale (CFS) is commonly used for frailty assessment but may be influenced by rater bias. Use of artificial intelligence (AI), particularly Large Language Models (LLMs) offers a promising method for efficient and reliable frailty scoring. METHODS: The study utilized seven standardized patient scenarios to evaluate the consistency and reliability of CFS scoring by OpenAI's GPT-3.5-turbo model. Two methods were tested: a basic prompt and an instruction-tuned prompt incorporating CFS definition, a directive for accurate responses, and temperature control. The outputs were compared using the Mann-Whitney U test and Fleiss' Kappa for inter-rater reliability. The outputs were compared with historic human scores of the same scenarios. RESULTS: The LLM's median scores were similar to human raters, with differences of no more than one point. Significant differences in score distributions were observed between the basic and instruction-tuned prompts in five out of seven scenarios. The instruction-tuned prompt showed high inter-rater reliability (Fleiss' Kappa of 0.887) and produced consistent responses in all scenarios. Difficulty in scoring was noted in scenarios with less explicit information on activities of daily living (ADLs). CONCLUSIONS: This study demonstrates the potential of LLMs in consistently scoring clinical frailty with high reliability. It demonstrates that prompt engineering via instruction-tuning can be a simple but effective approach for optimizing LLMs in healthcare applications. The LLM may overestimate frailty scores when less information about ADLs is provided, possibly as it is less subject to implicit assumptions and extrapolation than humans. Future research could explore the integration of LLMs in clinical research and frailty-related outcome prediction.

Brain-wide functional connectivity alterations and their cognitive correlates in subjective cognitive decline.

Background: Individuals with subjective cognitive decline (SCD) are at risk of developing Alzheimer's Disease (AD). Traditional seed-based analysis has shown biased functional connectivity (FC) in SCD individuals. To investigate unbiased altered FC by the brain-wide association study (BWAS) and to determine its association with cognition in SCD individuals. Methods: Measure of association (MA) analysis was applied to detect significant voxels with FC changes. Based on these changes, we identified regions of interest (ROIs) and conducted ROI-wise FC analyses. Correlation analyses were then performed between these FC circuits and cognition. Results: MA analysis identified 10 ROIs with significantly altered voxels. ROI-wise FC analyses revealed 14 strengthened FC, predominantly parietal-occipital link alterations. The FC between the right superior occipital gyrus and the right postcentral gyrus correlated positively with executive function, while the FC between the right middle occipital gyrus and the left angular gyrus correlated positively with episodic memory in SCD individuals. Conclusion: SCD involves multifocal impairments, of which regions of default mode network (DMN) and occipital lobe should be specially focused. Cross-hemispheric alterations indicate an internal interactive impairment pattern in SCD. The reduced FC between the right superior occipital gyrus and the right postcentral gyrus, and between the right middle occipital gyrus and the left angular gyrus, which correlate with specific cognitive functions, could serve as potential biomarkers for SCD diagnosis.

Novel PLCZ1 compound heterozygous mutations indicate gene dosage effect involved in total fertilisation failure after ICSI.

In brief: PLCZ1 mutations are related to total fertilisation failure (TFF) after intracytoplasmic sperm injection (ICSI), characterised by abnormal oocyte oscillations. The novel PLCZ1 compound heterozygous mutations reported by this study were associated with TFF after ICSI, with one of the mutations indicating a gene dosage effect. Abstract: Oocyte activation failure is thought to be one of the main factors for total fertilisation failure (TFF) after intracytoplasmic sperm injection (ICSI), which could be induced by abnormal calcium oscillations. Phospholipase C zeta (PLCZ), a sperm factor, is associated with Ca2+ oscillations in mammalian oocytes. To date, some mutations in PLCZ1 (the gene that encodes PLCZ) have been linked to TFF, as demonstrated by the observed reduction in protein levels or activity to induce Ca2+ oscillations. In this study, normozoospermic males whose sperms exhibited TFF after ICSI and their families were recruited. First, mutations in the PLCZ1 sequence were identified by whole exome sequencing and validated using Sanger sequencing. Then, the locations of PLCZ1/PLCZ and the transcript and protein levels in the sperm of the patients were studied. Subsequently, in vitro function analysis and in silico analysis were performed to investigate the function-structure correlation of mutations identified in PLCZ1 using western blotting, immunofluorescence, RT-qPCR, and molecular simulation. Ca2+ oscillations were detected after cRNA microinjection into MII mouse oocytes to investigate calcium oscillations induced by abnormal PLCZ. Five variants with compound heterozygosity were identified, consisting of five new mutations and three previously reported mutations distributed across the main domains of PLCZ, except the EF hands domain. The transcript and protein levels decreased to varying degrees among all detected mutations in PLCZ1 when transfected in HEK293T cells. Among these, mutations in M138V and R391* of PLCZ were unable to trigger typical Ca2+ oscillations. In case 5, aberrant localisation of PLCZ in the sperm head and an increased expression of PLCZ in the sperm were observed. In conclusion, this study enhances the potential for genetic diagnosis of TFF in clinics and elucidates the possible relationship between the function and structure of PLCZ in novel mutations.

Assessment of stress levels and reproductive condition in giant pandas: insights from hair, faecal and saliva samples.

Concerted conservation efforts have brought the giant panda (Ailuropoda melanoleuca) back from the brink of extinction, but pandas continue to face anthropogenic threats in the wild and breeding success in captivity remains low. Because stress can have detrimental impacts on reproduction, monitoring stress- and sex-steroid levels would help assess the effectiveness of conservation mitigation measures in panda populations as well as monitor the welfare and reproductive health of captive animals. In this proof-of-concept study, we used faecal sex steroid and cortisol concentrations (n = 867 samples collected from five males and five females at Beijing Zoo every 4 days over the course of 12 months) as a reference to investigate if testosterone, estradiol, progesterone and cortisol can be meaningfully measured in panda hair (n = 10) using radio-immuno-assays. Additionally, we calculated the ratio of testosterone to cortisol (T:C ratio) for each male, which can provide a biomarker of stress and physical performance. Our findings revealed distinct monthly variations in faecal sex-steroid and cortisol concentrations, reflecting reproductive seasonality and visitor-related stress among individual pandas. Notably, the oldest male had a significantly lower T:C ratio than other males. Our results confirm that the level of sex steroids and cortisol can be assayed by panda hair, and the hair cortisol concentrations correlate significantly with that in faeces with one month lag behind (r = 0.68, P = 0.03). However, the concentrations of hormones detected in saliva are lower than those in faeces by two orders of magnitude, making it difficult to ensure accuracy. By assessing the applicability of hair, faecal and salivary sampling, we can infer their utility in monitoring the reproductive status and acute and chronic stress levels of giant pandas, thereby providing a means to gauge the success of ongoing habitat restoration efforts and to discuss the feasibility of sample collection from wild populations.

The implementation of robotic dogs in automatic detection and surveillance of red imported fire ant nests.

BACKGROUND: The Red Imported Fire Ant (RIFA), scientifically known as Solenopsis invicta, is a destructive invasive species causing considerable harm to ecosystems and generating substantial economic costs globally. Traditional methods for RIFA nests detection are labor-intensive and may not be scalable to larger field areas. This study aimed to develop an innovative surveillance system that leverages artificial intelligence (AI) and robotic dogs to automate the detection and geolocation of RIFA nests, thereby improving monitoring and control strategies. RESULTS: The designed surveillance system, through integrating the CyberDog robotic platform with a YOLOX AI model, demonstrated RIFA nest detection precision rates of >90%. The YOLOX model was trained on a dataset containing 1118 images and achieved a final precision rate of 0.95, with an inference time of 20.16 ms per image, indicating real-time operational suitability. Field tests revealed that the CyberDog system identified three times more nests than trained human inspectors, with significantly lower rates of missed detections and false positives. CONCLUSION: The findings underscore the potential of AI-driven robotic systems in advancing pest management. The CyberDog/YOLOX system not only matched human inspectors in speed, but also exceeded them in accuracy and efficiency. This study's results are significant as they highlight how technology can be harnessed to address biological invasions, offering a more effective, ecologically friendly, and scalable solution for RIFA detection. The successful implementation of this system could pave the way for broader applications in environmental monitoring and pest control, ultimately contributing to the preservation of biodiversity and economic stability. © 2024 Society of Chemical Industry.

Identification of immune-related genes and small-molecule drugs in hypertension-induced left ventricular hypertrophy based on machine learning algorithms and molecular docking.

Background: Left ventricular hypertrophy (LVH) is a common consequence of hypertension and can lead to heart failure. The immune response plays an important role in hypertensive LVH; however, there is no comprehensive method to investigate the mechanistic relationships between immune response and hypertensive LVH or to find novel therapeutic targets. This study aimed to screen hub immune-related genes involved in hypertensive LVH as well as to explore immune target-based therapeutic drugs. Materials and methods: RNA-sequencing data from a mouse model generated by angiotensin II infusion were subjected to weighted gene co-expression network analysis (WGCNA) to identify core expression modules. Machine learning algorithms were applied to screen immune-related LVH characteristic genes. Heart structures were evaluated by echocardiography and cardiac magnetic resonance imaging (CMRI). Validation of hub genes was conducted by RT-qPCR and western blot. Using the Connectivity Map database and molecular docking, potential small-molecule drugs were explored. Results: A total of 1215 differentially expressed genes were obtained, most of which were significantly enriched in immunoregulation and collagen synthesis. WGCNA and multiple machine learning strategies uncovered six hub immune-related genes (Ankrd1, Birc5, Nuf2, C1qtnf6, Fcgr3, and Cdca3) that may accurately predict hypertensive LVH diagnosis. Immune analysis revealed that fibroblasts and macrophages were closely correlated with hypertensive LVH, and hub gene expression was significantly associated with these immune cells. A regulatory network of transcription factor-mRNA and a ceRNA network of miRNA-lncRNA was established. Notably, six hub immune-related genes were significantly increased in the hypertensive LVH model, which were positively linked to left ventricle wall thickness. Finally, 12 small-molecule compounds with the potential to reverse the high expression of hub genes were ruled out as potential therapeutic agents for hypertensive LVH. Conclusion: This study identified and validated six hub immune-related genes that may play essential roles in hypertensive LVH, providing new insights into the potential pathogenesis of cardiac remodeling and novel targets for medical interventions.

Potential association of rheumatic diseases with bone mineral density and fractures: a bi-directional mendelian randomization study.

BACKGROUND: Previous studies have implicated rheumatoid arthritis as an independent risk factor for bone density loss. However, whether there is a causal relationship between rheumatic diseases and bone mineral density (BMD) and fractures is still controversial. We employed a bidirectional Mendelian analysis to explore the causal relationship between rheumatic diseases and BMD or fractures. METHODS: The rheumatic diseases instrumental variables (IVs) were obtained from a large Genome-wide association study (GWAS) meta-analysis dataset of European descent. Analyses were performed for the three rheumatic diseases: ankylosing spondylitis (AS) (n = 22,647 cases, 99,962 single nucleotide polymorphisms [SNPs]), rheumatoid arthritis (RA) (n = 58,284 cases, 13,108,512 SNPs), and systemic lupus erythematosus (SLE) (n = 14,267 cases, 7,071,163 SNPs). Two-sample Mendelian randomization (MR) analyses were carried out by using R language TwoSampleMR version 0.5.7. The inverse-variance weighted (IVW), MR-Egger, and weighted median methods were used to analyze the causal relationship between rheumatic diseases and BMD or fracture. RESULTS: The MR results revealed that there was absence of evidence for causal effect of AS on BMD or fracture. However, there is a positive causal relationship of RA with fracture of femur (95% CI = 1.0001 to 1.077, p = 0.046), and RA and fracture of forearm (95% CI = 1.015 to 1.064, p = 0.001). SLE had positive causal links for fracture of forearm (95% CI = 1.004 to 1.051, p = 0.020). Additionally, increasing in heel bone mineral density (Heel-BMD) and total bone mineral density (Total-BMD) can lead to a reduced risk of AS without heterogeneity or pleiotropic effects. The results were stable and reliable. There was absence of evidence for causal effect of fracture on RA (95% CI = 0.929 to 1.106, p = 0.759), and fracture on SLE (95% CI = 0.793 to 1.589, p = 0.516). CONCLUSIONS: RA and SLE are risk factors for fractures. On the other hand, BMD increasing can reduce risk of AS. Our results indicate that rheumatic diseases may lead to an increased risk of fractures, while increased BMD may lead to a reduced risk of rheumatic diseases. These findings provide insight into the risk of BMD and AS, identifying a potential predictor of AS risk as a reduction in BMD.

Engineering Bis-Pyridine N-Functionalized Cellulose Aerogel for Efficient Extraction of Cu2+ from High-Acidity Wastewaters: Coupling Molecular Scale Interpretation with Experiment.

In order to address the issue of protonation of functional groups and structural instability on the surface of aerogel due to strong acidic wastewater, a three-dimensional bis-pyridine N cellulose aerogel [PEIPD/carboxymethyl cellulose (CMC)] with protonation resistance was prepared in this paper by grafting pyridine onto polyethylenimine. The adsorption capacity for Cu2+ of the as-prepared aerogel is as high as 1.64 mmol/g (pH 5) and is maintained well in high-acidity solutions (1.15 mmol/g at pH = 2). It reveals high selectivity, splendid anti-interference ability, and also reliable on the recycle performance. Through the zeta potential tests, this adsorbent reveals a rather low zero charge point (pHpzc = 2.2). The adsorption of Cu2+ on the adsorbent is consistent with the pseudo-second-order kinetic model and the Langmuir model, suggesting that the adsorption process is dominated by chemisorption in a monolayer. The characterizations by Fourier transform infrared spectrometry and X-ray photoelectron spectroscopy proved pyridine N as responsible binding sites, based on which two possible mechanisms are proposed, including chelation and cation-π interaction. Density functional theory calculations are further used to precisely investigate the pathway. By comparing the binding energies, molecular electrostatic potentials, electron densities, and differential charge densities, the bis-pyridine N functional group is finally determined to be of much higher affinity to Cu2+ following chelation reaction as designated. By integrating bis-pyridine N with the CMC and understanding their crucial roles, this will provide significant insights into the rational design of aerogel adsorbents to enhance the recovery of Cu from strongly acidic wastewaters.

Comparison of the Quality of Discharge Letters Written by Large Language Models and Junior Clinicians: Single-Blinded Study.

BACKGROUND: Discharge letters are a critical component in the continuity of care between specialists and primary care providers. However, these letters are time-consuming to write, underprioritized in comparison to direct clinical care, and are often tasked to junior doctors. Prior studies assessing the quality of discharge summaries written for inpatient hospital admissions show inadequacies in many domains. Large language models such as GPT have the ability to summarize large volumes of unstructured free text such as electronic medical records and have the potential to automate such tasks, providing time savings and consistency in quality. OBJECTIVE: The aim of this study was to assess the performance of GPT-4 in generating discharge letters written from urology specialist outpatient clinics to primary care providers and to compare their quality against letters written by junior clinicians. METHODS: Fictional electronic records were written by physicians simulating 5 common urology outpatient cases with long-term follow-up. Records comprised simulated consultation notes, referral letters and replies, and relevant discharge summaries from inpatient admissions. GPT-4 was tasked to write discharge letters for these cases with a specified target audience of primary care providers who would be continuing the patient's care. Prompts were written for safety, content, and style. Concurrently, junior clinicians were provided with the same case records and instructional prompts. GPT-4 output was assessed for instances of hallucination. A blinded panel of primary care physicians then evaluated the letters using a standardized questionnaire tool. RESULTS: GPT-4 outperformed human counterparts in information provision (mean 4.32, SD 0.95 vs 3.70, SD 1.27; P=.03) and had no instances of hallucination. There were no statistically significant differences in the mean clarity (4.16, SD 0.95 vs 3.68, SD 1.24; P=.12), collegiality (4.36, SD 1.00 vs 3.84, SD 1.22; P=.05), conciseness (3.60, SD 1.12 vs 3.64, SD 1.27; P=.71), follow-up recommendations (4.16, SD 1.03 vs 3.72, SD 1.13; P=.08), and overall satisfaction (3.96, SD 1.14 vs 3.62, SD 1.34; P=.36) between the letters generated by GPT-4 and humans, respectively. CONCLUSIONS: Discharge letters written by GPT-4 had equivalent quality to those written by junior clinicians, without any hallucinations. This study provides a proof of concept that large language models can be useful and safe tools in clinical documentation.

Lymphoma-associated hemophagocytic syndrome: a retrospective, single-center study of 86 patients.

To explore the clinical features, treatment, and prognosis of patients with lymphoma-associated hemophagocytic syndrome (LAHS) in a real-world clinical setting. We retrospectively examined LAHS patients diagnosed at our center between January 2016 and August 2023, focusing primarily on their clinical features, therapeutic approaches, overall response rate (ORR), and overall survival (OS). A combination of univariate and multivariate analyses was conducted to identify potential prognostic factors. A total of 86 patients diagnosed with LAHS were included to evaluate clinical characteristics and prognostic factors. Patients with T/NK cell lymphoma had a higher probability of developing hemophagocytic syndrome (HPS) during the clinical process than those with B cell lymphoma. The median survival time was 55 days for all patients, and 47 and 81 days for the T/NK cell LAHS and B cell LAHS cohorts, respectively (P = 0.025). Among the patients evaluated, the ORR was 42.2%. Patients starting with anti-lymphoma treatment had a better, albeit not significant, ORR than those beginning with anti-HPS treatment. In the univariate analysis, T/NK cell LAHS (P = 0.027), HPS onset at relapse (P = 0.036), higher baseline plasma EBV-DNA levels (> 4,000 copies/mL, P = 0.034), and treatments including cytokine adsorption and ruxolitinib (P < 0.001 and P = 0.017, respectively) were potentially associated with worse OS, while corticosteroid therapy benefited OS. In the multivariate analysis, T/NK cell LAHS (adjusted hazard ratio (aHR) = 2.007), cytokine adsorption therapy (aHR = 4.547), and corticosteroid therapy (aHR = 0.118) were independently associated with mortality. T/NK cell lymphoma was the main cause of LAHS and carried a worse prognosis. Whether anti-lymphoma or anti-HPS treatment should start first still requires prospective studies with larger sample sizes. The key point in controlling HPS is to block the cytokine storm promptly. Corticosteroid therapy is both effective and accessible and should be used early and in sufficient quantities.