Exploring decision-makers' challenges and strategies when selecting multiple systematic reviews: insights for AI decision support tools in healthcare.

BACKGROUND: Systematic reviews (SRs) are being published at an accelerated rate. Decision-makers may struggle with comparing and choosing between multiple SRs on the same topic. We aimed to understand how healthcare decision-makers (eg, practitioners, policymakers, researchers) use SRs to inform decision-making and to explore the potential role of a proposed artificial intelligence (AI) tool to assist in critical appraisal and choosing among SRs. METHODS: We developed a survey with 21 open and closed questions. We followed a knowledge translation plan to disseminate the survey through social media and professional networks. RESULTS: Our survey response rate was lower than expected (7.9% of distributed emails). Of the 684 respondents, 58.2% identified as researchers, 37.1% as practitioners, 19.2% as students and 13.5% as policymakers. Respondents frequently sought out SRs (97.1%) as a source of evidence to inform decision-making. They frequently (97.9%) found more than one SR on a given topic of interest to them. Just over half (50.8%) struggled to choose the most trustworthy SR among multiple. These difficulties related to lack of time (55.2%), or difficulties comparing due to varying methodological quality of SRs (54.2%), differences in results and conclusions (49.7%) or variation in the included studies (44.6%). Respondents compared SRs based on the relevance to their question of interest, methodological quality, and recency of the SR search. Most respondents (87.0%) were interested in an AI tool to help appraise and compare SRs. CONCLUSIONS: Given the identified barriers of using SR evidence, an AI tool to facilitate comparison of the relevance of SRs, the search and methodological quality, could help users efficiently choose among SRs and make healthcare decisions.

Psychological and psychosocial determinants of COVID-related handwashing behaviours: A systematic review.

Background: The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has resulted in illness, deaths and societal disruption on a global scale. Societies have implemented various control measures to reduce transmission of the virus and mitigate its impact. Individual behavioural changes are crucial to the successful implementation of these measures. One commonly recommended measure to limit risk of infection is frequent handwashing. It is important to identify those factors that can predict the uptake and maintenance of handwashing. Objectives: We aimed to identify and synthesise the evidence on malleable psychological and psychosocial factors that determine uptake and adherence to handwashing aimed at reducing the risk of infection or transmission of COVID-19. Search Methods: We searched various literature sources including electronic databases (Medline ALL, Child Development & Adolescent Studies, ERIC, PsycInfo, CINAHL and Web of Science), web searches, conference proceedings, government reports, other repositories of literature and grey literature. The search strategy was built around three concepts of interest including (1) context (terms relating to COVID-19), (2) behaviour of interest and (3) terms related to psychological and psychosocial determinants of COVID Health-Related Behaviours and adherence or compliance with handwashing, to capture malleable determines. Searches capture studies up until October 2021. Selection Criteria: Eligibility criteria included observational studies (both retrospective and prospective) and experimental studies that measure and report malleable psychological and psychosocial determinants and handwashing at an individual level, amongst the general public. Screening was supported by the Cochrane Crowd. Titles and abstracts were screened against the eligibility criteria by three independent screeners. Following this, all potentially relevant studies were screened at full-text level by the research team. All conflicts between screeners were resolved by discussion between the core research team. Data Collection and Analysis: All data extraction was managed in EPPI-Reviewer software. All eligible studies, identified through full-text screening were extracted by one author. We extracted data on study information, population, determinant, behaviour and effects. A second author checked data extraction on 20% of all included papers. All conflicts were discussed by the two authors until consensus was reached.We assessed methodological quality of all included studies using an adapted version of the Joanna Briggs Institute Quality appraisal tool for cross-sectional studies. Main Results: Our initial searches yielded 23,587 results, of which 56 studies were included in this review. The included studies were cross sectional in design, came from 22 countries and had a combined sample of 199,376 participants. The vast majority of studies had samples from the general public, with eight of the studies focusing on specific samples. All included studies considered people over the age of 18. The quality of the majority of the studies was good (n = 30 rated low risk of bias), with 8 rated high risk of bias, predominately due to lack of reporting of recruitment, sample characteristics and methodology. Thirty-four studies were included in the narrative synthesis and 28 in the meta-analysis.Findings indicated that emotions about COVID-19 (worry [0.381, confidence interval [CI] = 0.270-0.482, I 2 = 92%) and anxiety (0.308, CI = 0.154-0.448, I 2 = 91%]), knowledge of COVID-19 (0.323, CI = 0.223-0.417, I 2 = 94%), and perceived social norms (0.303, CI = 0.184-0.413, I 2 = 92%) were among the malleable determinants most associated with handwashing. Perceived severity (0.006, CI = -0.011-0.023) and susceptibility of COVID-19 (0.041, CI = -0.034 to 0.115) had little to no effect on handwashing behaviour. Authors' Conclusions: Understanding the effects of various malleable determinants on COVID-related handwashing can aid in the development and implementation of interventions and public health campaigns to promote handwashing behaviour in potential new waves of COVID-19 or other respiratory infections. Emotions about COVID, knowledge of COVID and perceived social norms warrant further consideration in future research and policy.

Synthetic routes and clinical application of Small-Molecule HER2 inhibitors for cancer therapy.

This comprehensive review undertakes a meticulous scrutiny of the synthesis and clinical applications pertaining to small-molecule tyrosine kinase inhibitors (TKIs) directed towards the human epidermal growth factor receptor 2 (HER2), a pivotal protagonist in the pathogenesis of cancer. Focused on compounds like lapatinib, neratinib, and tucatinib, the review delves into the intricate synthesis strategies, emphasizing the challenges associated with their structural complexity. The clinical utilization of HER2 TKIs underscores noteworthy strides in the therapeutic landscape for HER2-positive breast and gastric malignancies. Lapatinib, a dual HER2/ epidermal growth factor receptor (EGFR) inhibitor, has demonstrated efficacy in combination therapies, addressing the need for overcoming resistance mechanisms. Neratinib, an irreversible HER2 inhibitor, presents a promising avenue for patients with refractory tumors. Tucatinib, strategically engineered to traverse the blood-brain barrier, epitomizes a groundbreaking advancement in the management of metastatic HER2-positive breast cancer manifesting cerebral involvement. Despite their success, challenges such as resistance mechanisms and off-target effects persist, urging continuous research for the development of next-generation HER2 TKIs. This comprehensive review serves as a valuable resource for pharmaceutical scientists, offering insights into the synthetic intricacies and clinical impact of small-molecule TKIs targeting HER2.

Association between Time to Emergent Surgery and Outcomes in Trauma Patients: A 10-Year Multicenter Study.

Background: Research on the impact of reduced time to emergent surgery in trauma patients has yielded inconsistent results. Therefore, this study investigated the relationship between waiting emergent surgery time (WEST) and outcomes in trauma patients. Methods: This retrospective, multicenter study used data from the Tzu Chi Hospital trauma database. The primary clinical outcomes were in-hospital mortality, intensive care unit (ICU) admission, and prolonged hospital length of stay (LOS) of ≥30 days. Results: A total of 15,164 patients were analyzed. The median WEST was 444 min, with an interquartile range (IQR) of 248-848 min for all patients. Patients who died in the hospital had a shorter median WEST than did those who survived (240 vs. 446 min, p < 0.001). Among the trauma patients with a WEST of <2 h, the median time was 79 min (IQR = 50-100 min). No significant difference in WEST was observed between the survival and mortality groups for patients with a WEST of <120 min (median WEST: 85 vs. 78 min, p < 0.001). Multivariable logistic regression analysis revealed that WEST was not associated with an increased risk of in-hospital mortality (adjusted odds ratio [aOR] = 1.05, 95% confidence interval [CI] = 0.17-6.35 for 30 min ≤ WEST < 60 min; aOR = 1.12, 95% CI = 0.22-5.70 for 60 min ≤ WEST < 90 min; and aOR = 0.60, 95% CI = 0.13-2.74 for WEST ≥ 90 min). Conclusions: Our findings do not support the "golden hour" concept because no association was identified between the time to definitive care and in-hospital mortality, ICU admission, and prolonged hospital stay of ≥30 days.

Influencing factors of home hospice care needs of the older adults with chronic diseases at the end of life in China: a cross-sectional study.

Introduction: Chronic diseases are becoming a serious threat to the physical and mental health of older people in China as their aging process picks up speed. Home hospice care addresses diverse needs and enhances the quality of life for older adult individuals nearing the end of life. To ensure the well-being of chronically ill older adults at the end of life, it is vital to explore and assess the multidimensional hospice needs of terminally ill older individuals in their homes. The aim of this study was to investigate the current situation of home hospice care needs of Chinese older adults with chronic diseases at the end of life, and to analyze the influencing factors (sociodemographic and disease-related factors). Methods: In this cross-sectional study, 247 older adult people with chronic diseases at the end of life were selected from the communities of 4 community health service centers in Jinzhou City, Liaoning Province from June to October 2023 by random sampling method. A general information questionnaire and the home hospice care needs questionnaire developed by our research group were used to investigate. Independent samples t-test or one-way ANOVA was used to compare the differences in the scores of different characteristics, and the factors with significant differences were selected for multivariate linear regression analysis to determine the final influencing factors. Results: The total score of home hospice needs of the dying older adult was 115.70 ± 12, with the mean scores for each dimension in descending order being Information Needs (3.96 ± 0.61), Social Support Needs (3.96 ± 0.44), Spiritual Needs (3.92 ± 0.43), Physical Needs (3.60 ± 0.59), Psychological Needs (3.37 ± 0.65). Status of residence, duration of illness (year), the type of disease, and self-care ability were influential factors in the total score of home hospice needs. Discussion: The need for hospice care for the terminally ill older adult is high, and healthcare professionals should implement services according to the influencing factors of need to meet their multidimensional needs and improve their quality of life.

Study on the gelling properties of egg white/surfactant system by different heating intensities.

The aim of this study was to elucidate the different effects and difference mechanism of gelling properties among egg white (EW) treated with different heating intensities and the composite addition of rhamnolipid and soybean lecithin. Particle size analyzer, potentiometric analyzer, surface hydrophobicity method, and Fourier transform infrared spectroscopy techniques were used to determine the physicochemical properties and molecular structure, respectively. Low-field nuclear magnetic resonance, magnetic resonance imaging, texture profile analysis, and scanning electron microscopy techniques were used to analyze the gelling properties and gel structure, respectively. And we illuminate the different mechanisms in the gelling properties of the EW with various treatments and key internal factors that play important roles in improving gelling properties by establishing the link between the gelling properties and relevant characteristics by mixed effects model and visual network analysis. The results indicate raising the content of rhamnolipid decreased the migration of immobilized water in the EW gel and the free water content. At the heating intensities of 55 °C/3.5, 65 °C/2.5, and 67 °C/1.5 min, with an increase in rhamnolipid, the gel's cohesiveness, gumminess, and chewiness gradually increased. The mixed effects model indicated that heating intensities and composite ratios have a 2-way interaction on zeta potential, the relaxation time of bound water (T21), the content of bound water (P21), the content of immobilized water (P22), and fractal dimension (df) attributes (P < 0.05). The visual network analysis showed that the protein solubility, the relaxation time of immobilized water (T22), surface hydrophobicity, zeta potential, average particle size (d43) and the relaxation time of free water (T23) are critical contributors to the different gelling properties of EW subjected to various treatments and the improvement of gelling properties. This study will provide theoretical guidance for the development of egg white products and the expansion of egg white's application scope in the egg product processing industry.

Prehospital Shock Index Multiplied by the Alert/Verbal/Painful/Unresponsive Score as a Predictor of Clinical Outcomes in Traumatic Injury.

OBJECTIVE: Various prediction scores have been developed to predict mortality in trauma patients, such as the shock index (SI), modified SI (mSI), age-adjusted SI (aSI), and the shock index (SI) multiplied by the alert/verbal/painful/unresponsive (AVPU) score (SIAVPU). The SIAVPU is a novel scoring system but its prediction accuracy for trauma outcomes remains in need of further validation. Therefore, we investigated the accuracy of four scoring systems, including SI, mSI, aSI, and SIAVPU, in predicting mortality, admission to the intensive care unit (ICU), and prolonged hospital length of stay ≥ 30 days (LOS). METHODS: This retrospective multicenter study used data from the Tzu Chi Hospital trauma database. The area under the receiver operating characteristic curve (AUROC) was determined for each outcome to assess their discrimination capabilities and comparing by Delong's test. Subgroup analyses were conducted to investigate the prediction accuracy of the SIAVPU in different patient populations. RESULTS: In total, 5355 patients were included in the analysis. The median of SIAVPU were significantly higher among patients at those with major injury (1.47 vs 0.63), those admitted to the ICU (0.73 vs 0.62), those with prolonged hospital LOS≥ 30 days (0.83 vs 0.64), and those with mortality (1.08 vs 0.64). The AUROC of the SIAVPU was significantly higher than that of the SI, mSI, and aSI for 24-h mortality (AUROC: 0.845 vs 0.533, 0.540, and 0.678), 3-day mortality (AUROC: 0.803 vs 0.513, 0.524, and 0.688), 7-day mortality (AUROC: 0.755 vs 0.494, 0.505, and 0.648), in-hospital mortality (AUROC: 0.722 vs 0.510, 0.524, and 0.667), ICU admission (AUROC: 0.635 vs 0.547, 0.551, and 0.563). At the optimal cutoff value of 0.9, the SIAVPU had an accuracy of 82.2% for predicting 24-h mortality, 82.8% for predicting 3-day mortality, of 82.8% for predicting 7-day mortality, of 82.5% for predicting in-hospital mortality, of 73.9% for predicting Intensive Care Unit (ICU) admission, and of 81.7% for predicting prolonged hospital LOS ≥30 days. CONCLUSIONS: Our results reveal that SIAVPU has better accuracy than the SI, mSI, and aSI for predicting 24-h, 3-day, 7-day, and in-hospital mortality; ICU admission; and prolonged hospital LOS ≥30 days among patients with traumatic injury.

OTUB1 contributes to the stability and function of Influenza A virus NS2.

The influenza A virus (IAV) consists of 8 single-stranded, negative-sense viral RNA (vRNA) segments. After infection, vRNA is transcribed, replicated, and wrapped by viral nucleoprotein (NP) to form viral ribonucleoprotein (vRNP). The transcription, replication, and nuclear export of the viral genome are regulated by the IAV protein, NS2, which is translated from spliced mRNA transcribed from viral NS vRNA. This splicing is inefficient, explaining why NS2 is present in low abundance after IAV infection. The levels of NS2 and its subsequent accumulation are thought to influence viral RNA replication and vRNP nuclear export. Here we show that NS2 is ubiquitinated at the K64 and K88 residues by K48-linked and K63-linked polyubiquitin (polyUb) chains, leading to the degradation of NS2 by the proteasome. Additionally, we show that a host deubiquitinase, OTUB1, can remove polyUb chains conjugated to NS2, thereby stabilizing NS2. Accordingly, knock down of OTUB1 by siRNA reduces the nuclear export of vRNP, and reduces the overall production of IAV. These results collectively demonstrate that the levels of NS2 in IAV-infected cells are regulated by a ubiquitination-deubiquitination system involving OTUB1 that is necessary for optimal IAV replication.

Stellae-123 gene expression signature improved risk stratification in taiwanese acute myeloid leukemia patients.

The European Leukemia Net recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, notwithstanding that gene expression analysis is crucial in the risk stratification of AML. The Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated robust survival predictions in AML patients across four western-population cohorts. This study aims to evaluate the applicability of Stellae-123 in a Taiwanese cohort. The Stellae-123 model was applied to 304 de novo AML patients diagnosed and treated at the National Taiwan University Hospital. We find that the pretrained (BeatAML-based) model achieved c-indexes of 0.631 and 0.632 for the prediction of overall survival (OS) and relapse-free survival (RFS), respectively. Model retraining within our cohort further improve the cross-validated c-indexes to 0.667 and 0.667 for OS and RFS prediction, respectively. Multivariable analysis identify both pretrained and retrained models as independent prognostic biomarkers. We further show that incorporating age, Stellae-123, and ELN classification remarkably improves risk stratification, revealing c-indices of 0.73 and 0.728 for OS and RFS, respectively. In summary, the Stellae-123 gene expression signature is a valuable prognostic tool for AML patients and model retraining can improve the accuracy and applicability of the model in different populations.

On-Demand Catalysed n-Doping of Organic Semiconductors.

A new approach to control the n-doping reaction of organic semiconductors is reported using surface-functionalized gold nanoparticles (f-AuNPs) with alkylthiols acting as the catalyst only upon mild thermal activation. To demonstrate the versatility of this methodology, the reaction of the n-type dopant precursor N-DMBI-H with several molecular and polymeric semiconductors at different temperatures with/without f-AuNPs, vis-à-vis the unfunctionalized catalyst AuNPs, was investigated by spectroscopic, morphological, charge transport, and kinetic measurements as well as, computationally, the thermodynamic of catalyst activation. The combined experimental and theoretical data demonstrate that while f-AuNPs is inactive at room temperature both in solution and in the solid state, catalyst activation occurs rapidly at mild temperatures (~70 °C) and the doping reaction completes in few seconds affording large electrical conductivities (~10-140 S cm-1). The implementation of this methodology enables the use of semiconductor+dopant+catalyst solutions and will broaden the use of the corresponding n-doped films in opto-electronic devices such as thin-film transistors, electrochemical transistors, solar cells, and thermoelectrics well as guide the design of new catalysts.

Photocatalytic doping of organic semiconductors.

Chemical doping is an important approach to manipulating charge-carrier concentration and transport in organic semiconductors (OSCs)1-3 and ultimately enhances device performance4-7. However, conventional doping strategies often rely on the use of highly reactive (strong) dopants8-10, which are consumed during the doping process. Achieving efficient doping with weak and/or widely accessible dopants under mild conditions remains a considerable challenge. Here, we report a previously undescribed concept for the photocatalytic doping of OSCs that uses air as a weak oxidant (p-dopant) and operates at room temperature. This is a general approach that can be applied to various OSCs and photocatalysts, yielding electrical conductivities that exceed 3,000 S cm-1. We also demonstrate the successful photocatalytic reduction (n-doping) and simultaneous p-doping and n-doping of OSCs in which the organic salt used to maintain charge neutrality is the only chemical consumed. Our photocatalytic doping method offers great potential for advancing OSC doping and developing next-generation organic electronic devices.

Role of ERK in gender difference of fibromyalgia pain.

This study investigated the ERK pathway of the peripheral nervous system and discovered a gender-specific pattern of ERK activation in the dorsal root ganglion of an acid-induced chronic widespread muscular pain model. We employed a twice acid-induced chronic musculoskeletal pain model in rats to evaluate mechanical pain behavior in both male and female groups. We further conducted protein analysis of dissected dorsal root ganglions from both genders. Both male and female rats exhibited a similar pain behavior trend, with females demonstrating a lower pain threshold. Protein analysis of the dorsal root ganglion (DRG) showed a significant increase in phosphorylated ERK after the second acid injection in all groups. However, phosphorylation of ERK was observed in the dorsal root ganglion, with higher levels in the male ipsilateral group compared to the female group. Moreover, there was a no difference between the left and right sides in males, whereas the significant difference was observed in females. In conclusions, the administration of acid injections induced painful behavior in rats, and concurrent with this, a significant upregulation of pERK was observed in the dorsal root ganglia, with a greater magnitude of increase in males than females, and in the contralateral side compared to the ipsilateral side. Our findings shed light on the peripheral mechanisms underlying chronic pain disorders and offer potential avenues for therapeutic intervention.

A Highly Conductive n-Type Conjugated Polymer Synthesized in Water.

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is a benchmark hole-transporting (p-type) polymer that finds applications in diverse electronic devices. Most of its success is due to its facile synthesis in water, exceptional processability from aqueous solutions, and outstanding electrical performance in ambient. Applications in fields like (opto-)electronics, bioelectronics, and energy harvesting/storage devices often necessitate the complementary use of both p-type and n-type (electron-transporting) materials. However, the availability of n-type materials amenable to water-based polymerization and processing remains limited. Herein, we present a novel synthesis method enabling direct polymerization in water, yielding a highly conductive, water-processable n-type conjugated polymer, namely, poly[(2,2'-(2,5-dihydroxy-1,4-phenylene)diacetic acid)-stat-3,7-dihydrobenzo[1,2-b:4,5-b']difuran-2,6-dione] (PDADF), with remarkable electrical conductivity as high as 66 S cm-1, ranking among the highest for n-type polymers processed using green solvents. The new n-type polymer PDADF also exhibits outstanding stability, maintaining 90% of its initial conductivity after 146 days of storage in air. Our synthetic approach, along with the novel polymer it yields, promises significant advancements for the sustainable development of organic electronic materials and devices.

Necessary for seizure forecasting outcome metrics: seizure frequency and benchmark model.

Work is ongoing to advance seizure forecasting, but the performance metrics used to evaluate model effectiveness can sometimes lead to misleading outcomes. For example, some metrics improve when tested on patients with a particular range of seizure frequencies (SF). This study illustrates the connection between SF and metrics. Additionally, we compared benchmarks for testing performance: a moving average (MA) or the commonly used permutation benchmark. Three data sets were used for the evaluations: (1) Self-reported seizure diaries of 3,994 Seizure Tracker patients; (2) Automatically detected (and sometimes manually reported or edited) generalized tonic-clonic seizures from 2,350 Empatica Embrace 2 and Mate App seizure diary users, and (3) Simulated datasets with varying SFs. Metrics of calibration and discrimination were computed for each dataset, comparing MA and permutation performance across SF values. Most metrics were found to depend on SF. The MA model outperformed or matched the permutation model in all cases. The findings highlight SF's role in seizure forecasting accuracy and the MA model's suitability as a benchmark. This underscores the need for considering patient SF in forecasting studies and suggests the MA model may provide a better standard for evaluating future seizure forecasting models.

Comparative CKD risk prediction using homocitrulline and carbamylated albumin: two circulating markers of protein carbamylation.

BACKGROUND: Protein carbamylation, a post-translational protein modification primarily driven by urea, independently associates with adverse clinical outcomes in patients with CKD. Biomarkers used to quantify carbamylation burden have mainly included carbamylated albumin (C-Alb) and homocitrulline (HCit, carbamylated lysine). In this study, we aimed to compare the prognostic utility of these two markers in order to facilitate comparisons of existing studies employing either marker alone, and to inform future carbamylation studies. METHODS: Both serum C-Alb and free HCit levels were assayed from the same timepoint in 1632 individuals with CKD stages 2-4 enrolled in the prospective Chronic Renal Insufficiency Cohort (CRIC) study. Adjusted Cox proportional hazard models were used to assess risks for the outcomes of death (primary) and end stage kidney disease (ESKD) using each marker. C-statistics, net reclassification improvement, and integrated discrimination improvement were used to compare the prognostic value of each marker. RESULTS: Participant demographics included mean (SD) age 59 (11) years; 702 (43%) females; 700 (43%) white. C-Alb and HCit levels were positively correlated with one another (Pearson correlation coefficient 0.64). Higher C-Alb and HCit levels showed similar increased risk of death (e.g., the adjusted hazard ratio [HR] for death in the 4th carbamylation quartile compared to the 1st was 1.90 (95% confidence interval [CI] 1.35-2.66) for C-Alb, and 1.89 [1.27-2.81] for HCit; and on a continuous scale, the adjusted HR for death using C-Alb was 1.24 [1.11 to 1.39] per standard deviation increase, and 1.27 [1.10-1.46] using HCit). Both biomarkers also had similar HRs for ESKD. The C-statistics were similar when adding each carbamylation biomarker to base models (e.g., for mortality models, the C-statistic was 0.725 [0.707-0.743] with C-Alb and 0.725 [0.707-0.743] with HCit, both compared to a base model 0.723). Similarities were also observed for the net reclassification improvement and integrated discrimination improvement metrics. CONCLUSIONS: C-Alb and HCit had similar performance across multiple prognostic assessments. The markers appear readily comparable in CKD epidemiological studies.

Unlocking the potential of biochar: an iron-phosphorus-based composite modified adsorbent for adsorption of Pb(II) and Cd(II) in aqueous environments and response surface optimization of adsorption conditions.

In this work, iron-phosphorus based composite biochar (FPBC) was prepared by modification with potassium phosphate and iron oxides for the removal of heavy metal ions from single and mixed heavy metal (Pb and Cd) solutions. FTIR and XPS characterization experiments showed that the novel modified biochar had a greater number of surface functional groups compared to the pristine biochar. The maximum adsorption capacities of FPBC for Pb(II) and Cd(II) were 211.66 mg·g-1 and 94.08 mg·g-1 at 293 K. The adsorption of Pb(II) and Cd(II) by FPBC followed the proposed two-step adsorption kinetic model and the Freundlich isothermal adsorption model, suggesting that the mechanism of adsorption of Pb(II) and Cd(II) by FPBC involved chemical adsorption of multiple layers. Mechanistic studies showed that the introduction of -PO4 and -PO3 chemisorbed with Pb(II) and Cd(II), and the introduction of -Fe-O increased the ion exchange with Pb(II) and Cd(II) during the adsorption process and produced precipitates such as Pb3Fe(PO4)3 and Cd5Fe2(P2O7)4. Additionally, the abundant -OH and -COOH groups also participated in the removal of Pb(II) and Cd(II). In addition, FPBC demonstrated strong selective adsorption of Pb(II) in mixed heavy metal solutions. The Response Surface Methodology(RSM) analysis determined the optimal adsorption conditions for FPBC as pH 5.31, temperature 26.01 °C, and Pb(II) concentration 306.30 mg·L-1 for Pb(II). Similarly, the optimal adsorption conditions for Cd(II) were found to be pH 5.66, temperature 39.34 °C, and Cd(II) concentration 267.68 mg·L-1. Therefore, FPBC has the potential for application as a composite-modified adsorbent for the adsorption of multiple heavy metal ions.

A Rare Case of Atypical Hemolytic Uremic Syndrome (aHUS) Precipitated by Dengue and the Treatment Landscape in Singapore.

Atypical hemolytic uremic syndrome (aHUS) is a rare disease caused by uncontrolled complement activation due to complement dysregulation. It is often triggered by precipitating events such as infections, inflammation, pregnancy, or medications. Dengue, an endemic viral infection in Southeast Asia, can activate the complement pathway, thereby triggering aHUS in genetically susceptible individuals. Here, we present the case of a 33-year-old male who presented with Dengue fever and subsequently developed aHUS. Plasma exchange (PLEX) successfully normalized his neurological status and hematological parameters. Although his renal function improved, it failed to normalize. Eculizumab, a monoclonal antibody that inhibits C5, was administered for a total of six months. The treatment was successfully discontinued without evidence of relapse after six months of follow-up. This case report demonstrates the safety of discontinuing eculizumab in patients who do not possess pathogenic mutations or variants in complement factors.