Prevalência de Influenza A, vírus sincicial respiratório eSARS-CoV-2 em pacientes com síndrome respiratóriaaguda grave em Passo Fundo, Rio Grande do Sul / Prevalence of Influenza A, respiratory syncytial virus andSARS-CoV-2 in patients with severe acute respiratorysyndrome in Passo Fundo, Rio Grande do Sul

A síndrome respiratória aguda grave (SRAG) é caracterizada por sintomas de febre alta, tosse e dispneia, e, na maioria dos casos, relacionada a uma quantidade reduzida de agentes infecciosos. O objetivo foi avaliar a prevalência dos vírus respiratórios Influenza A (FluA), vírus sincicial respiratório (RSV) e do novo coronavírus (SARS-CoV-2) em pacientes com internação hospitalar por SRAG. Estudo transversal, com pacientes em internação hospitalar com SRAG entre novembro de 2021 e maio de 2022. Dados sociodemográficos e clínicos e amostras da nasofaringe foram coletados/as, as quais foram submetidas à extração de RNA e testadas quanto à positividade para Influenza A, RSV e SARS-CoV-2 por meio da técnica de PCR em tempo real pelo método SYBR Green. Foram incluídos 42 pacientes, sendo 59,5% do sexo feminino, 57,1% idosos, 54,8% com ensino fundamental. A maior parte dos pacientes reportou hábito tabagista prévio ou atual (54,8%), não etilista (73,8%) e 83,3% deles apresentavam alguma comorbidade, sendo hipertensão arterial sistêmica e diabetes mellitus tipo 2 as mais prevalentes. Um total de 10,5% dos pacientes testou positivo para FluA, nenhuma amostra positiva para RSV e 76,3% positivos para SARS-CoV-2. Na população estudada, SRAG com agravo hospitalar foi observado em maior proporção, em mulheres, idosos e pessoas com comorbidades, embora sem significância estatística, sendo o novo coronavírus o agente etiológico mais relacionado, o que evidencia a patogenicidade desse agente e suas consequências ainda são evidentes após quase 2 anos de período pandêmico.

Severe acute respiratory syndrome (SARS) is characterized by symptoms of high fever, cough and dyspnea, and is in most cases related to a reduced amount of infectious agents. The objective was to assess the prevalence of respiratory viruses Influenza A (FluA), respiratory syncytial virus (RSV) and the new coronavirus (SARS-CoV-2) in patients hospitalized for SARS. Cross-sectional study, with patients hospitalized with SARS between November 2021 and May 2022. Sociodemographic and clinical data and nasopharyngeal samples were collected, which were subjected to RNA extraction and tested for positivity for Influenza A, RSV and SARS-CoV-2 using the real-time PCR technique using the SYBR Green method. 42 patients were included, 59.5% female, 57.1% elderly, 54.8% with primary education. Most patients reported previous or current smoking habits (54.8%), non-drinkers (73.8) and 83.3% of them had some comorbidity, with systemic arterial hypertension and type 2 diabetes mellitus being the most prevalent. A total of 10.5% of patients tested positive for FluA, no samples positive for RSV, and 76.3% positive for SARS-CoV-2. In the studied population, SARS with hospital injury was observed more frequently in women and the elderly, with associated comorbidities, with the new coronavirus being the most related etiological agent, which shows, although not statistically significant, that the pathogenicity of this agent and its consequences are still evident after almost 2 years of period pandemic.

Real-world impact of acupuncture on analgesics and healthcare resource utilization in breast cancer survivors with pain.

BACKGROUND: This study evaluated the real-world impact of acupuncture on analgesics and healthcare resource utilization among breast cancer survivors. METHODS: From a United States (US) commercial claims database (25% random sample of IQVIA PharMetrics® Plus for Academics), we selected 18-63 years old malignant breast cancer survivors experiencing pain and ≥ 1 year removed from cancer diagnosis. Using the difference-in-difference technique, annualized changes in analgesics [prevalence, rates of short-term (< 30-day supply) and long-term (≥ 30-day supply) prescription fills] and healthcare resource utilization (healthcare costs, hospitalizations, and emergency department visits) were compared between acupuncture-treated and non-treated patients. RESULTS: Among 495 (3%) acupuncture-treated patients (median age: 55 years, stage 4: 12%, average 2.5 years post cancer diagnosis), most had commercial health insurance (92%) and experiencing musculoskeletal pain (98%). Twenty-seven percent were receiving antidepressants and 3% completed ≥ 2 long-term prescription fills of opioids. Prevalence of opioid usage reduced from 29 to 19% (P < 0.001) and NSAID usage reduced from 21 to 14% (P = 0.001) post-acupuncture. The relative prevalence of opioid and NSAID use decreased by 20% (P < 0.05) and 19% (P = 0.07), respectively, in the acupuncture-treated group compared to non-treated patients (n = 16,129). However, the reductions were not statistically significant after adjustment for confounding. Patients receiving acupuncture for pain (n = 264, 53%) were found with a relative decrease by 47% and 49% (both P < 0.05) in short-term opioid and NSAID fills compared to those treated for other conditions. High-utilization patients (≥ 10 acupuncture sessions, n = 178, 36%) were observed with a significant reduction in total healthcare costs (P < 0.001) unlike low-utilization patients. CONCLUSIONS: Although adjusted results did not show that patients receiving acupuncture had better outcomes than non-treated patients, exploratory analyses revealed that patients treated specifically for pain used fewer analgesics and those with high acupuncture utilization incurred lower healthcare costs. Further studies are required to examine acupuncture effectiveness in real-world settings.

Cross-step detection using center-of-pressure based algorithm for real-time applications.

BACKGROUND: Gait event detection is crucial for assessment, evaluation and provision of biofeedback during rehabilitation of walking. Existing online gait event detection algorithms mostly rely on add-on sensors, limiting their practicality. Instrumented treadmills offer a promising alternative by utilizing the Center of Pressure (CoP) signal for real-time gait event detection. However, current methods have limitations, particularly in detecting cross-step events during perturbed walking conditions. METHODS: We present and validate a CoP-based algorithm to detect gait events and cross-steps in real-time, which combines thresholding and logic techniques. The algorithm was evaluated on CoP datasets from healthy participants (age range 21-61 years), stroke survivors (age range 20-67 years), and people with unilateral transtibial amputation (age range 28-63 years) that underwent perturbation-based balance assessments, encompassing different walking speeds. Detected gait events from a simulated real-time processing operation were compared to offline identified counterparts in order to present related temporal absolute mean errors (AME) and success rate. RESULTS: The proposed algorithm demonstrated high accuracy in detecting gait events during native gait, as well as cross-step events during perturbed walking conditions. It successfully recognized the majority of cross-steps, with a detection success rate of 94%. However, some misclassifications or missed events occurred, mainly due to the complexity of cross-step events. AME for heel strikes (HS) during native gait and cross-step events averaged at 78 ms and 64 ms respectively, while toe off (TO) AME were 126 ms and 111 ms respectively. A statistically significant difference in the algorithm's success rate score in detecting gait events during cross-step intervals was observed across various walking speeds in a sample of 12 healthy participants, while there was no significant difference among groups. CONCLUSION: The proposed algorithm represents an advancement in gait event detection on instrumented treadmills. By leveraging the CoP signal, it successfully identifies gait events and cross-steps in the simulated real-time processing operation, providing valuable insights into human locomotion. The algorithm's ability to accommodate diverse CoP patterns enhance its applicability to a wide range of individuals and gait characteristics. The algorithm's performance was consistent across different populations, suggesting its potential for diverse clinical and research settings, particularly in the domains of gait analysis and rehabilitation practices.

Transcranial focused ultrasound stimulation enhances cerebrospinal fluid movement: Real-time in vivo two-photon and widefield imaging evidence.

BACKGROUND: Cerebrospinal fluid (CSF) flow is crucial for brain homeostasis and its dysfunction is highly associated with neurodegenerative diseases. Restoring CSF circulation is proposed as a key strategy for the treatment of the diseases. Among the methods to improve CSF circulation, focused ultrasound (FUS) stimulation has emerged as a promising non-invasive brain stimulation technique, with effectiveness evidenced by ex vivo studies. However, due to technical disturbances in in vivo imaging combined with FUS, direct evidence of real-time in vivo CSF flow enhancement by FUS remains elusive. OBJECTIVE: To investigate whether FUS administered through the skull base can enhance CSF influx in living animals with various real-time imaging techniques. METHODS: We demonstrate a novel method of applying FUS through the skull base, facilitating cortical CSF influx, evidenced by diverse in vivo imaging techniques. Acoustic simulation confirmed effective sonication of our approach through the skull base. After injecting fluorescent CSF tracers into cisterna magna, FUS was administered at the midline of the jaw through the skull base for 30 min, during which imaging was performed concurrently. RESULTS: Enhanced CSF influx was observed in macroscopic imaging, demonstrated by the influx area and intensity of the fluorescent dyes after FUS. In two-photon imaging, increased fluorescence was observed in the perivascular space (PVS) after stimulation. Moreover, particle tracking of microspheres showed more microspheres entering the imaging field, with increased mean speed after FUS. CONCLUSION: Our findings provide direct real-time in vivo imaging evidence that FUS promotes CSF influx and flow in the PVS.

Utilizing a optimized method for evaluating vapor recovery equipment control efficiency and estimating evaporative VOC emissions from urban oil depots via an extensive survey.

As an important intermediary between upstream refineries and downstream urban gas stations, volatile organic compound (VOC) emissions from urban oil depots were often disregarded, underestimating their environmental and health implications. An extensive investigation of urban depots' fuel composition and operational dynamics was conducted nationwide. We developed a novel approach that integrates theoretical models with easily measurable operational data from the depots to evaluate the efficiency of post-treatment devices in actual situations. Even in well-managed oil depots, the actual control efficiency of vapor recovery units fluctuates between 63 % and 85 %, depending on the concentration of hydrocarbon vapors in the intake of the device. The national emission factors for gasoline, diesel, and aviation kerosene at a national level were 6.64 ± 1.16, 2.07 ± 0.42, and 6.17 ± 1.05 tons per 10,000 tons, respectively. In 2019, China's urban oil depots emitted 165 thousand tons of VOC. Enhancing control strategies by optimizing the physical and chemical parameters of refined oil, improving storage capacity and turnover efficiency, and upgrading storage tanks had the potential to reduce emissions by more than 60 %. However, a 30 % failure rate in these systems could negate the benefits of these improved strategies.

Sequential vs. concurrent systemic therapies in combination with FOLFOX-HAIC for locally advanced hepatocellular carcinoma: a single-center, real-world cohort study.

BACKGROUND: Tri-combination therapy based on hepatic arterial infusion chemotherapy (HAIC) of infusion fluorouracil, leucovorin, and oxaliplatin (FOLFOX-HAIC) plus immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) for the locally advanced hepatocellular carcinoma (HCC) patients have been proven effective. However, whether it was best for these HCC patients to start with the most potent therapeutic pattern was still under debate. This retrospective study evaluated the efficacy and safety of FOLFOX-HAIC combined with systemic therapies in the patterns of sequential and concurrent schedules. METHODS: This real-world study included 117 unresectable HCC patients who initially received either FOLFOX-HAIC monotherapy (HAIC group, n = 44) or concurrent ICIs and TKIs (ConHAIC group, n = 73) from March 2020 and June 2022, during the period of FOLFOX-HAIC monotherapy in HAIC group, patients in the HAIC group (n = 30) experienced progressive disease (PD) would have their treatment pattern converted from the FOLFOX-HAIC monotherapy to the combination of FOLFOX-HAIC plus ICIs and TKIs sequentially (SeqHAIC group). The progression-free survival (PFS) and overall survival (OS), as primary outcomes, were compared between patients in the SeqHAIC and ConHAIC groups. RESULTS: The median follow-up time of the SeqHAIC group was 24.92 months (95% CI, 12.74-37.09 months) and of the ConHAIC group was 17.87 months (95% CI, 16.85-18.89 months) and no significant difference was observed in both PFS (HR, 1.572; 95% CI, 0.848-2.916; p = 0.151) and OS (HR, 1.212; 95% CI, 0.574-2.561; p = 0.614) between the SeqHAIC and the ConHAIC groups. As for the tumor responses, there was no significant difference between the two groups regarding tumor responses, overall response rates (p = 0.658) and disease control rates (p = 0.641) were 50.0%, 45.2%, and 83.3%, 89.0% for the SeqHAIC and the ConHAIC groups, respectively. CONCLUSION: Our study revealed that sequential systemic ICIs and TKIs in combination with FOLFOX-HAIC provides similar long-term prognosis and better tolerability compared to concurrent therapy for locally advanced HCC patients. Prospective studies with a larger sample size and longer follow-up are required to validate these findings.

Real-world data to support post-market safety and performance of embolization coils: evidence generation from a medical device manufacturer and data institute partnership.

BACKGROUND: Recognizing the limitations of pre-market clinical data, regulatory authorities have embraced total product lifecycle management with post-market surveillance (PMS) data to assess medical device safety and performance. One method of proactive PMS involves the analysis of real-world data (RWD) through retrospective review of electronic health records (EHR). Because EHRs are patient-centered and focused on providing tools that clinicians use to determine care rather than collecting information on individual medical products, the process of transforming RWD into real-world evidence (RWE) can be laborious, particularly for medical devices with broad clinical use and extended clinical follow-up. This study describes a method to extract RWD from EHR to generate RWE on the safety and performance of embolization coils. METHODS: Through a partnership between a non-profit data institute and a medical device manufacturer, information on implantable embolization coils' use was extracted, linked, and analyzed from clinical data housed in an electronic data warehouse from the state of Indiana's largest health system. To evaluate the performance and safety of the embolization coils, technical success and safety were defined as per the Society of Interventional Radiology guidelines. A multi-prong strategy including electronic and manual review of unstructured (clinical chart notes) and structured data (International Classification of Disease codes), was developed to identify patients with relevant devices and extract data related to the endpoints. RESULTS: A total of 323 patients were identified as treated using Cook Medical Tornado, Nester, or MReye embolization coils between 1 January 2014 and 31 December 2018. Available clinical follow-up for these patients was 1127 ± 719 days. Indications for use, adverse events, and procedural success rates were identified via automated extraction of structured data along with review of available unstructured data. The overall technical success rate was 96.7%, and the safety events rate was 5.3% with 18 major adverse events in 17 patients. The calculated technical success and safety rates met pre-established performance goals (≥ 85% for technical success and ≤ 12% for safety), highlighting the relevance of this surveillance method. CONCLUSIONS: Generating RWE from RWD requires careful planning and execution. The process described herein provided valuable longitudinal data for PMS of real-world device safety and performance. This cost-effective approach can be translated to other medical devices and similar RWD database systems.

Personalized sleep and nutritional strategies to combat adverse effects of night shift work: a controlled intervention protocol.

BACKGROUND: Working during the night interferes with the timing of normal daily activities and is associated with an increased risk of chronic diseases. Under controlled experimental conditions, interventions focusing on sleep and nutrition can mitigate the short-term adverse effects of shift work. However, it is unclear how these results translate to real-life, how they can be targeted to individual conditions, and how they relate to long-term health. Therefore, the current study aims to implement a personalized sleep and nutritional intervention among night shift workers in the field. METHODS: A non-blinded controlled intervention study is used, consisting of a run-in period, an intervention of 3 months, post-intervention measurements, and a follow-up after 12 months. Three study arms are included: sleep intervention, nutritional intervention, and control group (n = 25 each). Participants are healthy 18-60-year male night shift workers, with at least one year of experience in night shift work. Information from the run-in period will be used to personalize the interventions. The main outcomes are sleep measurements and continuous interstitial glucose levels. Furthermore, general health biomarkers and parameters will be determined to further evaluate effects on long-term health. DISCUSSION: This study aims to mitigate negative health consequences associated with night shift work by introducing two personalized preventive interventions. If proven effective, the personalized interventions may serve as practical solutions that can have a meaningful impact on the sustainable health and employability of night shift workers. This study will thereby contribute to the current need for high-quality data on preventative strategies for night shift work in a real-life context. TRIAL REGISTRATION: This trial has been registered under ClinicalTrials.gov Identifier NCT06147089. Registered 27 November 2023.

Model order reduction and sensitivity analysis for complex heat transfer simulations inside the human eyeball.

Heat transfer in the human eyeball, a complex organ, is significantly influenced by various pathophysiological and external parameters. Particularly, heat transfer critically affects fluid behavior within the eye and ocular drug delivery processes. Overcoming the challenges of experimental analysis, this study introduces a comprehensive three-dimensional mathematical and computational model to simulate the heat transfer in a realistic geometry. Our work includes an extensive sensitivity analysis to address uncertainties and delineate the impact of different variables on heat distribution in ocular tissues. To manage the model's complexity, we employed a very fast model reduction technique with certified sharp error bounds, ensuring computational efficiency without compromising accuracy. Our results demonstrate remarkable consistency with experimental observations and align closely with existing numerical findings in the literature. Crucially, our findings underscore the significant role of blood flow and environmental conditions, particularly in the eye's internal tissues. Clinically, this model offers a promising tool for examining the temperature-related effects of various therapeutic interventions on the eye. Such insights are invaluable for optimizing treatment strategies in ophthalmology.

Polyvinylpyrrolidone capped silver nanoparticles enhance the autophagic clearance of Acinetobacter baumannii from human pulmonary cells.

Acinetobacter baumannii, an opportunistic pathogen has shown an upsurge in its multi-drug resistant isolates. OmpA of A. baumannii induces incomplete autophagy and apoptosis in host cells. Various therapeutic alternatives are under investigation against A. baumannii. Here, the major emphasis has been laid on comparing the efficacy of AgNP with different capping agents. OmpA targeted lead, Ivermectin capped AgNP (IVM-AgNP) has been compared with the antibacterial polyvinylpyrrolidone capped AgNP (PVP-AgNP) for their role in the modulations of host autophagy. Upregulation of p62 and LC3B confirmed by real-time PCR analysis indicated an increased autophagic flux upon the treatment with AgNPs. The elongation and closure of autophagic vacuoles was also supported by upregulated Atg genes (Atg4, Atg3, Atg5) in A. baumannii infected cells after treatment with AgNP. Autophagic flux increased on treatment with PVP-AgNP as suggested by the rise in mcherryLC3B fluorescence in A549 cells treated with PVP-AgNP as compared to the GFP-LC3B of IVM-AgNP. This suggests that PVP-AgNP treatment more effectively promotes the elongation and maturation stages of autophagy by increasing autophagic flux. These results indicate that capped AgNPs have the efficiency to revert the incomplete autophagy induced by A. baumannii back to normal autophagic levels.

Real-world assessment of comprehensive genome profiling impact on clinical outcomes: A single-institution study in Japan.

INTRODUCTION: Comprehensive genome profiling (CGP) has revolutionized healthcare by offering personalized medicine opportunities. However, its real-world utility and impact remain incompletely understood. This study examined the extent to which CGP leads to genomically matched therapy and its effectiveness. METHODS: We analyzed data from advanced solid tumor patients who underwent CGP panel between December 2019 and May 2023 at the Osaka International Cancer Institute. Patient demographics, specimen details, and expert panel assessments were collected. Turnaround time (TAT) and genomically matched therapy outcomes were analyzed. Gene alterations and their co-occurrence patterns were also assessed. RESULTS: Among 1437 patients, 1096 results were available for analysis. The median TAT was 63 [28-182] days. There were 667 (60.9%) cases wherein recommended clinical trials were presented and there were 12 (1.1%) cases that could be enrolled in the trial and 25 (2.3%) cases that could lead to therapies under insurance reimbursement. The median progression free survival of the trial treatment was 1.58 months (95% CI: 0.66-4.37) in clinical trials and 3.66 months (95% CI: 2.14-7.13) in treatment under insurance. Pathologic germline variants were confirmed in 15 patients (1.3%). Co-alteration of CDKN2A, CDKN2B, and MTAP was significantly observed in overall population. CONCLUSION: The effectiveness of the genomically matched therapy based on the CGP panel was unsatisfactory. Expansion of clinical trials and utilization of remote clinical trials are required to ensure that the results of the CGP panel can be fully returned to patients.

Characteristics and real-world medication persistence of people living with HIV treated with DTG/3TC or BIC/FTC/TAF: a hospital claims database study in Japan.

Background: As the life expectancy of people living with human immunodeficiency virus (HIV) (PLWH) has improved, chronic disease burden and polypharmacy have increased in PLWH. Simplification of the antiretroviral therapy (ART) regimen for PLWH has become crucial. The real-world treatment patterns and medication persistence of the 2-drug single-tablet regimen (STR), dolutegravir/lamivudine (DTG/3TC), compared to bictegravir/emtricitabine/tenofovir alafenamide (BIC/FTC/TAF) prescribed were investigated. Methods: This retrospective, database study extracted data from a hospital-based medical claims database in Japan. The changes in ART distributions by year during the identification period between January 1, 2018 and December 31, 2021 were observed. Patients with disease record of HIV-1 infection and prescribed DTG/3TC or BIC/FTC/TAF as the first prescription of STR during the identification period were divided into two cohorts; DTG/3TC cohort and BIC/FTC/TAF cohort, respectively. Patient without medication records more than 3 months and no future data more than 6 months were excluded. Patients' characteristics were compared between the DTG/3TC cohort and the BIC/FTC/TAF cohort by Mantel-Haenszel test to adjust for age. Medication persistence was compared between the two cohorts by evaluating the continuation rates using Kaplan-Meier methods, using the log-rank test to assess the difference between the Kaplan-Meier curves. The median time-to-first prescription was compared between the two cohorts by Kaplan-Meier methods. Results: Prescriptions of DTG/3TC and BIC/FTC/TAF increased steadily from 2019 to 2021 after the release year of each STR. There was no significant difference in the time-to-first prescription (p = 0.3). A total of 959 patients were included, with 120 patients and 839 patients on DTG/3TC and BIC/FTC/TAF, respectively. The proportion of dyslipidemia at baseline was significantly higher in the DTG/3TC cohort than in the BIC/FTC/TAF cohort after adjusting for mean age (p = 0.002). There was no significant difference in medication persistence between the two cohorts (p = 0.91). Conclusion: This study showed that DTG/3TC was likely to be selected for elderly patients and those with chronic disease in real-world clinical practice, which seems in accordance with the treatment strategy recommended by guidelines. Comparable medication persistence was observed with both regimens, aligning with findings from other countries. The 2-drug single-tablet regimen DTG/3TC may be an important ART regimen for PLWH with multiple morbidities and polypharmacy in an aging society. Due to the limitations of the database, further research to assess viral loads, emergence of resistance and adverse events will be encouraged.

Real-World Experience With Janus Kinase Inhibitors in Immune-Mediated Diseases: Clinical Experience of a University Hospital.

BACKGROUND: Several Janus kinase (JAK) inhibitors have been developed in recent years. These agents are widely applicable in clinical practice as an alternative treatment for immune-mediated diseases. While the safety and efficacy profile of these drugs has been evaluated in several randomized clinical trials and studies, very few authors have assessed safety and effectiveness under the real-world conditions of daily clinical practice. OBJECTIVE: This study aims to describe the effectiveness and safety of JAK inhibitors in daily clinical practice for the treatment of immune-mediated rheumatic diseases in a university hospital. METHODS: We performed a single-center observational, descriptive, retrospective study of all patients with rheumatoid arthritis (RA), spondyloarthritis (SpA), and psoriatic arthritis (PsA) receiving active treatment with JAK inhibitors between March 2022 and February 2023. We recorded study variables from the clinical history for subsequent analysis using STATA 12.0 (StataCorp LLC, College Station, TX). A 95% confidence interval was applied. RESULTS: The final analysis was performed on 64 patients (upadacitinib: 27, baricitinib: 16, tofacitinib: 13, filgotinib: eight), with a mean age of 55.69±10.78 years (60.94% females). The distribution by disease was as follows: RA, 44 (70.31%); SpA, 11 (17.18%); and PsA, eight (12.5%). A significant improvement was observed in all groups at six to 12 months, as follows: RA, remission in 48.89% and low activity in 26.67%; SpA, remission in 9.09% and low activity in 54.54%; and PsA, low activity in 87.5%. The factors most associated with poor response to treatment were activity before initiation of treatment and previous failure of biological disease-modifying antirheumatic drugs (bDMARDs). Adverse effects and complications were detected in 26.56% (SARS-CoV-2, one case; basal cell carcinoma, one case; and herpes zoster, two cases). There were no reports of cardiovascular or thromboembolic events, opportunistic infection, or tuberculosis. CONCLUSIONS: Our real-world data show that treatment with JAK inhibitors leads to a high rate of remission/low activity that remains unchanged at six to 12 months in RA, SpA, and PsA. The predictors of a poor response to JAK inhibitors in our study population were the level of activity before initiation of treatment and previous failure of bDMARDs. No cardiovascular or thromboembolic events were reported. Of note, we did record one case of severe infection, one case of basal cell carcinoma, and two cases of herpes zoster.

Development and collaborative validation of an event-specific quantitative real-time PCR method for detection of genetically modified CC-2 maize.

As one of the developed genetically modified (GM) maize varieties in China, CC-2 has demonstrated promising commercial prospects during demonstration planting. The establishment of detection methods is a technical prerequisite for effective supervision and regulation of CC-2 maize. In this study, we have developed an event-specific quantification method that targets the junction region between the exogenous gene and the 5' flanking genomic DNA (gDNA) of CC-2. The accuracy and precision of this method were evaluated across high, medium, and low levels of CC-2 maize content, revealing biases within ±25% and satisfactory precision data. Additionally, we determined the limits of quantification of the method to be 0.05% (equivalent to 20 copies) of the CC-2 maize. A collaborative trial further confirmed that our event-specific method for detecting CC-2 produces reliable, comparable, and reproducible results when applied to five different samples provided by various sources. Furthermore, we calculated the expanded uncertainty associated with determining the content level of CC-2 in these samples.

Information density threshold of urban road traffic signs based on visual comfort.

The content and density of traffic signs directly affect the operation of urban road traffic and drivers. To overcome the limitations of quantitative research on the density threshold of traffic signs on urban roads, a real vehicle experiment was conducted to record the psychological characteristics of drivers. Four psychological parameters of drivers-pupil area, fixation intensity, heart rate change rate, and heart rate variability-were explored. Subsequently, principal component analysis was used to present a new index, S, divided into 5 grade scales, to represent the driving visual comfort level. The information entropy theory was applied to quantify the amount of information on road traffic signs that are included in driving tests, and a regression relationship between the traffic sign information and comfort index S was established. The visual psychological load thresholds for different comfort levels were -2.289≤S < -1.526 for very comfortable, 1.526≤S < -0.763 for relatively comfortable, -0.763≤S ≤ 0.763 for comfortable, 0.763

Effect of a prescription digital therapeutic for chronic insomnia on post-treatment insomnia severity, depression, and anxiety symptoms: results from the real-world DREAM study.

Introduction: Chronic insomnia is a substantial public health burden that often presents with co-occurring depression and anxiety. Randomized clinical trials and preliminary real-world evidence have shown that digitally delivered cognitive-behavioral therapy for insomnia (dCBT-I) is associated with improvements in insomnia, but real-world evidence is needed to determine the true impact of digital CBT-I. This pragmatic study aimed to evaluate the benefits of treating chronic insomnia with a tailored prescription digital therapeutic in a real-world population. Methods: This prospective, single-arm clinical study involved adults aged 22-75 with chronic insomnia living in the US who had access to a mobile device. Participants accessed the FDA-cleared prescription digital therapeutic (PDT; Somryst®) over a 9-week intervention period. The PDT delivers cognitive-behavioral therapy for insomnia via six interactive treatment cores and daily sleep diaries used for tailoring treatment. Participants completed validated patient-reported instruments at baseline, before completing treatment cores, immediately post-intervention, and at 6-month and 1-year follow-ups. The Insomnia Severity Index [ISI], the 8-item Patient Health Questionnaire [PHQ-8], and the Generalized Anxiety Disorder-7 scale [GAD-7] were used to determine the effect of the PDT on insomnia, depression, and anxiety. Results: After screening, 1565 adults accessed the PDT. 58% of those who began the program completed Core 4, established as exposure to all mechanisms of action in the digital therapeutic. For those who completed assessments for all 6 cores (48.4%), the ISI was lowered from 18.8 to a mean of 9.9 (P <.001). These scores continued to be lower than baseline at immediate post (11.0), 6-month (11.6), and 1-year follow-ups (12.2) (P <.001). The results of the PHQ-8 and GAD-7 also show significant decreases at all measured timepoints from baseline (P <.001). Of the patients that began the program, 908 (58.0%) were considered adherent and 733 (46.8%) completed all 6 cores. Conclusion: Data from the DREAM study contributes to the growing body of clinical evidence of how patients are utilizing a PDT in the real world, outside of controlled settings, offering insights for clinicians who use these therapeutics in practice. Clinical trial registration: ClinicalTrials.gov, identifier NCT04325464.

Lab-In-Fiber Optofluidic Device for Droplet Digital Polymerase Chain Reaction (DdPCR) with Real-Time Monitoring.

Droplet microfluidic systems have emerged as indispensable and advanced tools in contemporary biological science. A prominent example is the droplet digital polymerase chain reaction (ddPCR), which plays a pivotal role in next-generation sequencing and the detection of rare nucleic acids or mutations. However, existing optical detection configurations are bulky, intricate, and costly, and require meticulous optical alignment to optimize fluorescence sensing. Herein, we propose a lab-in-fiber optofluidic system (LiFO), which provides a stable and compact footprint, self-alignment, and enhanced optical coupling for high-accuracy ddPCR. Moreover, LiFO could expand its capabilities for multiangle-scattering light collection in which we collect focused forward-scattering light (fFSL) to enable real-time droplet counting and size monitoring. To accomplish these attributes, LiFO incorporates optical fibers, along with fabricated PDMS grooves, for a self-aligned optical setup to implement simultaneous fluorescence and scattering detection. Furthermore, LiFO harnesses the concept of flowing droplets functioning as microlenses, which allows us to collect and translate fFSL signals into droplet size information. We have demonstrated the effectiveness of LiFO in ddPCR applications, illustrating its capacity to enhance the accuracy and precision of DNA quantification. Notably, LiFO exhibits improved linearity in the measurement of serial DNA dilutions, reflected by an increase in R2 from 0.956 to 0.997. These results demonstrate the potential of LiFO to serve as a valuable tool across a wide spectrum of droplet microfluidic platforms, offering opportunities for advancement in practical applications.

The interdependence of targets for continuous glucose monitoring outcomes in type 1 diabetes with automated insulin delivery.

AIM: The aim was to determine the interdependence of targets for glucose management indicator (GMI), time within the ranges of 70-180 mg/dL (TIR) and 70-140 mg/dL (time in tight glucose range [TITR]), time above 180 mg/dL (TA180) and 250 mg/dL (TA250) and time below 70 mg/dL (TB70) and 54 mg/dL (TB54) and its implications for setting targets in automated insulin delivery (AID). MATERIALS AND METHODS: Real-world data from individuals with type 1 diabetes using the 780G system were used to calculate the receiver operating characteristic curves and establish interdependent targets for time in ranges based on several GMI benchmarks. Correlation, regression and principal component analysis were used to determine their association and dimensionality. RESULTS: In individuals aged >15 years (n = 41 692), a GMI <6.5% required targets of >81%, >58%, <15% and <1.9% for TIR, TITR, TA180 and TA250, respectively, with high sensitivity, specificity and accuracy (>90%), whereas these values were poor for time in hypoglycaemia and GMI, which had a modest correlation (-0.21 to -0.43). Two dimensions emerged: (1) GMI, TIR, TITR, TA180 and TA250, and (2) TB70 and TB54, explaining 95% of total variability. GMI (or TIR) and TB70 explained >81% of the variability in the remaining continuous glucose monitoring (CGM) metrics, providing accurate predictions. Individuals aged ≤15 years (n = 14 459) showed similar results. CONCLUSION: We developed a methodology to establish interdependent CGM targets for therapies with CGM data outputs. In AID with the 780G system, a GMI <7% requires time in ranges close to consensus targets. Targets for GMI, TIR, TITR, TA180 and TA250 could be reduced to targets for GMI or TIR, whereas targets for time in hypoglycaemia are not inherently tied to GMI/TIR targets.

Real-word outcomes for high-risk non-muscle-invasive bladder cancer: screened patients for the BRAVO trial.

OBJECTIVE: To report real-world outcomes for high-risk non-muscle-invasive bladder cancer (HRNMIBC), including bacillus Calmette-Guérin (BCG) and radical cystectomy (RC), as randomised comparisons of these have not been possible. METHODS: We detail consecutive participants screened for the BRAVO randomised controlled trial comparing RC with BCG (International Standard Randomised Controlled Trial Number [ISRCTN]12509361). Patients were prospectively registered and case-note review used for outcomes. The primary outcome was overall survival. Secondary outcomes included recurrence, progression, metastasis, and bladder cancer-specific survival. RESULTS AND LIMITATIONS: A total of 193 patients were screened, including 106 (54.9%) who received BCG, 43 (22.3%) primary RC, 37 (19.2%) 'other' treatment and seven (3.6%) hyperthermic intravesical mitomycin C. All-cause death occurred in 55 (28.5%) patients at median (interquartile range [IQR]) of 29.0 (19.5-42.0) months. In multivariable analysis, overall mortality was more common in older patients (hazard ratio [HR] 2.63, 95% confidence interval [CI] 1.35-5.13; Cox P = 0.004 for age >70 years), those recruited from district hospitals (HR 0.53, 95% CI 0.3-0.95; P = 0.032) and those who did not undergo RC as their first treatment (HR 2.16, 95% CI 1.17-3.99; P = 0.014). In all, 17 (8.8%) patients died from bladder cancer (BC) at median (IQR) of 22.5 (19-36.25) months. In multivariable analysis, BC-specific mortality was more common in older patients (HR 4.87, 95% CI 1.1-21.6; P = 0.037) and those with Tis/T1 disease (HR 2.26, 95% CI 1.23-4.16; P = 0.008) but did not vary with initial treatment. CONCLUSIONS: Patients with HRNMIBC are at high-risk of mortality. Those choosing RC as their initial treatment have lower risks of mortality than others, although this may reflect fitness and selection.

A machine learning model for early diagnosis of type 1 Gaucher disease using real-life data.

OBJECTIVE: The diagnosis of Gaucher disease (GD) presents a major challenge due to the high variability and low specificity of its clinical characteristics, along with limited physician awareness of the disease's early symptoms. Early and accurate diagnosis is important to enable effective treatment decisions, prevent unnecessary testing, and facilitate genetic counseling. This study aimed to develop a machine learning (ML) model for GD screening and GD early diagnosis based on real-world clinical data using the Maccabi Healthcare Services electronic database, which contains 20 years of longitudinal data on approximately 2.6 million patients. STUDY DESIGN AND SETTING: We screened the Maccabi Healthcare Services database for patients with GD between January 1998 and May 2022. Eligible controls were matched by year of birth, sex, and socioeconomic status in a 1:13 ratio. The data were partitioned into 75% training and 25% test sets and trained to predict GD using features obtained from medical and laboratory records. Model performances were evaluated using the area under the receiver operating characteristic curve and the area under the precision-recall curve. RESULTS: We detected 264 confirmed patients with GD to which we matched 3,429 controls. The best model performance (which included known GD signs and symptoms, previously unknown clinical features, and administrative codes) on the test set had an area under the receiver operating characteristic curve = 0.95 ± 0.03 and area under the precision-recall curve = 0.80 ± 0.08, which yielded a median GD identification of 2.78 years earlier than the clinical diagnosis (25th-75th percentile: 1.29-4.53). CONCLUSION: Using an ML approach on real-world data led to excellent discrimination between GD patients and controls, with the ability to detect GD significantly earlier than the time of actual diagnosis. Hence, this approach might be useful as a screening tool for GD and lead to earlier diagnosis and treatment. Furthermore, advanced ML analytics may highlight previously unrecognized features associated with GD, including clinical diagnoses and health-seeking behaviors. PLAIN LANGUAGE SUMMARY: Diagnosing Gaucher disease is difficult, which often leads to late or incorrect diagnoses. As a result, patients may undergo unnecessary tests and treatments and experience health deterioration despite medications availability for Gaucher disease. In this study, we used electronic health data to develop machine learning models for early diagnosis of Gaucher disease type 1. Our models, which included known Gaucher disease signs and symptoms, previously unknown clinical features, and administrative codes, were able to significantly outperform other models and expert opinions, detecting type 1 Gaucher disease 3 years on average before actual diagnosis. Our models also revealed new features linked to type 1 Gaucher disease, including specific diagnoses and patterns in patients' healthcare-seeking behaviors. We believe that the tool of machine learning can be valuable for patients with rare diseases.