Toxicity of Mucura (Petiveria alliacea) extracts from the peruvian amazon against Daphnia magna for environmental protection and sustainable development.

Natural products, specifically plant extracts with biological activity and the ability to act as botanical biopesticides are often mistakenly considered nontoxic. Scientific evidence indicates the contrary, and for this reason, the objective of this work was to evaluate the toxicity of extracts obtained from Petiveria alliacea L. (Caryophyllales, Phytolaccaceae) using Daphnia magna Straus (Cladocera, Daphniidae) as a bioindicator to identify the plant extracts and the respective concentrations that present the highest toxicity. Leaves of P. alliacea were collected in the Peruvian amazone. From this material, three types of extract (hexane, ethanolic and aqueous) were prepared, which were used in the bioassays with D. magna to find the least toxic extract. Acute toxicity bioassays with D. magna during 48 h of exposure to hexane, ethanolic, and aqueous extracts yielded median lethal concentration (LC50) values of 26.9, 230.6, and 657.9 mg L-1, respectively. The aqueous extract presented the lowest toxicity, causing minimal D. magna mortality in the range of 6.67 to 13.33% at concentrations of 10 and 100 mg L-1. This result enables the efficient use of this plant species in a sustainable manner with a minimal environmental impact for the future development of natural products for pest control.

Can 3D-printed patient-specific instruments improve local control and overall survival in pelvic sarcoma? A clinical validation study. / Guías impresas en 3D: ¿mejoran el control local y la supervivencia global en el tratamiento de los sarcomas pélvicos? Estudio de validación clínica.

BACKGROUND AND OBJECTIVES: 3D-printed patient-specific instruments (PSIs), also known as 3D guides, have been shown to improve accuracy in resection of pelvic tumors in cadaver studies and achieve better surgical margins in vivo. This study evaluates the clinical impact of 3D-printed guides on medium-term local and distant disease control, as well as disease-free and overall survival in patients. MATERIAL AND METHODS: A cohort study included 25 patients with primary pelvic or sacral sarcomas: 10 in the 3D group and 15 in the control group, with a median follow-up of 47 months. Demographic and clinical data, including tumor histology, stage, resection technique, associated reconstruction, adjuvant therapies, and complications, were evaluated. Surgical margins (free, marginal, and contaminated) and relapse-free and overall survival curves were analyzed. RESULTS: The 3D group achieved a higher rate of free margins (80% vs 66.7%, p = 0.345). Local recurrence (50% vs 60%, P=.244) and distant disease relapse (20% vs 47%, p = 0.132) rates were lower in the 3D group. At the end of the follow-up, the 3D group had a higher overall survival rate (60% vs 40%, p = 0.327). The complication rate was similar in both groups, with a deep infection rate of 40%. CONCLUSIONS: The use of 3D guides in resecting primary pelvic tumors not only achieves a higher rate of free margins compared to conventional techniques but also shows a trend towards higher local, distant, and overall disease-free survival. Further studies with larger sample sizes and higher levels of evidence are necessary to validate these clinical trends.

The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder.

BACKGROUND: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity. METHODS: Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393). RESULTS: Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %. LIMITATIONS: Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected. CONCLUSION: Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

The association between persistent cognitive difficulties and depression and functional outcomes in people with major depressive disorder.

BACKGROUND: Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes. METHODS: This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent major depressive disorder (MDD; N = 623). Participants completed app-based self-reported and performance-based cognitive function assessments alongside validated measures of depression, functional disability, and self-esteem every 3 months. Participants were followed-up for a maximum of 2-years. Multilevel hierarchically nested modelling was employed to explore between- and within-participant variation over time to identify whether persistent cognitive difficulties are related to levels of depression and functional impairment during follow-up. RESULTS: 508 individuals (81.5%) provided data (mean age: 46.6, s.d.: 15.6; 76.2% female). Increasing persistence of self-reported cognitive difficulty was associated with higher levels of depression and functional impairment throughout the follow-up. In comparison to low persistence of objective cognitive difficulty (<25% of timepoints), those with high persistence (>75% of timepoints) reported significantly higher levels of depression (B = 5.17, s.e. = 2.21, p = 0.019) and functional impairment (B = 4.82, s.e. = 1.79, p = 0.002) over time. Examination of the individual cognitive modules shows that persistently impaired executive function is associated with worse functioning, and poor processing speed is particularly important for worsened depressive symptoms. CONCLUSIONS: We replicated previous findings of greater persistence of cognitive difficulty with increasing severity of depression and further demonstrate that these cognitive difficulties are associated with pervasive functional disability. Difficulties with cognition may be an indicator and target for further treatment input.

Changes on depression and suicidal ideation under severe lockdown restrictions during the first wave of the COVID-19 pandemic in Spain: a longitudinal study in the general population.

AIMS: To assess whether there is a change in the prevalence of depression and suicidal ideation after the strict lockdown measures due to the first wave of the COVID-19 pandemic in Spain, and to assess which are the factors associated with the incidence of a depressive episode or suicidal ideation during the lockdown. METHODS: Data from a longitudinal adult population-based cohort from Madrid and Barcelona were analysed (n = 1103). Face-to-face home-based (pre-pandemic) and telephone interviews were performed. Depression and suicidal ideation were assessed through an adaptation of the Composite International Diagnostic Interview (CIDI 3.0). Population prevalence estimates and multivariable logistic regressions were computed. RESULTS: Prevalence rates of depression changed significantly from before to after the COVID-19 outbreak (from 3.06% to 12.00%; p = 0.01) and per sex and age groups. Individuals reporting COVID-19 concerns (odds ratio [OR] = 3.11; 95% confidence interval [CI] = 1.45-6.69) and those feeling loneliness (OR = 1.99; 95% CI = 1.52-2.61) during the lockdown were at increased risk of developing depression during the confinement. Resilience showed a protective effect against the risk of depression (OR = 0.57; 95% CI = 0.39-0.83), while individuals perceiving social support during the confinement were at lower risk of developing suicidal thoughts (OR = 0.21; 95% CI = 0.09-0.46). Greater disability during the lockdown was also associated with the risk of suicidal ideation (OR = 2.77; 95% CI = 1.53-5.03). CONCLUSIONS: Continuous reinforcement of mental health preventive and intervening measures is of global importance, particularly among vulnerable groups who are experiencing the most distress. Future research should strive to evaluate the long-term effects of the COVID-19 crisis on mental health.

The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity.

BACKGROUND: Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity. METHODS: Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions. RESULTS: Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms. CONCLUSIONS: Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.

Real-world treatment patterns and outcomes of abemaciclib for the treatment of HR + , HER2- metastatic breast cancer patients in Japan.

INTRODUCTION: This study described, in routine clinical practice in Japan, the patient characteristics, treatment patterns, and outcomes of female patients with HR + /HER2- metastatic breast cancer (MBC) who started abemaciclib treatment. METHODS: Clinical charts were reviewed for patients starting abemaciclib in 12/2018-08/2021 with a minimum of 3 months follow-up data post-abemaciclib initiation regardless of abemaciclib discontinuation. Patient characteristics, treatment patterns, and tumor response were descriptively summarized. Kaplan-Meier curves estimated progression-free survival (PFS). RESULTS: 200 patients from 14 institutions were included. At abemaciclib initiation, median age was 59 years, and the Eastern Cooperative Oncology Group performance status score was 0/1/2 for 102/68/5 patients (58.3/38.9/2.9%), respectively. Most had an abemaciclib starting dose of 150 mg (92.5%). The percentage of patients receiving abemaciclib as 1st, 2nd, or 3rd line treatment was 31.5%, 25.8%, and 25.2%, respectively. The most frequent endocrine therapy drugs used with abemaciclib were fulvestrant (59%) and aromatase inhibitors (40%). Evaluation of tumor response was available for 171 patients, 30.4% of whom had complete/partial response. Median PFS was 13.0 months (95% CI 10.1-15.8 months). CONCLUSIONS: In a routine clinical practice setting in Japan, patients with HR + , HER2- MBC appear to benefit from abemaciclib treatment in terms of treatment response and median PFS, with the results broadly reflecting the evidence demonstrated in clinical trials.

Patient preferences for key drivers and facilitators of adoption of mHealth technology to manage depression: A discrete choice experiment.

BACKGROUND: In time, we may be able to detect the early onset of symptoms of depression and even predict relapse using behavioural data gathered through mobile technologies. However, barriers to adoption exist and understanding the importance of these factors to users is vital to ensure maximum adoption. METHOD: In a discrete choice experiment, people with a history of depression (N = 171) were asked to select their preferred technology from a series of vignettes containing four characteristics: privacy, clinical support, established benefit and device accuracy (i.e., ability to detect symptoms), with different levels. Mixed logit models were used to establish what was most likely to affect adoption. Sub-group analyses explored effects of age, gender, education, technology acceptance and familiarity, and nationality. RESULTS: Higher level of privacy, greater clinical support, increased perceived benefit and better device accuracy were important. Accuracy was the most important, with only modest compromises willing to be made to increase other factors such as privacy. Established benefit was the least valued of the attributes with participants happy with technology that had possible but unknown benefits. Preferences were moderated by technology acceptance, age, nationality, and educational background. CONCLUSION: For people with a history of depression, adoption of technology may be driven by the desire for accurate detection of symptoms. However, people with lower technology acceptance and educational attainment, those who were younger, and specific nationalities may be willing to compromise on some accuracy for more privacy and clinical support. These preferences should help shape design of mHealth tools.

Multimorbidity, depression with anxiety symptoms, and decrements in health in 47 low- and middle-income countries.

BACKGROUND: Comorbid depression and anxiety is associated with worse health outcomes compared to depression or anxiety occurring in isolation, but there is little data on its association with multimorbidity. Thus, we investigated this association across 47 low- and middle-income countries, and further explored whether having anxiety symptoms in addition to depression is associated with significant declines in health outcomes among those with multimorbidity. METHODS: Cross-sectional, predominantly nationally representative, community-based data were analyzed from the World Health Survey. DSM-IV depression was assessed with the Composite International Diagnostic Interview. Anxiety symptoms referred to severe/extreme problems with worry or anxiety. Ten chronic conditions and health status across five domains (cognition, interpersonal activities, sleep/energy, self-care, pain/discomfort) were assessed. Multivariable regression analyses conducted. RESULTS: Data included 237,952 adults aged ≥18 years [mean age (SD) 38.4 (16.0); 50.8 % females]. Compared to no chronic conditions, 2 (OR = 6.86; 95%CI = 5.59-8.42), 3 (OR = 12.33; 95%CI = 9.72-15.63), and ≥4 (OR = 26.55; 95%CI = 20.21-35.17) chronic conditions were associated with significantly higher odds for comorbid depression/anxiety symptoms (vs. no depression or anxiety symptoms) in the multinomial logistic regression model. Among those with depression and multimorbidity, anxiety symptoms were associated with significantly worse health status across all domains. LIMITATIONS: Cross-sectional design, depression and anxiety symptoms were not based on a clinical assessment. CONCLUSIONS: Comorbid depression/anxiety is common in people with multimorbidity, and anxiety symptoms in people with depression and multimorbidity signify worse health status. Future studies should assess the utility of screening for and treating comorbid depression/anxiety in patients with multimorbidity in terms of clinical outcomes.

[Translated article] Validation of patient-specific 3D impression models for pelvic oncological orthopedic surgery.

INTRODUCTION: Pelvic ring tumours pose a challenge due to the difficulty in obtaining adequate surgical margins. Tools such as surgical navigation or 3D printing for the fabrication of patient-specific surgical positioning templates help in preoperative planning and intraoperative execution. Their correct positioning is essential in complex locations such as the pelvis, so it is necessary to identify positioning errors. The aim of this study is to demonstrate the reliability of 3D template placement for pelvic ring osteotomies. MATERIAL AND METHODS: Experimental study in cadaver with 10 hemipelvis. CT was performed to obtain the three-dimensional model, planning of osteotomies, design of positioning templates in ischiopubic (I), iliopubic (P), supracetabular (S) and iliac crest (C) branches; and a positioning marker (rigid-body) on the C and S templates for navigation. The templates and rigid-body are 3D printed and positioned according to pre-planning. Navigation allows the final position of the inserts and osteotomies to be checked. RESULTS: The positioning of the templates with respect to the preoperative planning varied depending on the location, being greater the error in those of the iliac crest. Using navigation the mean error of distance to the cutting plane is 3.5mm, except in pubis (5-8mm), being conditioned by the position of the rigid body. CONCLUSION: The use of patient-specific templates printed in 3D is a reliable tool for performing osteotomies in pelvic cancer surgery.

Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder.

BACKGROUND: Remote sensing for the measurement and management of long-term conditions such as Major Depressive Disorder (MDD) is becoming more prevalent. User-engagement is essential to yield any benefits. We tested three hypotheses examining associations between clinical characteristics, perceptions of remote sensing, and objective user engagement metrics. METHODS: The Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) study is a multicentre longitudinal observational cohort study in people with recurrent MDD. Participants wore a FitBit and completed app-based assessments every two weeks for a median of 18 months. Multivariable random effects regression models pooling data across timepoints were used to examine associations between variables. RESULTS: A total of 547 participants (87.8% of the total sample) were included in the current analysis. Higher levels of anxiety were associated with lower levels of perceived technology ease of use; increased functional disability was associated with small differences in perceptions of technology usefulness and usability. Participants who reported higher system ease of use, usefulness, and acceptability subsequently completed more app-based questionnaires and tended to wear their FitBit activity tracker for longer. All effect sizes were small and unlikely to be of practical significance. LIMITATIONS: Symptoms of depression, anxiety, functional disability, and perceptions of system usability are measured at the same time. These therefore represent cross-sectional associations rather than predictions of future perceptions. CONCLUSIONS: These findings suggest that perceived usability and actual use of remote measurement technologies in people with MDD are robust across differences in severity of depression, anxiety, and functional impairment.

SELNET clinical practice guidelines for bone sarcoma.

Bone sarcoma are infrequent diseases, representing < 0.2% of all adult neoplasms. A multidisciplinary management within reference centers for sarcoma, with discussion of the diagnostic and therapeutic strategies within an expert multidisciplinary tumour board, is essential for these patients, given its heterogeneity and low frequency. This approach leads to an improvement in patient's outcome, as demonstrated in several studies. The Sarcoma European Latin-American Network (SELNET), aims to improve clinical outcome in sarcoma care, with a special focus in Latin-American countries. These Clinical Practice Guidelines (CPG) have been developed and agreed by a multidisciplinary expert group (including medical and radiation oncologist, surgical oncologist, orthopaedic surgeons, radiologist, pathologist, molecular biologist and representatives of patients advocacy groups) of the SELNET consortium, and are conceived to provide the standard approach to diagnosis, treatment and follow-up of bone sarcoma patients in the Latin-American context.

Mental impact of Covid-19 among Spanish healthcare workers. A large longitudinal survey.

AIMS: Longitudinal data on the mental health impact of the coronavirus disease 2019 (Covid-19) pandemic in healthcare workers is limited. We estimated prevalence, incidence and persistence of probable mental disorders in a cohort of Spanish healthcare workers (Covid-19 waves 1 and 2) -and identified associated risk factors. METHODS: 8996 healthcare workers evaluated on 5 May-7 September 2020 (baseline) were invited to a second web-based survey (October-December 2020). Major depressive disorder (PHQ-8 ≥ 10), generalised anxiety disorder (GAD-7 ≥ 10), panic attacks, post-traumatic stress disorder (PCL-5 ≥ 7), and alcohol use disorder (CAGE-AID ≥ 2) were assessed. Distal (pre-pandemic) and proximal (pandemic) risk factors were included. We estimated the incidence of probable mental disorders (among those without disorders at baseline) and persistence (among those with disorders at baseline). Logistic regression of individual-level [odds ratios (OR)] and population-level (population attributable risk proportions) associations were estimated, adjusting by all distal risk factors, health care centre and time of baseline interview. RESULTS: 4809 healthcare workers participated at four months follow-up (cooperation rate = 65.7%; mean = 120 days s.d. = 22 days from baseline assessment). Follow-up prevalence of any disorder was 41.5%, (v. 45.4% at baseline, p < 0.001); incidence, 19.7% (s.e. = 1.6) and persistence, 67.7% (s.e. = 2.3). Proximal factors showing significant bivariate-adjusted associations with incidence included: work-related factors [prioritising Covid-19 patients (OR = 1.62)], stress factors [personal health-related stress (OR = 1.61)], interpersonal stress (OR = 1.53) and financial factors [significant income loss (OR = 1.37)]. Risk factors associated with persistence were largely similar. CONCLUSIONS: Our study indicates that the prevalence of probable mental disorders among Spanish healthcare workers during the second wave of the Covid-19 pandemic was similarly high to that after the first wave. This was in good part due to the persistence of mental disorders detected at the baseline, but with a relevant incidence of about 1 in 5 of HCWs without mental disorders during the first wave of the Covid-19 pandemic. Health-related factors, work-related factors and interpersonal stress are important risks of persistence of mental disorders and of incidence of mental disorders. Adequately addressing these factors might have prevented a considerable amount of mental health impact of the pandemic among this vulnerable population. Addressing health-related stress, work-related factors and interpersonal stress might reduce the prevalence of these disorders substantially. Study registration number: NCT04556565.

Four-month incidence of suicidal thoughts and behaviors among healthcare workers after the first wave of the Spain COVID-19 pandemic.

Healthcare workers (HCW) are at high risk for suicide, yet little is known about the onset of suicidal thoughts and behaviors (STB) in this important segment of the population in conjunction with the COVID-19 pandemic. We conducted a multicenter, prospective cohort study of Spanish HCW active during the COVID-9 pandemic. A total of n = 4809 HCW participated at baseline (May-September 2020; i.e., just after the first wave of the pandemic) and at a four-month follow-up assessment (October-December 2020) using web-based surveys. Logistic regression assessed the individual- and population-level associations of separate proximal (pandemic) risk factors with four-month STB incidence (i.e., 30-day STB among HCW negative for 30-day STB at baseline), each time adjusting for distal (pre-pandemic) factors. STB incidence was estimated at 4.2% (SE = 0.5; n = 1 suicide attempt). Adjusted for distal factors, proximal risk factors most strongly associated with STB incidence were various sources of interpersonal stress (scaled 0-4; odds ratio [OR] range = 1.23-1.57) followed by personal health-related stress and stress related to the health of loved ones (scaled 0-4; OR range 1.30-1.32), and the perceived lack of healthcare center preparedness (scaled 0-4; OR = 1.34). Population-attributable risk proportions for these proximal risk factors were in the range 45.3-57.6%. Other significant risk factors were financial stressors (OR range 1.26-1.81), isolation/quarantine due to COVID-19 (OR = 1.53) and having changed to a specific COVID-19 related work location (OR = 1.72). Among other interventions, our findings call for healthcare systems to implement adequate conflict communication and resolution strategies and to improve family-work balance embedded in organizational justice strategies.

Approximate reinforcement learning to control beaconing congestion in distributed networks.

In vehicular communications, the increase of the channel load caused by excessive periodical messages (beacons) is an important aspect which must be controlled to ensure the appropriate operation of safety applications and driver-assistance systems. To date, the majority of congestion control solutions involve including additional information in the payload of the messages transmitted, which may jeopardize the appropriate operation of these control solutions when channel conditions are unfavorable, provoking packet losses. This study exploits the advantages of non-cooperative, distributed beaconing allocation, in which vehicles operate independently without requiring any costly road infrastructure. In particular, we formulate the beaconing rate control problem as a Markov Decision Process and solve it using approximate reinforcement learning to carry out optimal actions. Results obtained were compared with other traditional solutions, revealing that our approach, called SSFA, is able to keep a certain fraction of the channel capacity available, which guarantees the delivery of emergency-related notifications with faster convergence than other proposals. Moreover, good performance was obtained in terms of packet delivery and collision ratios.