Large library docking for cannabinoid-1 receptor agonists with reduced side effects.

Large library docking can reveal unexpected chemotypes that complement the structures of biological targets. Seeking new agonists for the cannabinoid-1 receptor (CB1R), we docked 74 million tangible molecules, prioritizing 46 high ranking ones for de novo synthesis and testing. Nine were active by radioligand competition, a 20% hit-rate. Structure-based optimization of one of the most potent of these (Ki = 0.7 uM) led to '4042, a 1.9 nM ligand and a full CB1R agonist. A cryo-EM structure of the purified enantiomer of '4042 ('1350) in complex with CB1R-Gi1 confirmed its docked pose. The new agonist was strongly analgesic, with generally a 5-10-fold therapeutic window over sedation and catalepsy and no observable conditioned place preference. These findings suggest that new cannabinoid chemotypes may disentangle characteristic cannabinoid side-effects from their analgesia, supporting the further development of cannabinoids as pain therapeutics.

Quiste esplénico epidérmico infectado. Reporte de caso

Los quistes esplénicos son infrecuentes y presentan una baja incidencia (0.07%). Las etiologías son varias, pero en su mayoría se deben a parasitarios y no parasitarios. Entre los primeros se encuentran los quistes hidatídicos por equinococosis que son más comunes sobre todo en zonas endémicas. En el siguiente trabajo se presenta el caso de una paciente de sexo femenino de 17 años de edad que consulta por un cuadro de 6 días de evolución que inicia con dolor, tipo puntada de moderada intensidad, localizado en hipocondrio izquierdo, acompañado de fiebre graduada en 38 grados con escalofríos.

Splenic cysts are uncommon and have a low incidence rate (0.07%). The etiologies are diverse, but mostly attributed to both parasitic and non-parasitic origins. Among the former, hydatid cysts due to echinococcosis are more prevalent, especially in endemic areas. This report describes the case of a 17-year-old female patient who presented with a 6-day history of pain, of moderate intensity and stabbing type, localized in the left hypochondrium. The pain was accompanied by a fever reaching 38 degrees Celsius and chills.

Sludge bulking monitoring in industrial wastewater treatment plants through graphical methods: A dynamic graph embedding and Bayesian networks approach.

Sludge bulking is a prevalent issue in wastewater treatment plants (WWTPs) that negatively impacts effluent quality by hindering the normal functioning of treatment processes. To tackle this problem, we propose a novel graph-based monitoring framework that employs advanced graph-based techniques to detect and diagnose sludge bulking events. The proposed framework utilizes historical datasets under normal operating conditions to extract pertinent features and causal relationships between process variables. This enables operators to trigger alarms and diagnose the root cause of the bulking event. Sludge bulking detection is carried out using the dynamic graph embedding (DGE) method, which identifies similarities among process variables in both temporal and neighborhood dependencies. Consequently, the dynamic Bayesian network (DBN) computes the prior and posterior probabilities of a belief, updated at each time step. Variations in these probabilities indicate the potential root cause of the sludge bulking event. The results demonstrate that the DGE outperforms other linear and non-linear feature extraction methods, achieving a detection rate of 99%, zero false alarms, and less than one percent incorrect detections. Additionally, the DBN-based diagnostic method accurately identified the majority of sludge bulking root causes, primarily those resulting from sudden drops in COD concentration, with an accuracy of 98% an improvement of 11% over state-of-the-art techniques.

Smart solutions for urban health risk assessment: A PM2.5 monitoring system incorporating spatiotemporal long-short term graph convolutional network.

Current spatial-temporal early warning systems aim to predict outdoor air quality in urban areas either at short or long temporal horizons. These systems implemented architectures without considering the geographical distribution of each air quality monitoring station, increasing the uncertainty of the forecasting framework. This study developed an integrated spatiotemporal forecasting architecture incorporating an extensive air quality PM2.5 monitoring network and simultaneously forecasts PM2.5 concentrations at all locations, allowing the monitoring of the health risk associated with exposure to these levels. First, this study uses a graph convolutional layer to incorporate the spatial relationship of the neighboring stations at their current state with real-time measurements. Then, it is coupled to a deep learning temporal model to form the long- and short-term time-series graph convolutional network (LSTGraphNet) model, anticipating high pollutant concentration events. This work tested the proposed model with a case study of an existing ambient air quality monitoring network in South Korea. LSTGraphNet model showed prediction performances of PM2.5 at multiple monitoring stations with a mean absolute error (MAE) of 1.82 µg/m3, 4.46 µg/m3, and 4.87 µg/m3 for forecasting horizons of one, three, and 6 h ahead, respectively. Compared to conventional sequential models, this architecture was superior among the state-of-the-art baselines, where the MAE decreased to 41%, respectively. The results of the study showed that the proposed architecture was superior to conventional sequential models and could be used as a tool for decision-making in smart cities by revealing hotspots of higher and lower PM2.5 concentrations in the long term.

Paradoxical increases in anterior cingulate cortex activity during nitrous oxide-induced analgesia reveal a signature of pain affect.

The general consensus is that increases in neuronal activity in the anterior cingulate cortex (ACC) contribute to pain's negative affect. Here, using in vivo imaging of neuronal calcium dynamics in mice, we report that nitrous oxide, a general anesthetic that reduces pain affect, paradoxically, increases ACC spontaneous activity. As expected, a noxious stimulus also increased ACC activity. However, as nitrous oxide increases baseline activity, the relative change in activity from pre-stimulus baseline was significantly less than the change in the absence of the general anesthetic. We suggest that this relative change in activity represents a neural signature of the affective pain experience. Furthermore, this signature of pain persists under general anesthesia induced by isoflurane, at concentrations in which the mouse is unresponsive. We suggest that this signature underlies the phenomenon of connected consciousness, in which use of the isolated forelimb technique revealed that pain percepts can persist in anesthetized patients.

Effect of Participative Web-Based Educational Modules on HIV and Sexually Transmitted Infection Prevention Competency Among Medical Students: Single-Arm Interventional Study.

BACKGROUND: The number of new HIV diagnoses in the United States continues to slowly decline; yet, transgender women and men who have sex with men remain disproportionately affected. Key to improving the quality of prevention services are providers who are comfortable broaching the subjects of sexual health and HIV prevention with people across the spectrum of gender identities and sexual orientations. Preservice training is a critical point to establish HIV prevention and sexual health education practices before providers' practice habits are established. OBJECTIVE: The study aimed to develop participative web-based educational modules and test their impact on HIV prevention knowledge and awareness in future providers. METHODS: Sexual health providers at an academic hospital, research clinicians, community engagement professionals, and New York City community members were consulted to develop 7 web-based educational modules, which were then piloted among medical students. We assessed knowledge of HIV and sexually transmitted infection prevention and comfort assessing the prevention needs of various patients via web-based questionnaires administered before and after our educational intervention. We conducted exploratory factor analysis of the items in the questionnaire. RESULTS: Pre- and postmodule surveys were completed by 125 students and 89 students, respectively, from all 4 years of training. Before the intervention, the majority of students had heard of HIV pre-exposure prophylaxis (122/123, 99.2%) and postexposure prophylaxis (114/123, 92.7%). Before the training, 30.9% (38/123) of the students agreed that they could confidently identify a patient who is a candidate for pre-exposure prophylaxis or postexposure prophylaxis; this increased to 91% (81/89) after the intervention. CONCLUSIONS: Our findings highlight a need for increased HIV and sexually transmitted infection prevention training in medical school curricula to enable future providers to identify and care for diverse at-risk populations. Participative web-based modules offer an effective way to teach these concepts.

[Pediatric therapeutic options in autoimmune neurologic diseases]. / Opciones terapéuticas para enfermedades neurológicas autoinmunes en pediatría.

The pediatric neuroimmunology field has made significant progress in the last decade. Now, is possible to recognize primary demyelinating diseases, paraneoplastic syndromes, inflammatory (vasculitis), and granulomatous disorders that affect the central nervous system; at the same time, it is important to exclude neurologic manifestations caused by infections, toxic agents, and metabolic problems. An early diagnosis is imperative to institute treatment as soon as possible, improving outcomes. Treatment may include both, specific drugs if the etiology has been established, as well as drugs to treat potential complications, for example anticonvulsants, anti-inflammatory drugs, transfusions, or albumin replenishment within others. The main objective of this review is to provide guidance about the therapeutic options in pediatric autoimmune neurological diseases. We review the evidence and recommendations for the use of steroids in autoimmune demyelinating diseases, acute disseminated encephalomyelitis, optic neuritis, neuromyelitis optica, multiple sclerosis, among others. We will focus on current therapies, including high doses of intravenous methylprednisolone, followed by its progressive reduction, as well as intravenous immunoglobulin or plasmapheresis as second line therapies. Early institution of these treatments can save the patient's life and decrease their risk of permanent disability.

El campo de la pediatría neuro-inmunológica ha progresado significativamente en la última década. Ahora es posible reconocer con prontitud enfermedades desmielinizantes primarias, síndromes para-neoplásicos, enfermedades inflamatorias, autoinmunes y granulomatosas, que afectan el sistema nervioso central. Excluir con gran rapidez posibles causas infecciosas, agentes tóxicos, problemas metabólicos que se presenten con manifestaciones neurológicas es imperativo, ya que al hacer un diagnóstico preciso y temprano del paciente se puede instituir un tratamiento lo más pronto posible e incrementar las probabilidades de éxito. El tratamiento puede ser dirigido a la etiología específica, si se conoce. Adicionalmente, es importante tratar las complicaciones relacionadas a la propia enfermedad o efectos secundarios de los tratamientos que se impongan. El tratamiento puede incluir tanto fármacos específicos si se ha establecido la etiología, así como medicamentos para tratar posibles complicaciones, por ejemplo, anticonvulsivos, antiinflamatorios, transfusiones, o reposición de albúmina dentro de otros. El objetivo principal de esta revisión es brindar una guía sobre las opciones terapéuticas en enfermedades neurológicas autoinmunes en fase aguda. Revisamos la evidencia y recomendaciones acerca del uso de esteroides en enfermedades autoinmunes desmielinizantes, encefalomielitis aguda diseminada, neuritis óptica, neuromielitis óptica, esclerosis múltiple, entre otras, donde altas dosis de metilprednisolona, seguida por su disminución progresiva son esenciales, así como el uso de inmunoglobulina humana intravenosa y plasmaféresis, como tratamiento de segunda línea. La institución temprana de estos tratamientos puede salvar la vida del paciente y disminuir su discapacidad permanente.

Valoración de un programa de formación de cuidadores sobre la capacidad cognitiva de personas con demencia / Assessment of a caregiver training program on the cognitive capacity of people with dementia

Objetivos: El incremento de la población mayor ha hecho que se eleve el porcentaje de personas con demencia que requieren una atención especializada dirigida a mantener o retrasar su declive cognitivo y físico. El objetivo de esta investigación ha sido analizar si un grupo de personas con demencia mejoran cognitivamente al ser atendidos por cuidadores profesionales que han sido formados en un módulo de estimulación cognitiva del programa CUIDA-2 siguiendo los principios de la atención centrada en la persona. Metodología: La muestra estuvo formada por 47 personas con demencia (divididas en grupo tratamiento y grupo control) y 5 cuidadores formales de un centro de día de personas con demencia de Granada. El grupo tratamiento de personas mayores fue atendido durante 3 meses por cuidadores que recibieron el programa de formación. Todos los participantes fueron evaluados antes y después de la intervención con diversas pruebas de evaluación cognitiva. Resultados: Las personas con demencia que fueron atendidas por los cuidadores formados en el programa mantuvieron o mejoraron sus puntuaciones en todas las pruebas analizadas, si bien estas mejoras solo fueron significativas en diversas subescalas de los test empleados. Conclusiones: Se ha comprobado que el programa de formación de cuidadores aquí analizado produce un efecto positivo para las personas con demencia, ya que ayuda a mejorar y mantener sus funciones cognitivas. Esta investigación abre nuevas líneas de trabajo en el ámbito de la intervención cognitiva en personas con demencia que pueden ser de gran utilidad cuando se trabaje con esta población (AU)

Objectives: The increase in the elderly population has led to a rise in the percentage of people with dementia who require specialized attention aimed at maintaining or delaying their cognitive and physical decline. The aim of this research was to analyze whether a group of adults with dementia improve cognitively when being attended by professional caregivers who were trained in a cognitive stimulation module of the CUIDA-2 program following the principles of the person-centered-care model. Methodology: The sample consisted on 47 people with dementia (divided into treatment group and control group) and 5 professional caregivers of a day center for people with dementia in Granada. The older people treatment group was treated for three months by caregivers who received the training program. All participants were assessed before and after the intervention with various cognitive assessment tests. Results: People with dementia who were treated by caregivers trained in the program maintained or improved their scores in all the tests analyzed, although these improvements were only significant in various subtest. Conclusions: The caregiver training program produced a positive effect in the adults with dementia, as it helps to improve and maintain their cognitive functions. This research opens new lines of work in the field of cognitive intervention in people with dementia that can be very useful when working with this population (AU)

The impact of phosphorylated PTEN at threonine 366 on cortical connectivity and behaviour.

The lipid phosphatase PTEN (phosphatase and tensin homologue on chromosome 10) is a key tumour suppressor gene and an important regulator of neuronal signalling. PTEN mutations have been identified in patients with autism spectrum disorders, characterized by macrocephaly, impaired social interactions and communication, repetitive behaviour, intellectual disability, and epilepsy. PTEN enzymatic activity is regulated by a cluster of phosphorylation sites at the C-terminus of the protein. Here, we focused on the role of PTEN T366 phosphorylation and generated a knock-in mouse line in which Pten T366 was substituted with alanine (PtenT366A/T366A). We identify that phosphorylation of PTEN at T366 controls neuron size and connectivity of brain circuits involved in sensory processing. We show in behavioural tests that PtenT366/T366A mice exhibit cognitive deficits and selective sensory impairments, with significant differences in male individuals. We identify restricted cellular overgrowth of cortical neurons in PtenT366A/T366A brains, linked to increases in both dendritic arborization and soma size. In a combinatorial approach of anterograde and retrograde monosynaptic tracing using rabies virus, we characterize differences in connectivity to the primary somatosensory cortex of PtenT366A/T366A brains, with imbalances in long-range cortico-cortical input to neurons. We conclude that phosphorylation of PTEN at T366 controls neuron size and connectivity of brain circuits involved in sensory processing and propose that PTEN T366 signalling may account for a subset of autism-related functions of PTEN.

Missing data imputation and sensor self-validation towards a sustainable operation of wastewater treatment plants via deep variational residual autoencoders.

Missing data imputation and automatic fault detection of wastewater treatment plant (WWTP) sensors are crucial for energy conservation and environmental protection. Given the dynamic and non-linear characteristics of WWTP measurements, the conventional diagnosis models are inefficient and ignore potential valuable features in the offline modeling phase, leading to false alarms and inaccurate imputations. In this study, an inclusive framework for missing data imputation and sensor self-validation based on integrating variational autoencoders (VAE) with a deep residual network structure (ResNet-VAE) is proposed. This network structure can automatically extract complex features from WWTP data without the risk of vanishing gradients by learning the potential probability distribution of the input data. The proposed framework is intended to increase the reliability of faulty sensors by imputing missing data, detecting anomalies, identifying failure sources, and reconstructing faulty data to normal conditions. Several metrics were utilized to assess the performance of the suggested approach in comparison with other different methods. The VAE-ResNet approach showed superiority to detect (DRSPE = 100%), reconstruct faulty WWTP sensors (MAPE = 15.41%-5.68%) and impute the missing values (MAPE = 10.44%-3.98%). Lastly, the consequences of faulty data, missing data, reconstructed and imputed data were evaluated considering electricity consumption and resilience to demonstrate the ResNet-VAE model's superior performance for WWTP sustainability.

Inter-regional multimedia fate analysis of PAHs and potential risk assessment by integrating deep learning and climate change scenarios.

Polycyclic aromatic hydrocarbons (PAHs) are hazardous compounds associated with respiratory disease and lung cancer. Increasing fossil fuel consumption, which causes climate change, has accelerated the emissions of PAHs. However, potential risks by PAHs have not been predicted for Korea, and appropriate PAH regulations under climate change have yet to be developed. This study assesses the potential risks posed by PAHs using climate change scenarios based on deep learning, and a multimedia fugacity model was employed to describe the future fate of PAHs. The multimedia fugacity model describes the dynamics of sixteen PAHs by reflecting inter-regional meteorological transportation. A deep neural network predicts future environmental and economic conditions, and the potential risks posed by PAHs, in the year 2050, using a prediction model and climate change scenarios. The assessment indicates that cancer risks would increase by more than 50%, exceeding the lower risk threshold in the southern and western regions. A mix of strategies for developing PAH regulatory policies highlighted the necessity of increasing PAHs monitoring stations and controlling fossil fuel usage based on the domestic and global conditions under climate change scenarios.

Intervention Program to Improve Grief-Related Symptoms in Caregivers of Patients Diagnosed With Dementia.

The objectives of the present study were to adapt a grief intervention program to family caregivers of patients with dementia, and assess its effectiveness in improving the symptoms of grief and other health-related variables. The intervention was based on Shear and Bloom's grief intervention program, with the necessary adaptations for use in the grieving process for a family member's illness. A total of 52 family caregivers of individuals with dementia participated. They were evaluated using a battery of self-report measures assessing grief, overload, resilience, post-traumatic growth, experiential avoidance, health-related quality of life, and benefits of care. The results suggest that the program is effective in improving grief symptoms, caregiver burden, resilience, post-traumatic growth, and quality of life of family caregivers. It is necessary to create and implement interventions targeting caregivers' feelings and manifestations of ambiguous grief, because there is a lack of programs providing an efficient solution for the mental and physical health of caregivers, and because of the human and socioeconomic cost involved in neglecting this group.

PTEN deficiency leads to proteasome addiction: a novel vulnerability in glioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common primary brain tumor in adults with a median survival of approximately 15 months; therefore, more effective treatment options for GBM are required. To identify new drugs targeting GBMs, we performed a high-throughput drug screen using patient-derived neurospheres cultured to preferentially retain their glioblastoma stem cell (GSC) phenotype. METHODS: High-throughput drug screening was performed on GSCs followed by a dose-response assay of the 5 identified original "hits." A PI3K/mTOR dependency to a proteasome inhibitor (carfilzomib), was confirmed by genetic and pharmacologic experiments. Proteasome Inhibition Response Signatures were derived from proteomic and bioinformatic analysis. Molecular mechanism of action was determined using three-dimensional (3D) GBM-organoids and preclinical orthotopic models. RESULTS: We found that GSCs were highly sensitive to proteasome inhibition due to an underlying dependency on an increased protein synthesis rate, and loss of autophagy, associated with PTEN loss and activation of the PI3K/mTOR pathway. In contrast, combinatory inhibition of autophagy and the proteasome resulted in enhanced cytotoxicity specifically in GSCs that did express PTEN. Finally, proteasome inhibition specifically increased cell death markers in 3D GBM-organoids, suppressed tumor growth, and increased survival of mice orthotopically engrafted with GSCs. As perturbations of the PI3K/mTOR pathway occur in nearly 50% of GBMs, these findings suggest that a significant fraction of these tumors could be vulnerable to proteasome inhibition. CONCLUSIONS: Proteasome inhibition is a potential synthetic lethal therapeutic strategy for GBM with proteasome addiction due to a high protein synthesis rate and autophagy deficiency.

Transfer learning driven sequential forecasting and ventilation control of PM2.5 associated health risk levels in underground public facilities.

Particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) has become a major public concern in closed indoor environments, such as subway stations. Forecasting platform PM2.5 concentrations is significant in developing early warning systems, and regulating ventilation systems to ensure commuter health. However, the performance of existing forecasting approaches relies on a considerable amount of historical sensor data, which is usually not available in practical situations due to hostile monitoring environments or newly installed equipment. Transfer learning (TL) provides a solution to the scant data problem, as it leverages the knowledge learned from well-measured subway stations to facilitate predictions on others. This paper presents a TL-based residual neural network framework for sequential forecast of health risk levels traced by subway platform PM2.5 levels. Experiments are conducted to investigate the potential of the proposed methodology under different data availability scenarios. The TL-framework outperforms the RNN structures with a determination coefficient (R2) improvement of 42.84%, and in comparison, to stand-alone models the prediction errors (RMSE) are reduced up to 40%. Additionally, the forecasted data by TL-framework under limited data scenario allowed the ventilation system to maintain IAQ at healthy levels, and reduced PM2.5 concentrations by 29.21% as compared to stand-alone network.

Assessing Knowledge of HIV Vaccines and Biomedical Prevention Methods Among Transgender Women in the New York City Tri-State Area.

Purpose: To lower the HIV risk of transgender women, it is imperative to understand their unique HIV prevention needs and design biomedical prevention interventions that are responsive to the psychosocial, behavioral, and clinical needs of these communities. Preventive HIV vaccines are an important modality under investigation in diverse study participants. We sought to assess the knowledge of HIV vaccine research and the most common barriers and facilitators to participation in HIV vaccine studies among HIV-negative transgender women living in New York City. Methods: Six focus groups were conducted among 29 participants recruited in the New York City tri-state area from December 2014 to July 2015. Prefocus group quantitative questionnaire assessed demographic, behavioral information, knowledge of preventive vaccine research, and reasons for potential participation in prevention studies. Results: Median age of participants was 29 years and 41.4% identified as white. Over half of participants have heard of preventive vaccine research and majority indicated that an important factor in participating in HIV prevention research is to help the community collective effort. Key barriers that emerged were fear of side effects, feelings of exclusion from biomedical research. Facilitators to participation in prevention studies included trusting relationships with providers. Conclusions: These barriers and facilitators are important to consider in the design of studies inclusive of trans communities and transgender-specific prevention strategies. Barriers may be overcome by disseminating accurate information via social media or health providers.

An autonomous operational trajectory searching system for an economic and environmental membrane bioreactor plant using deep reinforcement learning.

Optimal operation of membrane bioreactor (MBR) plants is crucial to save operational costs while satisfying legal effluent discharge requirements. The aeration process of MBR plants tends to use excessive energy for supplying air to micro-organisms. In the present study, a novel optimal aeration system is proposed for dynamic and robust optimization. Accordingly, a deep reinforcement learning (DRL)-based optimal operating system is proposed, so as to meet stringent discharge qualities while maximizing the system's energy efficiency. Additionally, it is compared with the manual system and conventional reinforcement learning (RL)-based systems. A deep Q-network (DQN) algorithm automatically learns how to operate the plant efficiently by finding an optimal trajectory to reduce the aeration energy without degrading the treated water quality. A full-scale MBR plant with the DQN-based autonomous aeration system can decrease the MBR's aeration energy consumption by 34% compared to other aeration systems while maintaining the treatment efficiency within effluent discharge limits.

Author Correction: Longitudinal assessment of tumor development using cancer avatars derived from genetically engineered pluripotent stem cells.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Longitudinal assessment of tumor development using cancer avatars derived from genetically engineered pluripotent stem cells.

Many cellular models aimed at elucidating cancer biology do not recapitulate pathobiology including tumor heterogeneity, an inherent feature of cancer that underlies treatment resistance. Here we introduce a cancer modeling paradigm using genetically engineered human pluripotent stem cells (hiPSCs) that captures authentic cancer pathobiology. Orthotopic engraftment of the neural progenitor cells derived from hiPSCs that have been genome-edited to contain tumor-associated genetic driver mutations revealed by The Cancer Genome Atlas project for glioblastoma (GBM) results in formation of high-grade gliomas. Similar to patient-derived GBM, these models harbor inter-tumor heterogeneity resembling different GBM molecular subtypes, intra-tumor heterogeneity, and extrachromosomal DNA amplification. Re-engraftment of these primary tumor neurospheres generates secondary tumors with features characteristic of patient samples and present mutation-dependent patterns of tumor evolution. These cancer avatar models provide a platform for comprehensive longitudinal assessment of human tumor development as governed by molecular subtype mutations and lineage-restricted differentiation.

Grief Experiences in Family Caregivers of Children with Autism Spectrum Disorder (ASD).

The main objective of this study was to analyse the experience of grief and feelings of loss in family caregivers of children diagnosed with autism spectrum disorder (ASD), as well as the perceived overload from taking on the primary caregiver role. Twenty family caregivers of children with ASD participated. The family members were assessed using an ad-hoc semi-structured interview that addressed the families' reactions to the diagnosis, implications for daily functioning, and concerns for the immediate and long-term future of their relatives with ASD. The results indicate that family caregivers of children with ASD endure intense and continuous sorrow and grief due to the impact that having and caring for a child with these characteristics has on all aspects of their lives. These data highlight the importance of creating support and intervention programmes and services focused on the feelings and manifestations of ambiguous grief that occur in these family members, in order to improve their well-being and quality of life and reduce caregiver role overload.