A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data.

BACKGROUND: Social network analysis of animal societies allows scientists to test hypotheses about social evolution, behaviour, and dynamic processes. However, the accuracy of estimated metrics depends on data characteristics like sample proportion, sample size, and frequency. A protocol is needed to assess for bias and robustness of social network metrics estimated for the animal populations especially when a limited number of individuals are monitored. METHODS: We used GPS telemetry datasets of five ungulate species to combine known social network approaches with novel ones into a comprehensive five-step protocol. To quantify the bias and uncertainty in the network metrics obtained from a partial population, we presented novel statistical methods which are particularly suited for autocorrelated data, such as telemetry relocations. The protocol was validated using a sixth species, the fallow deer, with a known population size where ∼ 85 % of the individuals have been directly monitored. RESULTS: Through the protocol, we demonstrated how pre-network data permutations allow researchers to assess non-random aspects of interactions within a population. The protocol assesses bias in global network metrics, obtains confidence intervals, and quantifies uncertainty of global and node-level network metrics based on the number of nodes in the network. We found that global network metrics like density remained robust even with a lowered sample size, while local network metrics like eigenvector centrality were unreliable for four of the species. The fallow deer network showed low uncertainty and bias even at lower sampling proportions, indicating the importance of a thoroughly sampled population while demonstrating the accuracy of our evaluation methods for smaller samples. CONCLUSIONS: The protocol allows researchers to analyse GPS-based radio-telemetry or other data to determine the reliability of social network metrics. The estimates enable the statistical comparison of networks under different conditions, such as analysing daily and seasonal changes in the density of a network. The methods can also guide methodological decisions in animal social network research, such as sampling design and allow more accurate ecological inferences from the available data. The R package aniSNA enables researchers to implement this workflow on their dataset, generating reliable inferences and guiding methodological decisions.

Zwitterionic Injectable Hydrogel-Combined Chemo- and Immunotherapy Medicated by Monomolecular Micelles to Effectively Prevent the Recurrence of Tumor Post Operation.

Surgical resection remains the most common method of tumor treatment; however, the high recurrence and metastasis after surgery need to be solved urgently. Herein, we report an injectable zwitterionic hydrogel based on "thiol-ene" click chemistry containing doxorubicin (DOX) and a macrophage membrane (MM)-coated 1-methyl-tryptophan (1-MT)-loaded polyamide-amine dendrimer (P-DOX/1MT) for preventing the postoperative recurrence of tumors. The results indicated that P-DOX/1MT@MM exhibited enhanced recognition and uptake of the dendrimer by tumor cells and induced the immunogenic cell death. In the mice tumor model, the P-DOX/1MT@MM-Gel exhibited high therapeutic efficiency, which could significantly reduce the recurrence of the tumor, including suppressing tumor growth, promoting dendritic cell maturation, and increasing tumor-infiltrating cytotoxic T lymphocytes. The mechanism analysis revealed that the hydrogel greatly reduces the side effects to normal tissues and significantly improves its therapeutic effect. 1MT in the hydrogel is released more rapidly, improving the tumor suppressor microenvironment and increasing the tumor cell sensitivity to DOX. Then, the DOX in the P-DOX/1MT@MM effectively eliminatedo the residual tumor cells and exerted enhanced toxicity. In conclusion, this novel injectable hydrogel that combines chemotherapy and immunotherapy has the property of sequential drug release and is a promising strategy for preventing the postoperative recurrence of tumors.

Assessment of Quality of Life after Hysterectomy using European Quality of Life Five Dimension Scale (EQ5D).

In several regions throughout the globe, caesarean sections constitute the most common nonobstetric surgery, followed by hysterectomy, which is the surgical excision of the uterus. While it is not the only solution for reproductive organ issues, it is the most effective technique to treat many illnesses over the long term. The uterus is a very critical reproductive organ for all age groups as this is not only essential for giving birth but also for hormonal-related physiology in women's life. The quality of life is impacted by a number of hysterectomy-related effects on females. Physical, psychological, environmental, and social relations are some of these impacts. All EuroQol five-dimensions (EQ5D) subscales significantly improved, as per the research 's findings. Preoperative psychosocial status, perioperative pain, indication of hysterectomy, complications occur during surgery, and mode of hysterectomy postoperative infection had been discovered as determinants of quality of life outcome following hysterectomy. In most of the subjects we noticed small, however, noticable improvements in all component of EQ5D Scale. The strengths of EQ5D questionnaire lie in its simplicity and moreover it is available in several languages.

The characteristics and outcomes of patients with idiopathic pulmonary fibrosis admitted to the ICU with acute respiratory failure.

BACKGROUND: To date, studies have provided conflicting results regarding the outcomes of patients with Idiopathic Pulmonary Fibrosis (IPF) admitted to the ICU with acute respiratory failure (ARF). OBJECTIVE: To understand the characteristics and outcomes of these patients. METHODS: Retrospective study using a large single-center ICU database. We identified 48 unique patients with IPF admitted for ARF from 2001-2012. RESULTS: The most common causes of ARF were IPF exacerbation and pneumonia. The overall hospital mortality rate was 43.8% and was 56.7% in those who required invasive mechanical ventilation (IMV). In patients requiring IMV for IPF exacerbation, the mortality rate was 81.3%. In multiple regression analysis, the presence of diabetes mellitus was associated with decreased mortality whereas the need for IMV was associated with increased mortality. CONCLUSIONS: Although the overall mortality rate for IPF patients with ARF has improved, the need for IMV due to IPF exacerbations is associated with increased mortality.