The effect of a one-time 15-minute guided meditation (Isha Kriya) on stress and mood disturbances among operating room professionals: a prospective interventional pilot study

Background: Operating room professionals are exposed to high levels of stress and burnout. Besides affecting the individual, it can compromise patient safety and quality of care as well. Meditation practice is getting recognized for its ability to improve wellness among various populations, including healthcare providers. Methods: Baseline stress levels of perioperative healthcare providers were measured via an online survey using a Perceived Stress Scale (PSS) questionnaire. An in-person meditation workshop was demonstrated during surgical grand rounds and an international anesthesia conference using a 15-minute guided Isha Kriya meditation. The participants were then surveyed for mood changes before and after meditation using a Profile of Mood States (POMS) questionnaire. Results: Surgeons and anesthesiologists were found to have higher median (interquartile range) Perceived Stress Scores as compared to nurses respectively (17 [12, 20] and 17 [12, 21] vs 14 [9, 19]; P = 0.01). Total mood disturbances were found to be significantly reduced after meditation in both the surgical grand rounds (pre-meditation median [IQR] 99 [85, 112] vs 87 [80, 93] post-meditation; P < 0.0001) and anesthesia conference cohorts (pre-meditation 92 [86, 106] vs 87 [81, 92] post-meditation; P < 0.0001). Conclusions: Isha Kriya, a guided meditation, is easy to learn and takes less than 15 minutes to complete. This meditation technique improves mood changes and negative emotions among operating room professionals and could be used as a potential tool for improving wellness

Normal parameter reduction algorithm in soft set based on hybrid binary particle swarm and biogeography optimizer

© 2019, Springer-Verlag London Ltd., part of Springer Nature. Existing classification techniques that are proposed previously for eliminating data inconsistency could not achieve an efficient parameter reduction in soft set theory, which effects on the obtained decisions. Meanwhile, the computational cost made during combination generation process of soft sets could cause machine infinite state, which is known as nondeterministic polynomial time. The contributions of this study are mainly focused on minimizing choices costs through adjusting the original classifications by decision partition order and enhancing the probability of searching domain space using a developed Markov chain model. Furthermore, this study introduces an efficient soft set reduction-based binary particle swarm optimized by biogeography-based optimizer (SSR-BPSO-BBO) algorithm that generates an accurate decision for optimal and sub-optimal choices. The results show that the decision partition order technique is performing better in parameter reduction up to 50%, while other algorithms could not obtain high reduction rates in some scenarios. In terms of accuracy, the proposed SSR-BPSO-BBO algorithm outperforms the other optimization algorithms in achieving high accuracy percentage of a given soft dataset. On the other hand, the proposed Markov chain model could significantly represent the robustness of our parameter reduction technique in obtaining the optimal decision and minimizing the search domain.Published versio

An Update on Emergent Nano-Therapeutic Strategies against Pediatric Brain Tumors

Pediatric brain tumors are the major cause of pediatric cancer mortality. They comprise a diverse group of tumors with different developmental origins, genetic profiles, therapeutic options, and outcomes. Despite many technological advancements, the treatment of pediatric brain cancers has remained a challenge. Treatment options for pediatric brain cancers have been ineffective due to non-specificity, inability to cross the blood–brain barrier, and causing off-target side effects. In recent years, nanotechnological advancements in the medical field have proven to be effective in curing challenging cancers like brain tumors. Moreover, nanoparticles have emerged successfully, particularly in carrying larger payloads, as well as their stability, safety, and efficacy monitoring. In the present review, we will emphasize pediatric brain cancers, barriers to treating these cancers, and novel treatment options

Palm tocotrienols decrease levels of pro-angiogenic markers in human umbilical vein endothelial cells (HUVEC) and murine mammary cancer cells

Anti-angiogenic therapy is widely being used to halt tumour angiogenesis. In this study, the anti-angiogenic activity of palm tocotrienol-rich fraction (TRF) and its individual components (γ- and δ-tocotrienol) were first investigated in vitro in human umbilical vein endothelial cells (HUVEC) and 4T1 mouse mammary cancer cells. Results showed reduced levels of Interkeukin (IL)-8 and IL-6, two pro-angiogenic cytokines in HUVEC treated with palm tocotrienols compared with α-tocopherol (α-T) and control cells (P < 0.05). The production of IL-8 and IL-6 was lowest in δ-tocotrienol (δ-T3)-treated cells followed by γ-tocotrienol (γ-T3) and TRF. There was significant (P < 0.05) reduction in IL-8 and vascular endothelial growth factor (VEGF) production in 4T1 cells treated with TRF or δ-T3. There was decreased expression of VEGF and its receptors; VEGF-R1 (fms-like tyrosine kinase, Flt-1) and VEGF-R2 (Kinase-insert-domain-containing receptor, KDR/Flk-2) in tumour tissues excised from mice supplemented with TRF were observed. There was also decreased expression of VEGF-R2 in lung tissues of mice supplemented with TRF. These observations correlate with the smaller tumour size recorded in the tocotrienol-treated mice. This study confirms previous observations that palm tocotrienols exhibit anti-angiogenic properties that may inhibit tumour progression