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Background Previous research has investigated utilization rates, who sees chiropractors, for what reasons, and the type of care that chiropractors provide. However, these studies have not been comprehensively synthesized. We aimed to give a global overview by summarizing the current literature on the utilization of chiropractic services, reasons for seeking care, patient profiles, and assessment and treatment provided. Methods Systematic searches were conducted in MEDLINE, CINAHL, and Index to Chiropractic Literature using keywords and subject headings (MeSH or ChiroSH terms) from database inception to January 2016. Eligible studies: 1) were published in English or French; 2) were case series, descriptive, cross-sectional, or cohort studies; 3) described patients receiving chiropractic services; and 4) reported on the following theme(s): utilization rates of chiropractic services; reasons for attending chiropractic care; profiles of chiropractic patients; or, types of chiropractic services provided. Paired reviewers independently screened all citations and data were extracted from eligible studies. We provided descriptive numerical analysis, e.g. identifying the median rate and interquartile range (e.g., chiropractic utilization rate) stratified by study population or condition. Results The literature search retrieved 14,149 articles; 328 studies (reported in 337 articles) were relevant and reported on chiropractic utilization (245 studies), reason for attending chiropractic care (85 studies), patient demographics (130 studies), and assessment and treatment provided (34 studies). Globally, the median 12-month utilization of chiropractic services was 9.1% (interquartile range (IQR): 6.7%-13.1%) and remained stable between 1980 and 2015. Most patients consulting chiropractors were female (57.0%, IQR: 53.2%-60.0%) with a median age of 43.4 years (IQR: 39.6-48.0), and were employed (median: 77.3%, IQR: 70.3%-85.0%). The most common reported reasons for people attending chiropractic care were (median) low back pain (49.7%, IQR: 43.0%-60.2%), neck pain (22.5%, IQR: 16.3%-24.5%), and extremity problems (10.0%, IQR: 4.3%-22.0%). The most common treatment provided by chiropractors included (median) spinal manipulation (79.3%, IQR: 55.4%-91.3%), soft-tissue therapy (35.1%, IQR: 16.5%-52.0%), and formal patient education (31.3%, IQR: 22.6%-65.0%). Conclusions This comprehensive overview on the world-wide state of the chiropractic profession documented trends in the literature over the last four decades. The findings support the diverse nature of chiropractic practice, although common trends emerged.

On 7 October 2023, a mass-casualty attack at the Nova festival in Israel created an unprecedented convergence of collective trauma and altered states of consciousness. Many survivors were under the influence of psychedelics or other psychoactive substances at the time of the attack. This study explored how survivors made sense of and navigated recovery, with a focus on relational, community, and cultural processes. We conducted semi-structured interviews with 45 Israeli survivors (25 male, 20 female), recruited through a nonprofit organization that provides trauma support. All participants had been under the influence of at least one psychoactive substance during the attack and were engaged in psychological support afterward. Data were analysed using Reflexive Thematic Analysis (Braun & Clarke [2019]. Reflecting on reflexive thematic analysis. , (4), 589-597) with a phenomenological orientation to lived experience. Reflexivity was supported by journaling, peer debriefing, and a positionality statement. Two interrelated recovery pathways emerged from survivors' narratives: (1) Interpersonal and Therapeutic Supports (psychotherapy, therapeutic alliance, and peer solidarity) and (2) Collective Healing Practices (grassroots initiatives, community rituals, and culturally meaningful commemorations). Recovery from the Nova attack appears to be rooted in multisystemic and culturally significant contexts. In fact, psychedelic experiences became part of survivors' trauma stories not in isolation but when supported by therapeutic, peer, and community frameworks. These findings underscore the importance of culturally sensitive, system-level approaches to collective trauma recovery and emphasize the need for trauma services that incorporate community-led care and nonjudgmental engagement with altered states of consciousness.

In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the different parts of the system and enables to examine how global and complex functions might emerge from network topology. Previous work revealed that the human brain features 'small world' characteristics and that cortical hubs tend to interconnect among themselves. However, in order to fully understand the topological structure of hubs, and how their profile reflect the brain's global functional organization, one needs to go beyond the properties of a specific hub and examine the various structural layers that make up the network. To address this topic further, we applied an analysis known in statistical physics and network theory as k-shell decomposition analysis. The analysis was applied on a human cortical network, derived from MRI\\DSI data of six participants. Such analysis enables us to portray a detailed account of cortical connectivity focusing on different neighborhoods of inter-connected layers across the cortex. Our findings reveal that the human cortex is highly connected and efficient, and unlike the internet network contains no isolated nodes. The cortical network is comprised of a nucleus alongside shells of increasing connectivity that formed one connected giant component, revealing the human brain's global functional organization. All these components were further categorized into three hierarchies in accordance with their connectivity profile, with each hierarchy reflecting different functional roles. Such a model may explain an efficient flow of information from the lowest hierarchy to the highest one, with each step enabling increased data integration. At the top, the highest hierarchy (the nucleus) serves as a global interconnected collective and demonstrates high correlation with consciousness related regions, suggesting that the nucleus might serve as a platform for consciousness to emerge.

The Vegetative State (VS) is a severe disorder of consciousness in which patients are awake but display no signs of awareness. Yet, recent functional magnetic resonance imaging (fMRI) studies have demonstrated evidence for covert awareness in VS patients by recording specific brain activations during a cognitive task. However, the possible existence of incommunicable subjective emotional experiences in VS patients remains largely unexplored. This study aimed to probe the question of whether VS patients retain a brain ability to selectively process external stimuli according to their emotional value and look for evidence of covert emotional awareness in patients. In order to explore these questions we employed the emotive impact of observing personally familiar faces, known to provoke specific perceptual as well as emotional brain activations. Four VS patients and thirteen healthy controls first underwent an fMRI scan while viewing pictures of non-familiar faces, personally familiar faces and pictures of themselves. In a subsequent imagery task participants were asked to actively imagine one of their parent's faces. Analyses focused on face and familiarity selective regional brain activations and inter-regional functional connectivity. Similar to controls, all patients displayed face selective brain responses with further limbic and cortical activations elicited by familiar faces. In patients as well as controls, Connectivity was observed between emotional, visual and face specific areas, suggesting aware emotional perception. This connectivity was strongest in the two patients who later recovered. Notably, these two patients also displayed selective amygdala activation during familiar face imagery, with one further exhibiting face selective activations, indistinguishable from healthy controls. Taken together, these results show that selective emotional processing can be elicited in VS patients both by external emotionally salient stimuli and by internal cognitive processes, suggesting the ability for covert emotional awareness of self and the environment in VS patients.

The perioperative use of the β-adrenergic blocker, propranolol, and/or the semi-selective COX-2 inhibitor, etodolac, has improved biomarkers of cancer metastasis in several small randomized controlled trials (RCTs). In colorectal cancer (CRC) patients, the combined regimen showed potential to improve disease-free survival (DFS). We report data from our four RCTs including 148 patients with breast (n = 38), colorectal (n = 34 & n = 46), and pancreatic (n = 30) cancers. Treatment began 5 days pre-operatively, and continued for 5-30 postoperatively. Propranolol (slow-release) was initiated at 20 mg twice daily (b.i.d), increased to 80 mg b.i.d on surgery day, and gradually decreased thereafter to 20 mg b.i.d. Etodolac was provided at 400 mg b.i.d. The primary endpoints were perioperative safety outcomes, including adverse events (AEs) up to 30-day postoperatively, and 16 blood indices. Secondary outcomes were long-term oncological outcomes of 8-year DFS and overall survival (OS). Bradycardia occurred in 12% of treated vs. 3% of placebo patients (p = 0.057), and was easily resolved by temporary withholding β-blockade. Weakness, nausea, pain, infection, bleeding, leakage, tissue-healing, or death were not significantly affected. Drug treatment promoted eosinophils in pancreatic cancer patients (p = 0.015), increased potassium (p = 0.013), and decreased albumin (p = 0.016) in CRC patients; however, these effects did not remain significant after false discovery rate (FDR) correction. In CRC, treatment improved 8-year DFS (2/15 vs. 9/18, p = 0.034), although this exploratory analysis was underpowered. These findings suggest the safety of this inexpensive and easy-to-implement perioperative propranolol and etodolac regimen in patients participating in these RCTs. https://clinicaltrials.gov/study/NCT00502684, https://clinicaltrials.gov/study/NCT00888797, https://clinicaltrials.gov/study/NCT03919461, https://clinicaltrials.gov/study/NCT03838029, identifier NCT00502684, NCT00888797, NCT03919461, NCT03838029.

Background The Vegetative State (VS) is a severe disorder of consciousness in which patients are awake but display no signs of awareness. Yet, recent functional magnetic resonance imaging (fMRI) studies have demonstrated evidence for covert awareness in VS patients by recording specific brain activations during a cognitive task. However, the possible existence of incommunicable subjective emotional experiences in VS patients remains largely unexplored. This study aimed to probe the question of whether VS patients retain a brain ability to selectively process external stimuli according to their emotional value and look for evidence of covert emotional awareness in patients. Methods and Findings In order to explore these questions we employed the emotive impact of observing personally familiar faces, known to provoke specific perceptual as well as emotional brain activations. Four VS patients and thirteen healthy controls first underwent an fMRI scan while viewing pictures of non-familiar faces, personally familiar faces and pictures of themselves. In a subsequent imagery task participants were asked to actively imagine one of their parent's faces. Analyses focused on face and familiarity selective regional brain activations and inter-regional functional connectivity. Similar to controls, all patients displayed face selective brain responses with further limbic and cortical activations elicited by familiar faces. In patients as well as controls, Connectivity was observed between emotional, visual and face specific areas, suggesting aware emotional perception. This connectivity was strongest in the two patients who later recovered. Notably, these two patients also displayed selective amygdala activation during familiar face imagery, with one further exhibiting face selective activations, indistinguishable from healthy controls. Conclusions Taken together, these results show that selective emotional processing can be elicited in VS patients both by external emotionally salient stimuli and by internal cognitive processes, suggesting the ability for covert emotional awareness of self and the environment in VS patients.

The 2020 SARS-CoV-2 coronavirus pandemic highlighted the urgent need for novel small molecule antiviral drugs. (S)- DNDI-6510 is a non-covalent SARS-CoV-2 main protease inhibitor developed by the open science collaboration COVID Moonshot. Here, we report on the metabolic and toxicologic optimization of the lead series previously disclosed by the COVID Moonshot Initiative, leading up to the selection of (S)- DNDI-6510 as the preclinical candidate. We describe the thorough profiling of the series, identifying key risks such as formation of genotoxic metabolites and high clearance, which were successfully addressed during lead optimization. In addition, we disclose the and evaluation of (S)- DNDI-6510 in pharmacokinetic and pharmacodynamic models, exploring multiple approaches to ameliorate rodent-specific metabolic clearance, and show that both co-dosing of (S)- DNDI-6510 with an ABT inhibitor and utilizing a metabolically humanized mouse model (8HUM) achieve significant improvements in exposure. Through comparisons of ABT co-dosing and humanized mouse models in efficacy experiments, we demonstrate that continuous exposure over cellular EC is required for SARS-CoV-2 antiviral efficacy in an antiviral model using a mouse-adapted SARS-CoV-2 strain. Finally, (S)- DNDI-6510 was assessed in maximum tolerated dose experiments in two species, demonstrating significant in vivo PXR-linked auto-induction of metabolism, leading to the discontinuation of this compound. In summary, we report the successful effort to overcome series-specific AMES liabilities in a lead development program. Downstream optimization of existing series will require in-depth optimization of rodent-specific liabilities and metabolic induction profile.

Text-to-image diffusion models can synthesize high-quality images, but they have various limitations. Here we highlight a common failure mode of these models, namely, generating uncommon concepts and structured concepts like hand palms. We show that their limitation is partly due to the long-tail nature of their training data: web-crawled data sets are strongly unbalanced, causing models to under-represent concepts from the tail of the distribution. We characterize the effect of unbalanced training data on text-to-image models and offer a remedy. We show that rare concepts can be correctly generated by carefully selecting suitable generation seeds in the noise space, using a small reference set of images, a technique that we call SeedSelect. SeedSelect does not require retraining or finetuning the diffusion model. We assess the faithfulness, quality and diversity of SeedSelect in creating rare objects and generating complex formations like hand images, and find it consistently achieves superior performance. We further show the advantage of SeedSelect in semantic data augmentation. Generating semantically appropriate images can successfully improve performance in few-shot recognition benchmarks, for classes from the head and from the tail of the training data of diffusion models

In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the different parts of the system and enables to examine how global and complex functions might emerge from network topology. Previous work revealed that the human brain features 'small world' characteristics and that cortical hubs tend to interconnect among themselves. However, in order to fully understand the topological structure of hubs one needs to go beyond the properties of a specific hub and examine the various structural layers of the network. To address this topic further, we applied an analysis known in statistical physics and network theory as k-shell decomposition analysis. The analysis was applied on a human cortical network, derived from MRI data of six participants. Such analysis enables us to portray a detailed account of cortical connectivity focusing on different neighborhoods of interconnected layers across the cortex. Our findings reveal that the human cortex is highly connected and efficient, and unlike the internet network contains no isolated nodes. The cortical network is comprised of a nucleus alongside shells of increasing connectivity that formed one connected giant component. All these components were further categorized into three hierarchies in accordance with their connectivity profile, with each hierarchy reflecting different functional roles. Such a model may explain an efficient flow of information from the lowest hierarchy to the highest one, with each step enabling increased data integration. At the top, the highest hierarchy (the nucleus) serves as a global interconnected collective and demonstrates high correlation with consciousness related regions, suggesting that the nucleus might serve as a platform for consciousness to emerge.

This chapter considers the basic types of sensors that are used in the mobile robots. It also considers the principle of operation of these basic types of sensors. Bumper is one of the most basic and commonly used sensors. The main purpose of the bumper is to signalize that the movement zone's boundary is reached and no further movement in this direction is possible. The odometry sensor measures the length of the robot's trajectory that is necessary, especially for mobile robots. A distance sensor, also known as a range finder, enables a robot to detect obstacles in its path. Unlike the bumper switches that alert engineers when they have been hit, the range finder sensor can alert them to an obstacle in the path of the robot prior to hitting it. The most useful in robotics are laser and ultrasonic rangefinders. The main types of laser rangefinders are time‐of‐flight, phase‐shift, triangulation, and interference.