Title: Delta Variant Has Americans' Stress Levels Rising Again: Poll
Category: Health News
Created: 8/20/2021 12:00:00 AM
Last Editorial Review: 8/23/2021 12:00:00 AM

Title: Wildfire Smoke Could Raise Odds for Preterm Delivery
Category: Health News
Created: 8/26/2021 12:00:00 AM
Last Editorial Review: 8/26/2021 12:00:00 AM

Pulmonary hypertension (PH) is highly prevalent in patients with interstitial lung disease (ILD) and is associated with increased morbidity and mortality. Widely available noninvasive screening tools are warranted to identify patients at risk for PH, especially severe PH, that could be managed at expert centres. This review summarises current evidence on noninvasive diagnostic modalities and prediction models for the timely detection of PH in patients with ILD. It critically evaluates these approaches and discusses future perspectives in the field. A comprehensive literature search was carried out in PubMed and Scopus, identifying 39 articles that fulfilled inclusion criteria. There is currently no single noninvasive test capable of accurately detecting and diagnosing PH in ILD patients. Estimated right ventricular pressure (RVSP) on Doppler echocardiography remains the single most predictive factor of PH, with other indirect echocardiographic markers increasing its diagnostic accuracy. However, RVSP can be difficult to estimate in patients due to suboptimal views from extensive lung disease. The majority of existing composite scores, including variables obtained from chest computed tomography, pulmonary function tests and cardiopulmonary exercise tests, were derived from retrospective studies, whilst lacking validation in external cohorts. Only two available scores, one based on a stepwise echocardiographic approach and the other on functional parameters, predicted the presence of PH with sufficient accuracy and used a validation cohort. Although several methodological limitations prohibit their generalisability, their use may help physicians to detect PH earlier. Further research on the potential of artificial intelligence may guide a more tailored approach, for timely PH diagnosis.

BACKGROUND:Beneficial effects of breathing at FIO2 < 0.21 on disease outcomes have been reported in previous preclinical and clinical studies. However, the safety and intra-hospital feasibility of breathing hypoxic gas for 5 d have not been established. In this study, we examined the physiologic effects of breathing a gas mixture with FIO2 as low as 0.11 in 5 healthy volunteers.METHODS:All 5 subjects completed the study, spending 5 consecutive days in a hypoxic tent, where the ambient oxygen level was lowered in a stepwise manner over 5 d, from FIO2 of 0.16 on the first day to FIO2 of 0.11 on the fifth day of the study. All the subjects returned to an environment at room air on the sixth day. The subjects' SpO2, heart rate, and breathing frequency were continuously recorded, along with daily blood sampling, neurologic evaluations, transthoracic echocardiography, and mental status assessments.RESULTS:Breathing hypoxia concentration dependently caused profound physiologic changes, including decreased SpO2 and increased heart rate. At FIO2 of 0.14, the mean SpO2 was 92%; at FIO2 of 0.13, the mean SpO2 was 93%; at FIO2 of 0.12, the mean SpO2 was 88%; at FIO2 of 0.11, the mean SpO2 was 85%; and, finally, at an FIO2 of 0.21, the mean SpO2 was 98%. These changes were accompanied by increased erythropoietin levels and reticulocyte counts in blood. All 5 subjects concluded the study with no adverse events. No subjects exhibited signs of mental status changes or pulmonary hypertension.CONCLUSIONS:Results of the current physiologic study suggests that, within a hospital setting, delivering FIO2 as low as 0.11 is feasible and safe in healthy subjects, and provides the foundation for future studies in which therapeutic effects of hypoxia breathing are tested.

Exercise significantly alters human physiological functions, such as increasing cardiac output and muscle blood flow and decreasing glomerular filtration rate (GFR) and liver blood flow, thereby altering the absorption, distribution, metabolism, and excretion of drugs. In this study, we aimed to establish a database of human physiological parameters during exercise and to construct equations for the relationship between changes in each physiological parameter and exercise intensity, including cardiac output, organ blood flow (e.g., muscle blood flow and kidney blood flow), oxygen uptake, plasma pH and GFR, etc. The polynomial equation P = a_iHRⁱ was used for illustrating the relationship between the physiological parameters (P) and heart rate (HR), which served as an index of exercise intensity. The pharmacokinetics of midazolam, quinidine, digoxin, and lidocaine during exercise were predicted by a whole-body physiologically based pharmacokinetic (WB-PBPK) model and the developed database of physiological parameters following administration to 100 virtual subjects. The WB-PBPK model simulation results showed that most of the observed plasma drug concentrations fell within the 5^th–95^th percentiles of the simulations, and the estimated peak concentrations (C_max) and area under the curve (AUC) of drugs were also within 0.5–2.0 folds of observations. Sensitivity analysis showed that exercise intensity, exercise duration, medication time, and alterations in physiological parameters significantly affected drug pharmacokinetics and the net effect depending on drug characteristics and exercise conditions. In conclusion, the pharmacokinetics of drugs during exercise could be quantitatively predicted using the developed WB-PBPK model and database of physiological parameters.

Early detection of drug-drug interactions (DDIs) can facilitate timely drug development decisions, prevent unnecessary restrictions on patient enrollment, resulting in clinical study populations that are not representative of the indicated study population, and allow for appropriate dose adjustments to ensure safety in clinical trials. All of these factors contribute to a streamlined drug approval process and enhanced patient safety. Here we describe a new approach for early prediction of the magnitude of change in exposure for cytochrome P450 (P450) CYP3A4-related DDIs of small-molecule anticancer drugs based on the model-based extrapolation of human-CYP3A4-transgenic mice pharmacokinetics to humans. Victim drugs brigatinib and lorlatinib were evaluated with the new approach in combination with the perpetrator drugs itraconazole and rifampicin. Predictions of the magnitude of change in exposure deviated at most 0.99- to 1.31-fold from clinical trial results for inhibition with itraconazole, whereas exposure predictions for the induction with rifampicin were less accurate, with deviations of 0.22- to 0.48-fold. Results for the early prediction of DDIs and their clinical impact appear promising for CYP3A4 inhibition, but validation with more victim and perpetrator drugs is essential to evaluate the performance of the new method.

ABSTRACTWe document the effort over the last 30 years to respond to the call by women advocates at the International Conference on Population and Development for more woman-initiated single or dual-purpose contraceptive methods by developing the Caya contoured diaphragm, an innovative diaphragm designed to meet the needs of women and their partners and expand options for nonhormonal barrier contraception. We describe the complex and interrelated set of activities undertaken to develop the product using a human-centered design process and how we are working to create a corollary sustainable market. This review includes the evidence generated around improved acceptability among couples in low- and middle-income countries and depicts challenges and practical actions on how to dispel misconceptions about diaphragm use. Importantly, we share programmatic lessons learned on increasing universal access to this new sexual and reproductive health technology. Following our new model for increasing access to new and underutilized methods, Caya is now registered and being marketed in nearly 40 countries worldwide.

ABSTRACTIntroduction:Emergency contraceptive pills (ECPs) are effective and can be used safely at any age repeatedly within the same cycle. They are often favored by youth yet are underutilized. Private facilities can increase ECP access but present barriers including cost. Identifying effective public-sector ECP distribution models can help ensure equitable access. The Malawi Ministry of Health developed a strategy to improve ECP access in 2020. We documented ECP provision through select public, youth-serving channels recommended by the strategy: general and youth-specific outreach, paid and unpaid community health workers (CHWs), and youth clubs.Methods:We conducted this mixed methods study from November 2022–March 2023 in 2 rural districts (Mchinji and Phalombe) implementing the strategy. We conducted qualitative interviews with 10 national stakeholders, 46 providers, and 24 clients aged 15–24 years about ECP service delivery. Additionally, 25 providers collected quantitative tally data about clients seeking ECPs. We analyzed qualitative data using grounded theory and quantitative data descriptively.Results:Stakeholders and providers reported ECP uptake increased in geographies where the strategy was implemented, especially among youth. Providers documented 3,988 client visits for ECPs over 3 months. Of these visits, 26% were from male clients, 36% were from clients aged younger than 20 years, and 64% received ECPs for the first time. Across channels, youth club leaders and unpaid CHWs reported the most client visits per provider and served the youngest clients. However, no ECPs were dispensed during 29% of visits due to stock-outs. While many providers were supportive of youth accessing ECPs, most held unfavorable attitudes toward repeat use.Conclusion:ECP access should be expanded through provision in the studied channels, especially youth clubs and CHWs. However, to meet demand, the supply chain must be strengthened. We recommend addressing providers’ attitudes about repeat use to ensure informed method choice.

ABSTRACTBackground: This analysis aimed to evaluate the effectiveness of eliciting sexual partners from HIV-positive clients using the elicitation box model (where an HIV-positive index can report sexual contacts on paper and insert in a box for a health care provider to contact at a later time) compared to the conventional model (in which a health care provider elicits sexual contacts directly from clients) in Akwa Ibom, Southern Nigeria.Methods: Between March 2021 and April 2022, data were collected from index testing registers at 4 health facilities with a high volume of HIV clients currently on treatment in 4 local government areas in Akwa Ibom State. Primary outcome analyzed was the elicitation ratio (number of partners elicited per HIV-index offered index testing services). Secondary outcomes were the index testing acceptance (index HIV-positive clients accepted index testing service), testing coverage (partners tested for HIV from a list of partners elicited from HIV-index accepted index testing services), testing yield (index partners identified HIV positive from index partners HIV-tested), and linkage rate (index partners identified HIV positive and linked to antiretroviral therapy).Results: Of the total 2,705 index clients offered index testing services, 91.9% accepted, with 2,043 and 439 indexes opting for conventional elicitation and elicitation box models, respectively. A total of 3,796 sexual contacts were elicited: 2,546 using the conventional model (elicitation ratio=1:1) and 1,250 using the elicitation box model (elicitation ratio=1:3). Testing coverage was significantly higher in the conventional compared to the elicitation box model (P<.001). However, there was no significant difference in the testing yield (P=.81) and linkage rate using the conventional compared to elicitation box models (P=.13).Conclusion: The implementation of the elicitation box model resulted in an increase in partner elicitation compared to the conventional model. Increasing the testing coverage by implementing the elicitation box model should be considered.

ABSTRACTIntroduction:Postpartum hemorrhage (PPH) remains the leading cause of maternal mortality. A new clinical intervention (E-MOTIVE) holds the potential to improve early PPH detection and management. We aimed to develop and pilot implementation strategies to support uptake of this intervention in Kenya, Nigeria, South Africa, and Tanzania.Methods:Implementation strategy development: We triangulated findings from qualitative interviews, surveys and a qualitative evidence synthesis to identify current PPH care practices and influences on future intervention implementation. We mapped influences using implementation science frameworks to identify candidate implementation strategies before presenting these at stakeholder consultation and design workshops to discuss feasibility, acceptability, and local adaptations. Piloting: The intervention and implementation strategies were piloted in 12 health facilities (3 per country) over 3 months. Interviews (n=58), case report forms (n=1,269), and direct observations (18 vaginal births, 7 PPHs) were used to assess feasibility, acceptability, and fidelity.Results:Implementation strategy development: Key influences included shortages of drugs, supplies, and staff, limited in-service training, and perceived benefits of the intervention (e.g., more accurate PPH detection and reduced PPH mortality). Proposed implementation strategies included a PPH trolley, on-site simulation-based training, champions, and audit and feedback. Country-specific adaptations included merging the E-MOTIVE intervention with national maternal health trainings, adapting local PPH protocols, and PPH trollies depending on staff needs. Piloting: Intervention and implementation strategy fidelity differed within and across countries. Calibrated drapes resulted in earlier and more accurate PPH detection but were not consistently used at the start. Implementation strategies were feasible to deliver; however, some instances of limited use were observed (e.g., PPH trolley and skills practice after training).Conclusion:Systematic intervention development, piloting, and process evaluation helped identify initial challenges related to intervention fidelity, which were addressed ahead of a larger-scale effectiveness evaluation. This has helped maximize the internal validity of the trial.

Patients with arthritis report using cannabis for pain management, and the major cannabinoid delta-9-tetrahydrocannabinol (⁹-THC) has anti-inflammatory properties, yet the effects of minor cannabinoids on arthritis are largely unknown. The goal of the present study was to determine the antiarthritic potential of the minor cannabinoid delta-8-tetrahydrocannabinol (⁸-THC) using the collagen-induced arthritis (CIA) mouse model. Adult male DBA/1J mice were immunized and boosted 21 days later with an emulsion of collagen and complete Freund’s adjuvant. Beginning on the day of the booster, mice were administered twice-daily injections of ⁸-THC (3 or 30 mg/kg), the steroid dexamethasone (2 mg/kg), or vehicle for two weeks. Dorsal-ventral paw thickness and qualitative measures of arthritis were recorded daily, and latency to fall from an inverted grid was measured on alternating days, to determine arthritis severity and functional impairment. On the final day of testing, spontaneous wire-climbing behavior and temperature preference in a thermal gradient ring were measured to assess CIA-depressed behavior. The ⁸-THC treatment (30 mg/kg) reduced paw swelling and qualitative signs of arthritis. ⁸-THC also blocked CIA-depressed climbing and CIA-induced preference for a heated floor without producing locomotor effects but did not affect latency to fall from a wire grid. In alignment with the morphologic and behavioral assessments in vivo, histology revealed that ⁸-THC reduced synovial inflammation, proteoglycan loss and cartilage and bone erosion in the foot joints in a dose-dependent manner. Together, these findings suggest that ⁸-THC not only blocked morphologic changes but also prevented functional loss caused by collagen-induced arthritis.

Chronic pain conditions affect nearly 20% of the population in the United States. Current medical interventions, such as opioid drugs, are effective at relieving pain but are accompanied by many undesirable side effects. This is one reason increased numbers of chronic pain patients have been turning to Cannabis for pain management. Cannabis contains many bioactive chemical compounds; however, current research looking into lesser-studied minor cannabinoids in Cannabis lacks uniformity between experimental groups and/or excludes female mice from investigation. This makes it challenging to draw conclusions between experiments done with different minor cannabinoid compounds between laboratories or parse out potential sex differences that could be present. We chose five minor cannabinoids found in lower quantities within Cannabis: cannabinol (CBN), cannabidivarin (CBDV), cannabigerol (CBG), 8-tetrahydrocannabinol (8-THC), and 9-tetrahydrocannabivarin (THCV). These compounds were then tested for their cannabimimetic and pain-relieving behaviors in a cannabinoid tetrad assay and a chemotherapy-induced peripheral neuropathy (CIPN) pain model in male and female CD-1 mice. We found that the minor cannabinoids we tested differed in the cannabimimetic behaviors evoked, as well as the extent. We found that CBN, CBG, and high-dose 8-THC evoked some tetrad behaviors in both sexes, while THCV and low-dose 8-THC exhibited cannabimimetic tetrad behaviors only in females. Only CBN efficaciously relieved CIPN pain, which contrasts with reports from other researchers. Together these findings provide further clarity to the pharmacology of minor cannabinoids and suggest further investigation into their mechanism and therapeutic potential.

⁹-Tetrahydrocannabinol (THC) is a psychoactive phytocannabinoid found in the Cannabis sativa plant. THC is primarily metabolized into 11-hydroxy-⁹-tetrahydrocannabinol (11-OH-THC) and 11-nor-9-carboxy-⁹-tetrahydrocannabinol (COOH-THC), which may themselves be psychoactive. There is very little research-based evidence concerning the pharmacokinetics and pharmacodynamics of 11-OH-THC as an individual compound. Male C57BL/6 mice were treated with THC or 11-OH-THC via intraperitoneal injection, tail vein intravenous injection, or oral gavage, and whole-blood compound levels were measured to determine pharmacokinetic parameters [C_max, time to C_max (T_max), elimination half-life, area under the curve, apparent volume of distribution, systemic clearance, terminal rate constant, and absolute bioavailability] while also monitoring changes in catalepsy, body temperature, and nociception. 11-OH-THC achieved a T_max at 30 minutes for all routes of administration. The maximum concentration at 30 minutes was not different between intravenous and intraperitoneal routes, but the oral gavage C_max was significantly lower. THC had a 10-minute time to the maximum concentration, which was the first blood collection time point, for intravenous and intraperitoneal and 60 minutes for oral gavage, with a lower C_max for intraperitoneal and oral gavage compared with intravenous. When accounting for circulating compound levels and ED₅₀ responses, these data suggest that 11-OH-THC was 153% as active as THC in the tail-flick test of nociception and 78% as active as THC for catalepsy. Therefore, 11-OH-THC displayed equal or greater activity than the parent compound THC, even when accounting for pharmacokinetic differences. Thus, the THC metabolite 11-OH-THC likely plays a critical role in the bioactivity of cannabis; understanding its activity when administered directly will aid in the interpretation of future animal and human studies.

People with sickle cell disease (SCD) often experience chronic pain as well as unpredictable episodes of acute pain, which significantly affects their quality of life and life expectancy. Current treatment strategies for SCD-associated pain primarily rely on opioid analgesics, which have limited efficacy and cause serious adverse effects. Cannabis has emerged as a potential alternative, yet its efficacy remains uncertain. In this study, we investigated the antinociceptive effects of ⁹-tetrahydrocannabinol (THC), cannabis’ intoxicating constituent, in male HbSS mice, which express >99% human sickle hemoglobin, and male HbAA mice, which express normal human hemoglobin A, as a control. Acute THC administration (0.1–3 mg/kg^–1, i.p.) dose-dependently reduced mechanical and cold hypersensitivity in human sickle hemoglobin (HbSS) but not human normal hemoglobin A (HbAA) mice. In the tail-flick assay, THC (1 and 3 mg/kg^–1, i.p.) produced substantial antinociceptive effects in HbSS mice. By contrast, THC (1 mg/kg^–1, i.p.) did not alter anxiety-like behavior (elevated plus maze) or long-term memory (24-hour novel object recognition). Subchronic THC treatment (1 and 3 mg/kg^–1, i.p.) provided sustained relief of mechanical hypersensitivity but led to tolerance in cold hypersensitivity in HbSS mice. Together, the findings identify THC as a possible therapeutic option for the management of chronic pain in SCD. Further research is warranted to elucidate its mechanism of action and possible interaction with other cannabis constituents.

The aim of this study was to validate a previously developed deep learning model in 5 independent clinical trials. The predictive performance of this model was compared with the international prognostic index (IPI) and 2 models incorporating radiomic PET/CT features (clinical PET and PET models). Methods: In total, 1,132 diffuse large B-cell lymphoma patients were included: 296 for training and 836 for external validation. The primary outcome was 2-y time to progression. The deep learning model was trained on maximum-intensity projections from PET/CT scans. The clinical PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, SUV_peak, age, and performance status. The PET model included metabolic tumor volume, maximum distance from the bulkiest lesion to another lesion, and SUV_peak. Model performance was assessed using the area under the curve (AUC) and Kaplan–Meier curves. Results: The IPI yielded an AUC of 0.60 on all external data. The deep learning model yielded a significantly higher AUC of 0.66 (P < 0.01). For each individual clinical trial, the model was consistently better than IPI. Radiomic model AUCs remained higher for all clinical trials. The deep learning and clinical PET models showed equivalent performance (AUC, 0.69; P > 0.05). The PET model yielded the highest AUC of all models (AUC, 0.71; P < 0.05). Conclusion: The deep learning model predicted outcome in all trials with a higher performance than IPI and better survival curve separation. This model can predict treatment outcome in diffuse large B-cell lymphoma without tumor delineation but at the cost of a lower prognostic performance than with radiomics.

The role of gastrin-releasing peptide receptor (GRPR) in various diseases, including cancer, has been extensively studied and has emerged as a promising therapeutic target. In this study, we successfully achieved the use of [²¹²Pb]Pb-DOTAM-GRPR1, comprising the α-particle generator, ²¹²Pb, combined with a GRPR-targeting peptide, GRPR1, in a prostate cancer model. Methods: Pharmacokinetics, toxicity, radiation dosimetry, and efficacy were assessed in GRPR-positive prostate tumor–bearing mice after intravenous administration of [²¹²Pb]Pb-DOTAM-GRPR1 (where DOTAM is 1,4,7,10-tetrakis(carbamoylmethyl)-1,4,7,10-tetraazacyclododecane). Results: Preclinical studies have shown tumor targeting of up to 5 percent injected dose per gram over 24 h, and optimization of the drug formulation and quantity has led to minimized oxidation and off-target binding, respectively. Particularly, an increase in peptide amount from 28 to 280 ng was shown to reduce off-target uptake, especially at the level of the pancreas, by about 30%. Furthermore, dosimetry studies confirmed the kidney as the dose-limiting organ, and toxicity studies revealed that a nontoxic dose of up to 1,665 kBq could be injected into mice. Efficacy studies indicated a median survival time of 9 wk in the control group, which received only a buffer solution, compared with 19 wk in the group that received 4 injections of 370 kBq at 3-wk intervals. Conclusion: Taken together, these combined data demonstrate the safety, tolerability, and efficacy of [²¹²Pb]Pb-DOTAM-GRPR1, thus warranting further exploration in clinical trials.

Historically, the intestinal lymphatics were considered passive conduits for fluids, immune cells, dietary lipids, lipid soluble vitamins, and lipophilic drugs. Studies of intestinal lymphatic drug delivery in the late 20th century focused primarily on the drugs’ physicochemical properties, especially high lipophilicity, that resulted in intestinal lymphatic transport. More recent discoveries have changed our traditional view by demonstrating that the lymphatics are active, plastic, and tissue-specific players in a range of biological and pathological processes, including within the intestine. These findings have, in turn, inspired exploration of lymph-specific therapies for a range of diseases, as well as the development of more sophisticated strategies to actively deliver drugs or vaccines to the intestinal lymph, including a range of nanotechnologies, lipid prodrugs, and lipid-conjugated materials that "hitchhike" onto lymphatic transport pathways. With the increasing development of novel therapeutics such as biologics, there has been interest in whether these therapeutics are absorbed and transported through intestinal lymph after oral administration. Here we review the current state of understanding of the anatomy and physiology of the gastrointestinal lymphatic system in health and disease, with a focus on aspects relevant to drug delivery. We summarize the current state-of-the-art approaches to deliver drugs and quantify their uptake into the intestinal lymphatic system. Finally, and excitingly, we discuss recent examples of significant pharmacokinetic and therapeutic benefits achieved via intestinal lymphatic drug delivery. We also propose approaches to advance the development and clinical application of intestinal lymphatic delivery strategies in the future.

This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts, such as concentration-response curves, additive effects, and predictive models, are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. Although various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors, such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care.

Rare genetic conditions are challenging for the primary care provider to manage without proper guidelines. This clinical review is designed to assist the pediatrician, family physician, or internist in the primary care setting to manage the complexities of 16p11.2 deletion syndrome. A multidisciplinary medical home with the primary care provider leading the care and armed with up-to-date guidelines will prove most helpful to the rare genetic patient population. A special focus on technology to fill gaps in deficits, review of case studies on novel medical treatments, and involvement with the educational system for advocacy with an emphasis on celebrating diversity will serve the rare genetic syndrome population well.

We identified a de novo heterozygous transient receptor potential cation channel subfamily M (melastatin) member 3 (TRPM3) missense variant, p.(Asn1126Asp), in a patient with developmental delay and manifestations of cerebral palsy (CP) using phenotype-driven prioritization analysis of whole-genome sequencing data with Exomiser. The variant is localized in the functionally important ion transport domain of the TRPM3 protein and predicted to impact the protein structure. Our report adds TRPM3 to the list of Mendelian disease–associated genes that can be associated with CP and provides further evidence for the pathogenicity of the variant p.(Asn1126Asp).

PURPOSE

Currently, 40% of counties in the United States do not have an obstetrician or midwife, and in rural areas the likelihood of childbirth being attended to by a family medicine (FM) physician is increasing. We sought to characterize the effect of the FM presence on unit culture and a key perinatal quality metric in Iowa hospital intrapartum units.

Background

In an evolving landscape of practices and policies, reviewing and incorporating the latest scientific evidence is necessary to ensure optimal clinical management for people with opioid use disorder. We provide a synopsis of the 2024 update of the 2018 National Guideline for the Clinical Management of Opioid Use Disorder, from the Canadian Research Initiative in Substance Matters.

The respiratory literature, both written and in online formats, is growing exponentially. Capturing quality content, to meet the learning needs of those working in all fields of respiratory medicine and delivering it in a palatable, accessible format is challenging but paramount. In this article we discuss ways to determine the information content and review different methods of delivering this content to those who need it.

Deller on politics, music and his film Everybody in the Place, now showing at The Vinyl Factory's Reverb exhibition.

The post Interview: Jeremy Deller appeared first on Fact Magazine.

Putting aside my natural annoyance at Metal Gear Solid Delta: Snake Eater for almost beating out the Twarhammer series in the headline real estate wars, I am more than a little excited to play. Some days, you simply must feast on a tree frog, and while we still don’t have a solid release date, that day doesn’t feel too far away. Good news for stealth fans, and perhaps gooder news for a dozen strapline writers sweating profusely, soiling themselves in anticipation of using “kept you waiting, huh?”.

Until then, I at least have a steady drip feed of new information to keep me sated, the latest of which is the substantial hint that there'll be some new dialogue in the game, as per the video below. Alongside that, the previously pseudonymous Suzetta Miñet - who was credited with voicing EVA in MGS3 and Peace Walker - has revealed herself to be Jodi Benson, the voice of Ariel in Disney’s The Little Mermaid. Cheers for the spot, Automaton West.

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Sega are delisting several bundles of 'classic' games from digital stores, along with "select individual" games. On Steam specifically, this adds up to over 60 games in total, including several actual classics including the original Streets Of Rage trilogy, Crazy Taxi, and Jet Set Radio.

The games will be removed on December 6th but will remain playable to those who already own them.

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After their initial training phase, AI algorithms can’t update and learn from new data, meaning tech companies have to keep training new models from scratch

Supremacy, a new book from tech journalist Parmy Olson, takes us inside the rise of machine learning and AI, and examines the people behind it

Large language models can be used to scam humans, but AI is also susceptible to being scammed – and some models are more gullible than others

The software used to control a robot is normally highly adapted to its specific physical set up. But now researchers have created a single general-purpose robotic control policy that can operate robotic arms, wheeled robots, quadrupeds, and even drones.

One of the biggest challenges when it comes to applying machine learning to robotics is the paucity of data. While computer vision and natural language processing can piggyback off the vast quantities of image and text data found on the Internet, collecting robot data is costly and time-consuming.

To get around this, there have been growing efforts to pool data collected by different groups on different kinds of robots, including the Open X-Embodiment and DROID datasets. The hope is that training on diverse robotics data will lead to “positive transfer,” which refers to when skills learned from training on one task help to boost performance on another.

The problem is that robots often have very different embodiments—a term used to describe their physical layout and suite of sensors and actuators—so the data they collect can vary significantly. For instance, a robotic arm might be static, have a complex arrangement of joints and fingers, and collect video from a camera on its wrist. In contrast, a quadruped robot is regularly on the move and relies on force feedback from its legs to maneuver. The kinds of tasks and actions these machines are trained to carry out are also diverse: The arm may pick and place objects, while the quadruped needs keen navigation.

That makes training a single AI model for robots on these large collections of data challenging, says Homer Walke, a Ph.D. student at the University of California, Berkeley. So far, most attempts have either focused on data from a narrower selection of similar robots or researchers have manually tweaked data to make observations from different robots more similar. But in research to be presented at the Conference on Robot Learning (CoRL) in Munich in November, they unveiled a new model called CrossFormer that can train on data from a diverse set of robots and control them just as well as specialized control policies.

“We want to be able to train on all of this data to get the most capable robot,” says Walke. “The main advance in this paper is working out what kind of architecture works the best for accommodating all these varying inputs and outputs.”

How to control diverse robots with the same AI model

The team used the same model architecture that powers large language model, known as a transformer. In many ways, the challenge the researchers were trying to solve is not dissimilar to that facing a chatbot, says Walke. In language modeling, the AI has to to pick out similar patterns in sentences with different lengths and word orders. Robot data can also be arranged in a sequence much like a written sentence, but depending on the particular embodiment, observations and actions vary in length and order too.

“Words might appear in different locations in a sentence, but they still mean the same thing,” says Walke. “In our task, an observation image might appear in different locations in the sequence, but it’s still fundamentally an image and we still want to treat it like an image.”

UC Berkeley/Carnegie Mellon University

Most machine learning approaches work through a sequence one element at a time, but transformers can process the entire stream of data at once. This allows them to analyze the relationship between different elements and makes them better at handling sequences that are not standardized, much like the diverse data found in large robotics datasets.

Walke and his colleagues aren’t the first to train transformers on large-scale robotics data. But previous approaches have either trained solely on data from robotic arms with broadly similar embodiments or manually converted input data to a common format to make it easier to process. In contrast, CrossFormer can process images from cameras positioned above a robot, at head height or on a robotic arms wrist, as well as joint position data from both quadrupeds and robotic arms, without any tweaks.

The result is a single control policy that can operate single robotic arms, pairs of robotic arms, quadrupeds, and wheeled robots on tasks as varied as picking and placing objects, cutting sushi, and obstacle avoidance. Crucially, it matched the performance of specialized models tailored for each robot and outperformed previous approaches trained on diverse robotic data. The team even tested whether the model could control an embodiment not included in the dataset—a small quadcopter. While they simplified things by making the drone fly at a fixed altitude, CrossFormer still outperformed the previous best method.

“That was definitely pretty cool,” says Ria Doshi, an undergraduate student at Berkeley. “I think that as we scale up our policy to be able to train on even larger sets of diverse data, it’ll become easier to see this kind of zero shot transfer onto robots that have been completely unseen in the training.”

The limitations of one AI model for all robots

The team admits there’s still work to do, however. The model is too big for any of the robots’ embedded chips and instead has to be run from a server. Even then, processing times are only just fast enough to support real-time operation, and Walke admits that could break down if they scale up the model. “When you pack so much data into a model it has to be very big and that means running it for real-time control becomes difficult.”

One potential workaround would be to use an approach called distillation, says Oier Mees, a postdoctoral research at Berkley and part of the CrossFormer team. This essentially involves training a smaller model to mimic the larger model, and if successful can result in similar performance for a much smaller computational budget.

But of more importance than the computing resource problem is that the team failed to see any positive transfer in their experiments, as CrossFormer simply matched previous performance rather than exceeding it. Walke thinks progress in computer vision and natural language processing suggests that training on more data could be the key.

Others say it might not be that simple. Jeannette Bohg, a professor of robotics at Stanford University, says the ability to train on such a diverse dataset is a significant contribution. But she wonders whether part of the reason why the researchers didn’t see positive transfer is their insistence on not aligning the input data. Previous research that trained on robots with similar observation and action data has shown evidence of such cross-overs. “By getting rid of this alignment, they may have also gotten rid of this significant positive transfer that we’ve seen in other work,” Bohg says.

It’s also not clear if the approach will boost performance on tasks specific to particular embodiments or robotic applications, says Ram Ramamoorthy, a robotics professor at Edinburgh University. The work is a promising step towards helping robots capture concepts common to most robots, like “avoid this obstacle,” he says. But it may be less useful for tackling control problems specific to a particular robot, such as how to knead dough or navigate a forest, which are often the hardest to solve.

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

ICRA@40: 23–26 September 2024, ROTTERDAM, NETHERLANDS

IROS 2024: 14–18 October 2024, ABU DHABI, UAE

ICSR 2024: 23–26 October 2024, ODENSE, DENMARK

Cybathlon 2024: 25–27 October 2024, ZURICH

Enjoy today’s videos!

Zipline has (finally) posted some real live footage of its new Platform 2 drone, and while it’s just as weird looking as before, it seems to actually work really well.

[ Zipline ]

I appreciate Disney Research’s insistence on always eventually asking, “okay, but can we get this to work on a real robot in the real world?”

[ Paper from ETH Zurich and Disney Research [PDF] ]

In this video, we showcase our humanoid robot, Nadia, being remotely controlled for boxing training using a simple VR motion capture setup. A remote user takes charge of Nadia’s movements, demonstrating the power of our advanced teleoperation system. Watch as Nadia performs precise boxing moves, highlighting the potential for humanoid robots in dynamic, real-world tasks.

[ IHMC ]

Guide dogs are expensive to train and maintain—if available at all. Because of these limiting factors, relatively few blind people use them. Computer science assistant professor Donghyun Kim and Ph.D candidate Hochul Hwang are hoping to change that with the help of UMass database analyst Gail Gunn and her guide dog, Brawny.

[ University of Massachusetts, Amherst ]

Thanks Julia!

The current paradigm for motion planning generates solutions from scratch for every new problem, which consumes significant amounts of time and computational resources. Our approach builds a large number of complex scenes in simulation, collects expert data from a motion planner, then distills it into a reactive generalist policy. We then combine this with lightweight optimization to obtain a safe path for real world deployment.

[ Neural MP ]

A nice mix of NAO and AI for embodied teaching.

[ Aldebaran ]

When retail and logistics giant Otto Group set out to strengthen its operational efficiency and safety, it turned to robotics and automation. The Otto Group has become the first company in Europe to deploy the mobile case handling robot Stretch, which unloads floor-loaded trailers and containers.

[ Boston Dynamics ]

From groceries to last-minute treats, Wing is here to make sure deliveries arrive quickly and safely. Our latest aircraft design features a larger, more standardized box and can carry a higher payload which came directly from customer and partner feedback.

[ Wing ]

It’s the jacket that gets me.

[ Devanthro ]

In this video, we introduce Rotograb, a robotic hand that merges the dexterity of human hands with the strength and efficiency of industrial grippers. Rotograb features a new rotating thumb mechanism, allowing for precision in-hand manipulation and power grasps while being adaptable. The robotic hand was developed by students during “Real World Robotics”, a master course by the Soft Robotics Lab at ETH Zurich.

[ ETH Zurich ]

A small scene where Rémi, our distinguished professor, is teaching chess to the person remotely operating Reachy! The grippers allow for easy and precise handling of chess pieces, even the small ones! The robot shown in this video is the Beta version of Reachy 2, our new robot coming very soon!

[ Pollen ]

Enhancing the adaptability and versatility of unmanned micro aerial vehicles (MAVs) is crucial for expanding their application range. In this article, we present a bimodal reconfigurable robot capable of operating in both regular quadcopter flight mode and a unique revolving flight mode, which allows independent control of the vehicle’s position and roll-pitch attitude.

[ City University Hong Kong ]

The Parallel Continuum Manipulator (PACOMA) is an advanced robotic system designed to replace traditional robotic arms in space missions, such as exploration, in-orbit servicing, and docking. Its design emphasizes robustness against misalignments and impacts, high precision and payload capacity, and sufficient mechanical damping for stable, controlled movements.

[ DFKI Robotics Innovation Center ]

Even the FPV pros from Team BlackSheep do, very occasionally, crash.

[ Team BlackSheep ]

This is a one-hour uninterrupted video of a robot cleaning bathrooms in real time. I’m not sure if it’s practical, but I am sure that it’s impressive, honestly.

[ Somatic ]

Donald Trump will embrace the truth Joe Biden has refused to countenance: Israel's enemies are America's enemies. And when Israel defeats its enemies, America wins.

According to a report Tuesday, the league deliberately decided not to impose an immediate fine on San Francisco 49ers defensive end Nick Bosa for wearing a "Make America Great Again" hat during a postgame television interview.

In an interview with IT World Canada, consulting giant Deloitte highlighted the importance of an ecosystem-based approach to tackle issues around digital equity in Canada and service delivery challenges in the public sector. “Our strong view is that the people of Canada benefit when there’s effective collaboration between public and private organizations, including on critical […]

A woman's brain was scanned throughout her pregnancy, adding to the growing body of evidence that dramatic remodelling takes place in preparation for motherhood

Canada Post workers might soon be putting down their mailbags and grabbing picket signs

Delta Goodrem and her revolving chair have proved their star power, helping to reverse Nine’s horror start to the year.

A SpaceX capsule carrying the crew parachuted before dawn into the Gulf of Mexico just off the Florida coast.

Microsoft works to make Recall "secure and trusted" after security complaints.

The 16GB RAM upgrade is one of many welcome, if incremental, improvements.

Despite their often dangerous stings, these creatures create serene scenes as they float through the deep sea

The world's first wooden satellite arrived at the International Space Station this week.

FrontierMath's difficult questions remain unpublished so that AI companies can't train against it.

On May 13, 1985, after a long standoff, Philadelphia municipal authorities dropped a bomb on the headquarters of the African-American radical group MOVE. In the documentary Let the Fire Burn, director Jason Osder uses archival footage to chronicle the years of tension that ended in tragedy.

1. Bulldozer justice: SC lays down pan-India guidelines for demolition of properties, says Executive can’t become judge and accused, convicts have certain rights  The Hindu
2. "House Embodies Hope": Supreme Court Demolishes 'Bulldozer Justice' Idea  NDTV
3. Unconstitutional to demolish house without following due process merely because they are involved in a crime: SC  The Indian Express
4. Supreme Court on bulldozer action: ‘No demolition without following guidelines, 15-day notice’  Hindustan Times
5. Bulldozer justice: Executive can't become judge, demolish house of accused, SC says  The Times of India