The malicious use of artificial intelligence is growing rapidly, creating major security threats for individuals and the healthcare sector. Individuals with mental illness may be especially vulnerable. Healthcare provider data are a prime target for cybercriminals. There is a need to improve cybersecurity to detect and prevent cyberattacks against individuals and the healthcare sector, including the use of artificial intelligence predictive tools.

Clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) for treatment of treatment-resistant depression (TRD) vary widely and there is no mood rating scale that is standard for assessing rTMS outcome. It remains unclear whether TMS is as efficacious in older adults with late-life depression (LLD) compared to younger adults with major depressive disorder (MDD). This study examined the effect of age on outcomes of rTMS treatment of adults with TRD. Self-report and observer mood ratings were measured weekly in 687 subjects ages 16–100 years undergoing rTMS treatment using the Inventory of Depressive Symptomatology 30-item Self-Report (IDS-SR), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item, and Hamilton Depression Rating Scale 17-item (HDRS). All rating scales detected significant improvement with treatment; response and remission rates varied by scale but not by age (response/remission ≥ 60: 38%–57%/25%–33%; <60: 32%–49%/18%–25%). Proportional hazards models showed early improvement predicted later improvement across ages, though early improvements in PHQ and HDRS were more predictive of remission in those < 60 years (relative to those ≥ 60) and greater baseline IDS burden was more predictive of non-remission in those ≥ 60 years (relative to those < 60). These results indicate there is no significant effect of age on treatment outcomes in rTMS for TRD, though rating instruments may differ in assessment of symptom burden between younger and older adults during treatment.

With the recent advances in artificial intelligence (AI), patients are increasingly exposed to misleading medical information. Generative AI models, including large language models such as ChatGPT, create and modify text, images, audio and video information based on training data. Commercial use of generative AI is expanding rapidly and the public will routinely receive messages created by generative AI. However, generative AI models may be unreliable, routinely make errors and widely spread misinformation. Misinformation created by generative AI about mental illness may include factual errors, nonsense, fabricated sources and dangerous advice. Psychiatrists need to recognise that patients may receive misinformation online, including about medicine and psychiatry.

The recent achievement of fusion ignition with laser-driven technologies at the National Ignition Facility sets a historic accomplishment in fusion energy research. This accomplishment paves the way for using laser inertial fusion as a viable approach for future energy production. Europe has a unique opportunity to empower research in this field internationally, and the scientific community is eager to engage in this journey. We propose establishing a European programme on inertial-fusion energy with the mission to demonstrate laser-driven ignition in the direct-drive scheme and to develop pathway technologies for the commercial fusion reactor. The proposed roadmap is based on four complementary axes: (i) the physics of laser–plasma interaction and burning plasmas; (ii) high-energy high repetition rate laser technology; (iii) fusion reactor technology and materials; and (iv) reinforcement of the laser fusion community by international education and training programmes. We foresee collaboration with universities, research centres and industry and establishing joint activities with the private sector involved in laser fusion. This project aims to stimulate a broad range of high-profile industrial developments in laser, plasma and radiation technologies along with the expected high-level socio-economic impact.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

The IntCal family of radiocarbon (14C) calibration curves is based on research spanning more than three decades. The IntCal group have collated the 14C and calendar age data (mostly derived from primary publications with other types of data and meta-data) and, since 2010, made them available for other sorts of analysis through an open-access database. This has ensured transparency in terms of the data used in the construction of the ratified calibration curves. As the IntCal database expands, work is underway to facilitate best practice for new data submissions, make more of the associated metadata available in a structured form, and help those wishing to process the data with programming languages such as R, Python, and MATLAB. The data and metadata are complex because of the range of different types of archives. A restructured interface, based on the “IntChron” open-access data model, includes tools which allow the data to be plotted and compared without the need for export. The intention is to include complementary information which can be used alongside the main 14C series to provide new insights into the global carbon cycle, as well as facilitating access to the data for other research applications. Overall, this work aims to streamline the generation of new calibration curves.

Every year, there are over 200 traumatic deaths at work in Australia. A government safety inspector usually investigates each incident. The investigation may lead to prosecution of the employer or another party deemed to have breached relevant legislation. However, little systematic research has examined the needs and interests of grieving families in this process. Drawing on interviews with 48 representatives of institutions that deal with deaths at work (including regulators, unions, employers, police and coronial officers), this article examines how they view the problems and experiences of families. Notwithstanding some recent improvements, findings indicate ongoing shortcomings in meeting the needs of families regarding information provision, involvement and securing justice.

Approximately one-third of individuals in a major depressive episode will not achieve sustained remission despite multiple, well-delivered treatments. These patients experience prolonged suffering and disproportionately utilize mental and general health care resources. The recently proposed clinical heuristic of ‘difficult-to-treat depression’ (DTD) aims to broaden our understanding and focus attention on the identification, clinical management, treatment selection, and outcomes of such individuals. Clinical trial methodologies developed to detect short-term therapeutic effects in treatment-responsive populations may not be appropriate in DTD. This report reviews three essential challenges for clinical intervention research in DTD: (1) how to define and subtype this heterogeneous group of patients; (2) how, when, and by what methods to select, acquire, compile, and interpret clinically meaningful outcome metrics; and (3) how to choose among alternative clinical trial design options to promote causal inference and generalizability. The boundaries of DTD are uncertain, and an evidence-based taxonomy and reliable assessment tools are preconditions for clinical research and subtyping. Traditional outcome metrics in treatment-responsive depression may not apply to DTD, as they largely reflect the only short-term symptomatic change and do not incorporate durability of benefit, side effect burden, or sustained impact on quality of life or daily function. The trial methodology will also require modification as trials will likely be of longer duration to examine the sustained impact, raising complex issues regarding control group selection, blinding and its integrity, and concomitant treatments.

Health disparities between Appalachia and the rest of the country are widening. To address this, the Appalachian Translational Research Network (ATRN) organizes an annual ATRN Health Summit. The most recent Summit was held online September 22–23, 2020, and hosted by Wake Forest Clinical and Translational Science Institute in partnership with the Northwest Area Health Education Center. The Summit, titled “Community-Engaged Research in Translational Science: Innovations to Improve Health in Appalachia,” brought together a diverse group of 141 stakeholders from communities, academic institutions, and the National Center for Advancing Translational Science (NCATS) to highlight current research, identify innovative approaches to translational science and community-engaged research, develop cross-regional research partnerships, and establish and disseminate priorities for future Appalachian-focused research. The Summit included three plenary presentations and 39 presentations within 12 concurrent breakout sessions. Here, we describe the Summit planning process and implementation, highlight some of the research presented, and outline nine emergent themes to guide future Appalachian-focused research.

In the Cordillera Darwin, southernmost South America, we used 10Be and 14C dating, dendrochronology, and historical observations to reconstruct the glacial history of the Dalla Vedova valley from deglacial time to the present. After deglacial recession into northeastern Darwin and Dalla Vedova, by ~16 ka, evidence indicates a glacial advance at ~13 ka coeval with the Antarctic Cold Reversal. The next robustly dated glacial expansion occurred at 870 ± 60 calendar yr ago (approximately AD 1150), followed by less-extensive dendrochronologically constrained advances from shortly before AD 1836 to the mid-twentieth century. Our record is consistent with most studies within the Cordillera Darwin that show that the Holocene glacial maximum occurred during the last millennium. This pattern contrasts with the extensive early- and mid-Holocene glacier expansions farther north in Patagonia; furthermore, an advance at 870 ± 60 yr ago may suggest out-of-phase glacial advances occurred within the Cordillera Darwin relative to Patagonia. We speculate that a southward shift of westerlies and associated climate regimes toward the southernmost tip of the continent, about 900–800 yr ago, provides a mechanism by which some glaciers advanced in the Cordillera Darwin during what is generally considered a warm and dry period to the north in Patagonia.