Washington State University Vancouver

Abstract Physicochemical soil parameters are key drivers of biogeochemical processes, controlling microbial activity and the mobility, solubility, and bioavailability of organic and inorganic matter. These parameters vary with depth, yet tools for their quantification are limited. Microelectrodes, among the most common tools, are primarily designed for biofilms only a few micrometers to millimeters thick and thus unsuitable for centimeter-scale soil gradients. To address this gap, we developed a custom-built automated manipulator system for soil depth profiling. Using off-the-shelf components, we constructed an instrument called Soil Electrochemical Profiling System (SEPS) capable of operating to depths of up to 27 cm with a minimum step interval of 25 µm. SEPS integrates directly with a potentiostat, enabling electrochemical techniques such as redox potential measurements, cyclic voltammetry, and chronoamperometry experiments. We validated the system by generating depth-resolved redox profiles and cyclic voltammograms in soil and sediment reactors. Additionally, we demonstrated its utility for microbial enrichment by polarizing a microelectrode at a fixed depth over 40 days. This system uniquely combines fine-scale automated positioning with electrochemical instrumentation functionality, providing a versatile and affordable platform for soil depth profiling and advancing the study of biogeochemical and microbial processes in terrestrial environments.

This study investigates how adolescents from two culturally distinct Central African communities—the Aka hunter-gatherers and Ngandu farmers—perceive health, attractiveness, and marriageability, focusing on how local socio-ecological contexts shape perceptions of health, attraction, and mate preferences. The research examines how body mass index and parasite load relate to perceived health and attractiveness. Seventy-five adolescents (39 Aka and 36 Ngandu) evaluated photographs of peers for health, attractiveness, and marriagability, while physical health was objectively measured using anthropometric and parasitological data. Regression analyses revealed that BMI was a consistent and significant predictor of both perceived health and attractiveness, whereas total parasite load did not significantly influence either outcome. Notably, perceptions of health strongly predicted attractiveness and marriageability, but not vice versa. Ethnic and gender differences in perception were also found: Aka adolescents prioritized social traits like kindness and cooperation, while Ngandu participants emphasized physical cleanliness and robustness. Male raters showed more variability and stricter standards, particularly when evaluating females. These findings underscore the role of robust phenotypic features, such as BMI, in determining how health, beauty, and reproductive value are interpreted. This research contributes to understanding how evolutionarily evolved preferences and cultural contexts shape perceptions of health, attraction, and marriageability.

Sixth-generation (6G) wireless communication systems impose stringent requirements on antenna performance, including ultra-high data rates, ultra-lowlatency, massive connectivity, high-frequency operation, advanced beamforming, and long-term reliability. Achieving these goals at mm-wave and sub-terahertz frequencies introduces major challenges such as severe path loss, hardware complexity, thermal stress, limited flexibility, and performance degradation under mechanical and environmental variations. This review presents a comprehensive overview of 6G antenna requirements, key antenna technologies, material platforms, fabrication techniques, AI/ML integration, and reliability assessment. Advanced antenna solutions, including hybrid antenna arrays, antenna collocation, metasurfaces and reconfigurable intelligent surfaces, and mm-wave and terahertz antennas are discussed alongside their limitations in flexibility and robustness. Flexible antennas are highlighted as a promising solution, enabled by emerging materials and additive fabrication methods such as inkjet printing, aerosol jet printing, screen printing, and additive manufacturing. In addition, standardized testing and reliability evaluation under harsh environments, such as bending, thermal cycling, humidity, and aging are reviewed. Finally, the integration of artificial intelligence and machine learning for antenna design optimization, fabrication control, and performance enhancement is discussed, outlining future directions for reliable and scalable 6G antenna systems.

Knowledge about death, dying, loss, grief, and end-of-life care is an essential skill for physicians. However, end-of-life education is often incorporated into medical school curricula in the United States as electives. This scoping review explores the current empirical literature on how death and dying is taught in U.S. medical schools to identify evidence-based teaching practices and areas of opportunities to enhance death and dying education for future physicians. The authors conducted a systematic scoping review in PubMed and EMBASE, using PRISMA-ScR guidelines, of articles focused on death and dying education conducted in a U.S. MD-granting medical school setting between January 2010 and April 2025. Successive reviews of the titles, abstracts, and full texts were performed, as well as forward and backward citation searches. The initial search yielded 4,959 records; ultimately, the analytic sample for this review was 43 articles. Overall, the 43 included articles described significant variation in how death and dying is taught in medical schools. Twenty-one studies used quantitative methodologies, 13 used qualitative methodologies, and 9 used mixed or multiple methods. In line with competency-based medical education standards, the authors organize the findings around the knowledge, skills, and abilities model. Over half of the articles (n = 25) emphasized knowledge acquisition, 22 integrated skills-based components, and 28 addressed the assessment of abilities. Simulation training was common within skills-based interventions. There remains a sizeable gap in evidence-based medical education related to knowledge, skills, and abilities pertaining to end-of-life care. The authors offer next steps for developing, implementing, and measuring evidence-based interventions to improve end-of-life care competency. The authors advocate for continued implementation of evidence-based educational interventions, regardless of anticipated specialty area, throughout all preclinical and clinical years.

Abstract Medical students typically encounter death during their training, an experience that profoundly shapes their professional aspirations, coping strategies, and personal reflections on mortality. This study explored the emotional impact of these encounters, along with students’ attitudes about death and their experiences with end-of-life (EOL) training. Undergraduate medical students completed an online survey (n = 45) and then a sub-sample (n = 10) participated in in-depth interviews focusing on how EOL encounters or training influenced their professional and personal growth. Using a reflective research methodology, four additional medical student researchers contributed to the narrative analysis of transcribed interviews via an inductive, open coding approach. Over 70% of survey respondents (n = 32) reported both personal and professional experiences with death and 90% wanted more education (i.e., elective course offering). Follow-up interviews highlighted gaps in essential skills like goals-of-care conversations and trauma stewardship. Key themes from the narrative analysis included: (1) developing personal strategies for coping with death, (2) exploring how to comfort others, and (3) conceptualizing what it means to “die well.” Students also emphasized the importance of peer and institutional support to build resilience, manage emotions, navigate EOL care, and prevent burnout. However, students also perceived hesitancy among mentors to discuss EOL options or palliative care, attributing their discomfort to knowledge gaps. These findings highlight the need for comprehensive EOL training in medical curricula to help improve future patient care and to foster resilience, compassion, and well-being in future physicians.

Lung cancer remains the leading cause of cancer death in the United States. Annual lung cancer screening (LCS) with low-dose chest CT (LDCT) can prevent lung cancer deaths in high-risk individuals; However, these benefits are tempered by low adherence to annual screening and low rates of follow-up for those with abnormal findings. To evaluate the impact of centralized approaches to care coordination on LCS follow-up in community settings through a hybrid implementation-effectiveness trial. This is a pre-post intervention trial of a pragmatic and flexible approach to LCS care coordination delivered at the system-level at two community LCS programs based at regional hospitals in Washington state. Care coordination approaches include standardized LCS follow-up workflows incorporating universal tracking of LCS results, universal results delivery to patients, stepped approaches to follow-up reminders and personalized approaches to positive findings. Participants who are eligible for and undergo LCS during either period (n∼6750) will be included. Primary outcomes include adjusted changes in screening adherence to annual follow-up and follow-up for positive findings between the pre- (August 2022-March 2025) and post- (March 2025-September 2027) intervention period. Secondary outcomes include assessing the impact of interventions by community site, patient ethnicity, socioeconomic status, and rurality. We will also assess the implementation of the intervention with attention to adaptation, sustainability and equity. Implementing centralizing care coordination models may decrease barriers and improve adherence to LCS in community settings and serve as a model to improve LCS follow-up in clinical care settings. ClinicalTrials.gov ID NCT06324110.

Adaptations that enable plant-associated bacteria to fill disparate niches comprise a critical component of microbial diversity. Genes that confer locally adaptive bacterial traits, ranging from heavy metal resistance to pathogen or symbiont infectivity, often reside within mobile genetic elements (MGEs) that can move between genomes. While MGEs may speed microbial adaptation, they also have selfish fitness interests and potentially separate evolutionary trajectories from their host genome. MGEs can also impose physiological burdens and be limited in the transmissibility of function across hosts, which likely constrains bacterial local adaptation. Given these constraints, the prevalence of adaptive loci on potentially exploitative MGEs poses a dilemma: how do fitness conflicts and alignments between MGEs and the main replicon shape bacterial local adaptation and impact plant hosts? We synthesize research on ways MGEs confer rapid, niche-specific fitness advantages to bacteria, identify factors that promote or constrain bacterial adaptation, and highlight MGE impacts on plants. We focus on large, self-transmissible MGEs (islands, plasmids, and prophages; though we expect relevance to other MGEs as well) to better understand how MGEs bolster yet constrain bacterial local adaptation. We specifically explore the role of MGEs in shaping bacteria that themselves play a role in expanding or contracting the plant niche.

Deep learning applications use tensors, the fundamental data structures, for storing input/output data and managing intermediate weights and parameters during training/inference. The memory layout of tensors can be changed from contiguous to non-contiguous by tensor operators at runtime. In this paper, we comprehensively study the impact of tensor memory layout on the performance of deep-learning applications. The study shows that performing conversions at runtime yields speed improvements of 8.17% − 249.6%. Based on this observation, we propose a new approach, SmartConvert, which is designed to dynamically convert the memory layout of intermediate tensors from non-contiguous to contiguous and hide the conversion time by overlapping its cost with I/O or communication operations during training and inference. We conduct a preliminary performance study using GAT models. The results show that SmartConvert can reduce the computation time by 23% on average.

Anxiety and other psychological symptoms may not be addressed in Mohs micrographic surgery (MMS) informed consent procedures nor assessed during the perioperative period. First, to examine psychological adverse events (AEs) associated with MMS, and second, to examine psychological risks identified in MMS informed consent forms. This review was registered (PROSPERO CRD42024594453). First, MEDLINE and PsycINFO were searched from inception through November 5, 2024 for studies of adults undergoing MMS with quantitative measures of psychological status in the perioperative period. Thirteen measures, most often of anxiety, were standardized for pooled analysis. Second, Google was searched for US MMS consent forms on October 23, 2024. Data were extracted with 20% conducted in duplicate; authors were contacted for missing data. Risk of bias was assessed. The literature search resulted in 29 studies totaling 6,455 patients. Using one standardized score per study, patients reported a pooled distress rating of 25.26 out of 100, with significant heterogeneity (95% confidence interval, 11.44‒61.11, I2 = 100%). The consent form search resulted in 20 consent forms: none listed psychological risks. Psychological AEs of MMS are common and should be addressed as risks in informed consent processes.