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Abstract Background The global burden of mental illness is substantial, with depression impacting close to 300 million people worldwide. This has been exacerbated within the context of the COVID-19 pandemic. Yet, in many low- and middle-income countries including Vietnam, there is a substantial treatment gap, with many requiring mental health care unable to access it. Task-shifting is an evidence-based approach that seeks to address this gap by utilizing non-specialist providers to provide care. While there is a large body of literature exploring task-shifting, there is little that explores the client experience. This paper describes the facilitators and barriers impacting the client experience of a task-shifting supported self-management (SSM) intervention for depression in Vietnam. SSM involves a client workbook and supportive coaching by non-specialist providers. Methods This paper is situated within a randomized controlled trial that demonstrated the effectiveness of the SSM intervention in adult populations across eight provinces in Vietnam. Semi-structured interviews were conducted with a convenience sample of clients (recipients of the intervention) with depression caseness as measured by the Self-Report Questionnaire-20 depression screening measure, and providers (non-specialist “social collaborators”) to explore SSM’s acceptability and factors influencing participation and adherence. This paper presents the qualitative findings from an analysis of the interviews, focusing on the client perspective. Qualitative descriptive methods and thematic analysis were used. Results Forty-five clients were interviewed. Sub-themes reported for the facilitators and benefits for the client experience of the SSM intervention were client-provider relationship building and family and community connections. Sub-themes reported for the barriers were clients’ responsibilities, clients’ health conditions, and consequences of stigma. Conclusions Due to challenges with sustaining and scaling up the in-person SSM intervention in Vietnam, the research team has pivoted to delivering the SSM intervention digitally through a smartphone-based app adapted from SSM, with direction from the Government of Vietnam. Findings from this study suggest that while digital interventions may support accessibility and convenience, they may neglect the critical human contact component of mental health care. Ultimately, a model that combines digital delivery with some form of human contact by a support person may be important.

Abstract This study presents a data-driven battery emulator using long short-term memory deep learning models to predict the charge–discharge behaviour of lithium-ion batteries (LIBs). This study aimed to reduce the economic costs and time associated with the fabrication of large-scale automotive prototype batteries by emulating their performance using smaller laboratory-produced batteries. Two types of datasets were targeted: simulation data from the Dualfoil model and experimental data from liquid-based LIBs. These datasets were used to accurately predict the voltage profiles from the arbitrary inputs of various galvanostatic charge–discharge schedules. The results demonstrated high prediction accuracy, with the coefficient of determination scores reaching 0.98 and 0.97 for test datasets obtained from the simulation and experiments, respectively. The study also confirmed the significance of state-of-charge descriptors and inferred that a robust model performance could be achieved with as few as five charge–discharge training datasets. This study concludes that data-driven emulation using machine learning can significantly accelerate the battery development process, providing a powerful tool for reducing the time and economic costs associated with the production of large-scale prototype batteries.

Abstract All-solid-state Li-metal batteries can conceivably improve the safety and extend the driving ranges of electric vehicles. In this regard, the garnet-type solid electrolyte Li7La3Zr2O12 (LLZ) has garnered considerable attention because of its high Li-ion conductivity and nonreactivity towards molten Li metal. Here, we perform molecular dynamics (MD) simulations using a universal neural network potential (UNNP) to analyse the Li-ion exchange at the LLZ/Li interface at the atomic scale. The UNNP-MD calculations show that Li ions traverse the LLZ/Li interface and that excess Li ions relative to the stoichiometric composition accumulate in an approximately 1 nm-thick zone near the LLZ phase interface, signifying the formation of a space-charge layer. Electronic structural analysis of the UNNP-MD-derived configuration, performed using density functional theory calculations, reveals band bending near the LLZ phase interface and the simultaneous suppression of Li metal reduction. These findings can help expedite the development of rationally designed all-solid-state Li-metal batteries.

BackgroundCollege students significantly decrease physical activity (PA) over the course of a four-year degree, increasing the risk for chronic disease. Research shows that psychological constructs impact behavior and goal attainment. However, little is known regarding the effect of psychological variables on PA levels in students. This study examined the association of psychological factors, PA, and exercise goals in college students.MethodsStudents completed two questionnaires within one semester approximately 8 weeks apart. The first (Time 1) included the Adult Hope Scale, Life Orientation Test-Revised, Self-Efficacy to Regulate Exercise, International Physical Activity Questionnaire (IPAQ), and goal assessments. The second (Time 2) included the IPAQ, and scales for goal progress and success. One-hundred seven participants completed both surveys and included an exercise goal.ResultsPredictors of exercise goal attainment included moderate PA at Time 1, goal importance, hope-agency, and the hope-agency by major interaction. Predictors of vigorous PA at Time 2 included hope-agency and moderate PA. The only predictor of moderate PA at Time 2 was moderate PA at Time 1. The only predictor of total PA at Time 2 was moderate PA at Time 1.ConclusionHigher hope-agency scores predicted self-reported vigorous PA. We also provide evidence that trait hope influences perceived exercise goal achievement over time.

All-solid-state batteries composed of inorganic materials are in high demand as power sources for electric vehicles owing to their improved safety, energy density, and overall lifespan. However, the low ionic conductivity of inorganic solid electrolytes has limited the performance and adoption of inorganic all-solid-state batteries. The solid electrolyte LiZr2(PO4)3 has attracted attention owing to its high Li-ion conductivity. The ionic conductivity of LiZr2(PO4)3 changes with the crystalline phase obtained, which varies based on composition control through elemental substitution and process conditions such as sintering temperature. Traditionally, optimizing such parameters and understanding their relationship to physical properties have relied on researcher experience and intuition. However, a recent use of a materials informatics approach utilizing machine learning shows promise for more efficient property optimization. This study proposes a deep learning model to correlate powder X-ray diffraction (XRD) profiles with the activation energy (Ea) for Li-ion conduction, thereby enhancing the interpretability of the measurement data. XRD profiles, which contain information on crystal structure, lattice strain, and particle size, were used as-is (i.e., without preprocessing) in the deep learning model. An attention mechanism was introduced to the deep learning model that focuses on XRD crystal-structure information and visualization of important factors embedded in the XRD profiles. The highlighted areas in the output of this model successfully predict LiZr2(PO4)3 phases with low Ea (high Li conductivity) and high Ea (low Li conductivity). Moving forward, this deep learning model can offer new insights to materials researchers, potentially contributing to the discovery of new solid electrolyte materials.

Abstract Inexpensive and safe energy-storage batteries with high energy densities are in high demand (e.g., for electric vehicles and grid-level renewable energy storage). This study focused on using NaFeCl4, comprising ubiquitous elements, as an electrode material for all-solid-state sodium-ion batteries. Monoclinic NaFeCl4, expected to be the most resource-attractive Fe redox material, is also thermodynamically stable. The Fe2+/3+ redox reaction of the monoclinic NaFeCl4 electrode has a higher potential (3.45 V vs. Na/Na+) than conventional oxide electrodes (e.g., Fe2O3 with 1.5 V vs. Na/Na+) because of the noble properties of chlorine. Additionally, NaFeCl4 exhibits unusually high deformability (99% of the relative density of the pellet) upon uniaxial pressing (382 MPa) at 298 K. NaFeCl4 operates at 333 K in an electrode system containing no electrolyte, thereby realizing next-generation all-solid-state batteries with high safety. A high energy density per positive electrode of 281 Wh kg−1 was achieved using only a simple powder press.

For the halide solid electrolyte Li3InCl6, which has both high water resistance and high ionic conductivity, doping with different elements to further increase the conductivity is attracting attention. In this study, we investigated co-doping Li3InCl6 with Nb5+ and Zr4+. A pretrained neural-network potential was used for molecular dynamics simulations, and the results indicated that doping with a high concentration of Zr4+ and low concentration of Nb5+ promotes disorder in the Li+/vacancy arrangement on the diffusion path, even at relatively low temperatures. Bayesian optimization revealed the optimal composition with fewer samples, highlighting its utility for exploring complex compositions and expensive experimental investigations.

Abstract Efforts to optimize known materials and enhance their performance are ongoing, driven by the advancements resulting from the discovery of novel functional materials. Traditionally, the search for and optimization of functional materials has relied on the experience and intuition of specialized researchers. However, materials informatics (MI), which integrates materials data and machine learning, has frequently been used to realize systematic and efficient materials exploration without depending on manual tasks. Nonetheless, the discovery of new materials using MI remains challenging. In this study, we propose a method for the discovery of materials outside the scope of existing databases by combining MI with the experience and intuition of researchers. Specifically, we designed a two-dimensional map that plots known materials data based on their composition and structure, facilitating researchers’ intuitive search for new materials. The materials map was implemented using an autoencoder-based neural network. We focused on the conductivity of 708 lithium oxide materials and considered the correlation with migration energy (ME), an index of lithium-ion conductivity. The distribution of existing data reflected in the materials map can contribute to the development of new lithium-ion conductive materials by enhancing the experience and intuition of material researchers.

Owing to their high-speed, force-field (FF) calculations for inorganic solid-state materials using the parametric potential have been widely employed as an effective tool for high-throughput calculations such as exhaustive property evaluation of material databases and/or calculations for models containing tens of thousands of atoms or more, including amorphous and grain boundary models. However, the accuracy of such calculations strongly depends on the choice of the FF parameters. Today, compounds containing three or more elements are targeted in the research and development of functional materials, in which case the number of parameters often exceeds 10 dimensions. This significantly increases the search space, making it difficult to determine the parameters rationally. To resolve this issue, we previously reported an FF parameter determination approach based on meta-heuristics (APL Materials, 8, 081111 (2020)). In this study, we further investigated a methodology to efficiently determine the FF parameters using a conditional variational autoencoder (CVAE), a type of deep learning method, which can reduce the dimension of the input parameters and distribute them in a probabilistic manner in the latent space. As a demonstration, we applied the method to the optimization of 11 FF parameters for an argyrodite-type Li7PS6 material, which has attracted considerable attention as a solid electrolyte for all-solid-state batteries. The results confirmed that the proposed approach can generate valid FFs that are highly consistent with the results of first-principles calculations, even when using a limited set of meta-heuristics-generated FF parameters.

The Li-ion conductivities of Li3InCl6 (LIC), which is a promising chloride solid electrolyte, and its compositional derivatives, Nb5+- and Zr4+-doped LIC, i.e., Li3−2xIn1−xNbxCl6 and Li3−yIn1−yZryCl6, respectively, were experimentally and computationally investigated. An increase in the ionic conductivity caused by Nb5+ or Zr4+ doping, which was due to the increase in Li vacancies, was observed in both the experimental and computational results. Nb5+ doping yielded a larger increase in conductivity at 60 °C. First-principles molecular dynamics studies indicated two factors affecting the Li-ion conductivity under doping with higher-valent ions: (1) the vacancy trapping effect and (2) the reduction in the phase-transition temperature from a Li/vacancy ordered structure to a disordered structure. In particular, in factor (2), the effect of Nb5+ doping is larger than that of Zr4+ doping, which supports the improvement in ionic conductivity at 333 K in the experiment.

Abstract Li-metal rechargeable batteries are an attractive option for devices that require an extremely high specific energy density, high robustness, and long-term durability, such as high-altitude platform stations. However, Li dendrite growth during charge–discharge cycling causes short-circuit problems. One technical solution is to form an intermediate layer between the Li metal and electrolyte. This interfacial layer should possess mechanical strength, electrochemical stability in the presence of Li, and Li-ion conductivity. In this study, the Li-ion conductivity of spinel-type LiAl5O8 was investigated using first-principles density functional theory and force field molecular dynamics calculations. The calculation results confirmed that stoichiometric LiAl5O8 compounds do not exhibit Li-ion conductivity, whereas off-stoichiometric compounds with excess Li show long-range Li-ion diffusion. The evaluated activation energy was 0.28 eV, which is as low as that of well-known fast Li-ion conductors, such as garnet-type Li7La3Zr2O12. However, the extrapolated Li-ion conductivity at 298 K was relatively low (~ 10−6 S/cm) owing to the limited formation of migration pathways.

IntroductionAntifungal agents are not always efficient in resolving vulvovaginal candidiasis (VVC), a common genital infection caused by the overgrowth of Candida spp., including Candida albicans, or in preventing recurrent infections. Although lactobacilli (which are dominant microorganisms constituting healthy human vaginal microbiota) are important barriers against VVC, the Lactobacillus metabolite concentration needed to suppress VVC is unknown.MethodsWe quantitatively evaluated Lactobacillus metabolite concentrations to determine their effect on Candida spp., including 27 vaginal strains of Lactobacillus crispatus, L. jensenii, L. gasseri, Lacticaseibacillus rhamnosus, and Limosilactobacillus vaginalis, with inhibitory abilities against biofilms of C. albicans clinical isolates.ResultsLactobacillus culture supernatants suppressed viable fungi by approximately 24%-92% relative to preformed C. albicans biofilms; however, their suppression differed among strains and not species. A moderate negative correlation was found between Lactobacillus lactate production and biofilm formation, but no correlation was observed between hydrogen peroxide production and biofilm formation. Both lactate and hydrogen peroxide were required to suppress C. albicans planktonic cell growth. Lactobacillus strains that significantly inhibited biofilm formation in culture supernatant also inhibited C. albicans adhesion to epithelial cells in an actual live bacterial adhesion competition test.Discussion Healthy human microflora and their metabolites may play important roles in the development of new antifungal agent against C. albicans-induced VVC.

Materials with a high Li-ion conductivity and deformability are garnering interest for the facile fabrication of safe all-solid-state batteries with high energy densities. Hence, increasing attention has been focused on Li-containing chloride materials that meet these requirements since they were first reported in 2018 (Asano et al. Advanced Materials 2018, 30 (44), 1803075). In this paper, we report a novel Li-containing chloride of Li3LuCl6 with a high Li-ion conductivity (σ25 °C = 3.1 × 10−4 S cm−1) and sufficient deformability. Furthermore, its defect derivative of Li3−xLuCl6−x (x = 1), i.e., Li2LuCl5 with a higher Li-ion conductivity (σ25 °C = 5.2 × 10−4 S cm−1), is synthesized. Scanning electron microscopy confirms the dense packing of both Li3LuCl6 and Li2LuCl5 as compressed pellets. Hence, Li2LuCl5 is presented as a promising solid electrolyte with a high Li-ion conductivity and deformability, which presents a novel opportunity for exploring the composition of Li2MCl5 (M: trivalent metal ion) compounds and indicates potential applications as an all-solid-state battery material. Furthermore, as there are no reported cases of high-Li-ion-conductivity chloride materials with the Li2MCl5 composition until this work, this study is expected to increase the progress in future studies of LiCl-deficient Li2MCl5 compositions with a Li3MCl6 composition.

Shuta Morishige,1 Yoshikazu Yamaguchi,1 Kei Nakajima,1 Sayaka Tsuboi,1 Yoh Sugawara,2 Hajime Hayami,1 Joseph D Tobias,3 Gaku Inagawa1 1Department of Anesthesiology, Yokohama Municipal Citizen’s Hospital, Yokohama, Japan; 2Department of Anesthesiology, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA; 3Department of Anesthesiology and Pain Medicine, Nationwide Children’s Hospital and The Ohio State University, Columbus, OH, USACorrespondence: Yoshikazu Yamaguchi, Department of Anesthesiology, Yokohama Municipal Citizen’s Hospital, 1-1 Mitsuzawanishimachi, Kanagawa-ku, Yokohama-shi, Kanagawa, 221-0855, Japan, Tel +81-45-316-4580, Fax +81-45-316-6580, Email yoshikaz@yokohama-cu.ac.jpAbstract: Cardiac surgery-associated acute kidney injury may require postoperative renal replacement therapy. Although the right internal jugular vein and femoral veins are generally the preferred insertion sites for the hemodialysis catheter for continuous renal replacement therapy, the presence of other indwelling catheters or prior thrombotic events from previous catheters may preclude use of these sites. We present a case in which the hemodialysis catheter was inserted into the distal femoral vein using point-of-care ultrasound in a patient with multiple catheter insertions after coronary artery bypass grafting. Although the tip of the dialysis catheter was more distal than the classic femoral approach, renal replacement therapy was performed without problems. Moreover, it was easier for the nurses to keep the insertion site clean and to change the patient’s position.Keywords: central venous catheter, renal replacement therapy, femoral vein

Megumi Yoshida,1 Yoshikazu Yamaguchi,1 Mizuho Matsushita,1 Sayaka Tsuboi,1 Yoh Sugawara,1 Hajime Hayami,1 Joseph Tobias,2 Gaku Inagawa1 1Department of Anesthesiology, Yokohama Municipal Citizen‘s Hospital, Yokohama, Japan; 2Department of Anesthesiology & Pain Medicine, Nationwide Children’s Hospital and The Ohio State University, Columbus, OH, USACorrespondence: Megumi YoshidaYokohama Municipal Citizen’s Hospital, 1-1 Mitsuzawanishimachi, Kanagawa-ku, Yokohama, 221-0855, JapanTel +81 45 316-4580Fax +81 45 316-6580Email megu.m.y06@gmail.comAbstract: Tetanus is a potentially fatal infectious disease caused by the toxins produced by the anaerobic bacterium, Clostridium tetani. Of major concern during the perioperative care of these patients is control of muscle spasms, skeletal rigidity, and autonomic dysfunction. Several of the modern sedative and opioid agents including remifentanil have not been fully evaluated in managing tetanus. We present the intraoperative use of remifentanil in a 75-year-old woman with generalized tetanus who required anesthetic care during placement of a tracheostomy. The end-organ involvement of tetanus is presented, previous reports of anesthetic care reviewed, and the potential utility of remifentanil explored.Keywords: tetanus, tracheostomy, general anesthesia

Abstract Background While depression is a leading contributor to burden of disease in Vietnam, there is a critical gap in depression care due to the shortage of mental health specialists and extremely limited mental health services in general health care settings. We have previously reported the effectiveness of a supported self-management (SSM) task-sharing intervention for depression, delivered by social collaborators (lay social workers). The purpose of this study was to identify factors influencing the effectiveness of delivery of SSM by social collaborators and delineate areas for further attention that are relevant for scale-up. Methods A hundred and ten (110) key informant interviews were conducted with three stakeholder groups (patients, social collaborators, experts) from eight provinces in Vietnam. Participants were identified through records from a recently completed randomized trial that showed the effectiveness of SSM in community-based settings in Vietnam. Qualitative descriptive methods and thematic analysis were used to examine the interviews. A coding framework and corresponding themes were developed deductively, based on the findings from the randomized trial and the literature, and through inductive analysis, to describe the contextual factors that impacted the social collaborators’ role in successfully implementing the SSM intervention. Results Our analysis identified the following benefits of working with social collaborators: (1) increased awareness of mental health in the family and community; (2) reduced stigma; (3) a better understanding that depression is treatable; (4) increased help-seeking; and (5) improved access to care. There were also significant challenges, including social collaborator characteristics (age, education, pre-existing training and skills) and contextual factors influencing their work (roles and responsibilities, training, compensation, support from government). Conclusions Engaging social collaborators in the delivery of SSM in the community can help fill a critical gap in depression care in Vietnam. However, several contextual challenges that are an impediment to increased engagement and sustainable integration into health and social systems need to be resolved through policy change to regulate their practice, define their scope of work, and provide adequate remuneration.

Abstract The geometries (i.e., dip angles) of active faults from the surface to the seismogenic zone are the most important factors used to evaluate earthquake ground motion, which is crucial for seismic hazard assessments in urban areas. In Osaka, a metropolitan city in Japan, there are several active faults (e.g., the Uemachi and Ikoma faults), which are inferred from the topography, the attitude of active faults in surface trenches, the seismic reflection profile at shallow depths (less than 2 km), and the three-dimensional distribution of the Quaternary sedimentary layers. The Uemachi and Ikoma faults are N–S-striking fault systems with total lengths of 42 km and 38 km, respectively, with the former being located ~ 12 km west of the latter; however, the geometries of each of the active faults within the seismogenic zone are not clear. In this study, to examine the geometries of the Uemachi and Ikoma faults from the surface to the seismogenic zone, we analyze the development of the geological structures of sedimentary layers based on numerical simulations of a two-dimensional visco-elasto-plastic body under a horizontal compressive stress field, including preexisting high-strained weak zones (i.e., faults) and surface sedimentation processes, and evaluate the relationship between the observed geological structures of the Quaternary sediments (i.e., the Osaka Group) in the Osaka Plain and the model results. As a result, we propose geometries of the Uemachi and Ikoma faults from the surface to the seismogenic zone. When the friction coefficient of the faults is ~ 0.5, the dip angles of the Uemachi and Ikoma faults near the surface are ~ 30°–40° and the Uemachi fault has a downward convex curve at the bottom of the seismogenic zone, but does not converge to the Ikoma fault. Based on the analysis in this study, the dip angle of the Uemachi fault zone is estimated to be approximately 30°–40°, which is lower than that estimated in the previous studies. If the active fault has a low angle, the width of the fault plane is long, and thus the estimated seismic moment will be large.

Abstract Background Patient awareness surveys on polypharmacy have been reported previously, but no previous study has examined the effects of sending feedback to health professionals on reducing medication use. Our study aimed to conduct a patient survey to examine factors contributing to polypharmacy, feedback the results to health professionals, and analyze the resulting changes in the number of polypharmacy patients and prescribed medications. Methods After conducting a questionnaire survey of patients in Study 1, we provided its results to the healthcare professionals, and then surveyed the number of polypharmacy patients and oral medications using a before-after comparative study design in Study 2. In Study 1, we examined polypharmacy and its contributing factors by performing logistic regression analysis. In Study 2, we performed a t-test and a chi-square test. Results In the questionnaire survey, significant differences were found in the following 3 items: age (odds ratio (OR) = 3.14; 95% confidence interval (CI) = 2.01–4.91), number of medical institutions (OR = 2.34; 95%CI = 1.50–3.64), and patients’ difficulty with asking their doctors to deprescribe their medications (OR = 2.21; 95%CI = 1.25–3.90). After the feedback, the number of polypharmacy patients decreased from 175 to 159 individuals and the mean number of prescribed medications per patient decreased from 8.2 to 7.7 (p

The slow kinetics of the oxygen exchange reaction at the surface of air electrodes for solid oxide fuel cells must be improved to reduce their operating temperature. In this study, we use first-principles computation, based on the density functional theory, to investigate the surface morphology and oxygen vacancy formation energies of perovskite-type LaCoO3 and La0.5Sr0.5Co0.5Fe0.5O3 (LSCF5555) compounds. The cationic arrangement is optimized energetically for LSCF5555 using a genetic algorithm approach. We confirm that Sr and Co condensation occurs near the LSCF5555 surface. Significant lowering of the oxygen vacancy formation energies at the perovskite surface is indicated for both the compounds. In addition, several surface O sites in LSCF5555 exhibit lower oxygen vacancy formation energies than those in LaCoO3, which may improve the kinetics of the surface charge-transfer reaction in the LSCF-related compounds.

Out-of-plane ferroelectricity is usually unstable in the two dimensional limit due to the presence of the depolarization field. Here, the authors successfully circumvent this issue by growing µm-sized SnS monolayers that exhibit in-plane ferroelectricity that is stable at room temperature.

Abstract Background This study tested the effectiveness of a supported self-management (SSM) intervention to reduce symptoms of depression among adults compared with enhanced treatment as usual in community-based and primary care settings in Vietnam. Methods The cluster randomized trial included 376 adults in 32 communes in eight provinces. Eligible participants scored > 7 on the SRQ-20 depression scale. Patients with severe symptoms were excluded and referred to tertiary care. Randomization took place at the commune level. The immediate intervention group included 16 communes with 190 participants and the delayed group included 16 communes with 186 participants. Participants in communes randomized to the immediate intervention group received a two-month course of SSM, consisting of a workbook and supportive coaching. Those in communes randomized to the delayed group received enhanced treatment as usual and, for ethical purposes, received the SSM intervention after 4 months. The primary outcome is the effect of SSM on reduction in depression scores as indicated by a reduced proportion of participants with SRQ-20 scores > 7 at 2 months after commencement of SSM intervention. Blinding was not possible during intervention delivery but outcome assessors were blinded. Analysis was intention-to-treat. Results At 2 months, 26.4% of the intervention group and 42.3% of the delayed group had SRQ-20 scores > 7. The adjusted odds ratio of having depression between the intervention and control was 0.42 (p

BackgroundPsychological factors (eg, depression) and related biological and behavioral responses are associated with numerous physical health outcomes. Most research in this area relies on self-reported assessments of psychological factors, which are difficult to scale because they may be expensive and time-consuming. Investigators are increasingly interested in using social media as a novel and convenient platform for obtaining information rapidly in large populations. ObjectiveWe evaluated the feasibility of obtaining Facebook data from a large ongoing cohort study of midlife and older women, which may be used to assess psychological functioning efficiently with low cost. MethodsThis study was conducted with participants in the Nurses’ Health Study II (NHSII), which was initiated in 1989 with biennial follow-ups. Facebook does not share data readily; therefore, we developed procedures to enable women to download and transfer their Facebook data to cohort servers (for linkage with other study data they have provided). Since privacy is a critical concern when collecting individual-level data, we partnered with a third-party software developer, Digi.me, to enable participants to obtain their own Facebook data and to send it securely to our research team. In 2020, we invited a subset of the 18,519 NHSII participants (aged 56-73 years) via email to participate. Women were selected if they reported on the 2017-2018 questionnaire that they regularly posted on Facebook and were still active cohort participants. We included an exit survey for those who chose not to participate in order to gauge the reasons for nonparticipation. ResultsWe invited 309 women to participate. Few women signed the consent form (n=52), and only 3 used the Digi.me app to download and transfer their Facebook data. This low participation rate was observed despite modifying our protocol between waves of recruitment, including by (1) excluding active health care workers, who might be less available to participate due to the pandemic, (2) developing a Frequently Asked Questions factsheet to provide more information regarding the protocol, and (3) simplifying the instructions for using the Digi.me app. On our exit survey, the reasons most commonly reported for not participating were concerns regarding data privacy and hesitation sharing personal Facebook posts. The low participation rate suggests that obtaining individual-level Facebook data in a cohort of middle-aged and older women may be challenging. ConclusionsIn this cohort of midlife and older women who were actively participating for over three decades, we were largely unable to obtain permission to access individual-level data from participants’ Facebook accounts. Despite working with a third-party developer to customize an app to implement safeguards for privacy, data privacy remained a key concern in these women. Future studies aiming to leverage individual-level social media data should explore alternate populations or means of sharing social media data.

Tetracyclines (TCs) are widely used for livestock, and the high prevalence of TC-resistant Escherichia coli in livestock has become a serious concern worldwide. In Japan, the National Action Plan on Antimicrobial Resistance in 2016 aimed to reduce the TC resistance rate in E. coli derived from livestock. Flavophospholipol (FPL), used as a feed additive, has an inhibitory effect on the spread of plasmid-mediated antimicrobial resistance. The number of TC-resistant E. coli was determined in pigs administered TCs and/or FPL to clarify the effect of FPL on reducing the number of TC-resistant E. coli in pigs. TC-resistant E. coli and their plasmids were then analyzed. The pigs were divided into four groups: control, doxycycline (DOXY; a TC), FPL, and a DOXY-FPL combination. Their feces were collected from the nursing period to the day before being transported to the slaughterhouse, followed by estimation of TC-resistant E. coli (colony-forming units [CFU]/g). The number of TC-resistant E. coli increased with the use of DOXY, suggesting that DOXY administration provides a selective pressure for TC-resistant E. coli. Supplementation with FPL as a feed additive significantly suppressed the increase in the number of TC-resistant E. coli, especially during the DOXY administration period. Transfer and growth inhibition analyses were performed for TC-resistant isolates. FPL inhibited the conjugational transfer and growth of a few TC-resistant E. coli isolates. These results suggest that FPL is effective against the spread of TC-resistant E. coli.

Abstract A 24‐year‐old woman diagnosed with 22 q 11.2 deletion syndrome was referred for multiple extractions. Due to the syndrome, the patient had schizophrenia, cardiac anomalies, and maxillofacial complications. This case report suggested that a multidisciplinary team approach is important for perioperative management of patients with 22 q 11.2 deletion syndrome.

Endometritis has a major impact on fertility in postpartum dairy cows. Since previous studies showed an association between reproductive microbiota and perinatal disease, we monitored both bovine uterine and vaginal microbiota in primiparous cows to elucidate the effect of early postpartum microbiota on endometritis. Uterine and vaginal samples were collected at time points from pre-calving to 35 days postpartum (DPP), and analyzed by 16S rRNA sequencing, combined with ancillary bacterial culture. A total of seven healthy cows and seven cows diagnosed with endometritis on 35 DPP were used in the current study. The uterine and vaginal microbiota showed a maximum of 20.1% shared amplicon sequence variants (ASVs) at linked time points. 16S rRNA based analysis and traditional culture methods revealed that Trueperella showed a higher abundance in both uterus and vagina of the endometritis group compared to the healthy group on 21 DPP (U-test p < 0.05). Differential abundance analysis of the uterine microbiota showed that Enterococcus and six bacterial genera including Bifidobacterium were unique to the healthy group on the day of calving (0 DPP) and 28 DPP, respectively. In contrast, Histophilus and Mogibacteriaceae were characteristic bacteria in the vagina pre-calving in cows that later developed endometritis, suggesting that these bacteria could be valuable to predict clinical outcomes. Comparing the abundances of bacterial genera in the uterine microbiota, a negative correlation was observed between Trueperella and several bacteria including Lactobacillus. These results suggest that building an environment where there is an increase in bacteria that are generally recognized as beneficial, such as Lactobacillus, may be one possible solution to reduce the abundance of Trueperella and control endometritis.

Solid electrolytes with high Mg-ion conductivity are required to develop solid-state Mg-ion batteries. The migration energies of the Mg2+ ions of 5,576 Mg compounds tabulated from the inorganic crystal structure database (ICSD) were evaluated via high-throughput calculations. Among the computational results, we focused on the Mg2+ ion diffusion in Mg0.6Al1.2 Si1.8O6, as this material showed a relatively low migration energy for Mg2+ and was composed solely of ubiquitous elements. Furthermore, first-principles molecular dynamics calculations confirmed a single-phase Mg2+ ion conductor. The bulk material with a single Mg0.6Al1.2Si1.8O6 phase was successfully prepared using the sol-gel method. The relative density of the sample was 81%. AC impedance measurements indicated an electrical conductivity of 1.6 × 10−6 Scm−1 at 500°C. The activation energy was 1.32 eV, which is comparable to that of monoclinic-type Mg0.5Zr2(PO4)3.