A variety of larvae and parthenitae of trematodes have been detected in gastropods in the intertidal zone in Japan. However, because of the difficulty associated with the morphological identification of these stages, they have rarely been identified to the species or higher taxonomic levels. In this study, trematodes of these stages were sampled from intertidal gastropods in the Japanese coastal regions and were identified to the species, genus, or family levels morphologically and molecularly to elucidate or predict their life cycles. Investigation of 17 gastropod species (682 individuals in total) from 14 localities led to the detection of trematodes in 47 individuals belonging to six snail species. The infected gastropods were morphologically identified as Nipponacmea fuscoviridis, Monodonta confusa, Trochus sacellum, Batillaria attramentaria, Littorina brevicula, and Purpuradusta gracilis. Our molecular analyses revealed that sporocysts, rediae, and metacercariae from the gastropods were divided into 14 species belonging to nine families: Philophthalmidae, Fellodistomidae, Gymnophallidae, Lepocreadiidae, Heterophyidae, Opisthorchiidae, Notocotylidae, Microphallidae, and Opecoelidae. These trematodes were thought to use fishes, octopuses, seabirds, and marine mammals as their definitive hosts. Marine organisms such as jellyfishes, crustaceans, and fishes are also thought to act as the second intermediate and paratenic hosts of few present trematode species. As for the other trematode species, DNA barcodes of trematodes from various marine organisms will also illuminate the life cycles in future.

Background: Traumatic brain injury (TBI) patients exhibit variable post-injury recovery trajectories. Days at Home (DAH) is a patient-centered measure that captures healthcare transitions and offers a more nuanced understanding of recovery. Here, we use DAH to characterize longterm recovery trajectories for moderate to severe TBI (msTBI) survivors. Methods: This multicenter retrospective cohort study utilized population health data from Ontario to identify adults sustaining isolated msTBI hospitalized between 2009-2021. DAH were calculated in distinct 30-day intervals from index admission to 3 years post-injury; latent class mixed modeling identified unique recovery trajectories and trajectory attributes were quantified. Results: There were 2,510 patients eligible for latent class analysis. Four DAH trajectories were identified: early recovery (69.9%), intermediate recovery (11.4%), late recovery (2.9%), and poor recovery (15.8%). Patients in the poor recovery group were older, more frail, and had lower admission GCS scores, while those in early recovery exhibited lower acute care needs. Intermediate and late recovery groups exhibited protracted transitions home, with near-complete reintegration by 24 months. A prediction model distinguished unfavorable trajectories with good accuracy (C-index=0.824). Conclusions: Despite high initial institutional care requirements, 85% of patients reintegrated into the community within three years of msTBI. These findings shed light on post-injury care requirements for brain-injured patients.

Background: Artificial intelligence (AI) holds promise to predict outcomes for patients sustaining moderate to severe traumatic brain injury (msTBI). This systematic review sought to identify studies utilizing AI-based methods to predict mortality and functional outcomes after msTBI, where prognostic uncertainty is highest. Methods: The APPRAISE-AI quantitative evidence appraisal tool was used to evaluate methodological quality of included studies by determining overall scores and domain-specific scores. We constructed a multivariable linear regression model using study sample size, country of data collection, publication year and journal impact factor to quantify associations with overall APPRAISE-AI scores. Results: We identified 38 studies comprising 591,234 patients with msTBI. Median APPRAISE-AI score was 45.5 (/100 points), corresponding to moderate study quality. There were 13 low-quality studies (34%) and only 5 high-quality studies (13%). Weakest domains were methodological conduct, robustness of results and reproducibility. Multivariable linear regression highlighted that higher journal impact factor, larger sample size, more recent publication year and use of data that were collected in a high-income country were associated with higher APPRAISE-AI overall scores. Conclusions: We identified several study weaknesses of existing AI-based prediction models for msTBI; this work highlights methodological domains that require quality improvement to ultimately ensure safety and effiicacy of clinical AI models.

Background: Despite the utility of administrative health data, there remains a lack of patient-centered outcome measures to meaningfully capture morbidity after traumatic brain injury (TBI). We sought to characterize and validate days at home (DAH) as a feasible measure to assess population-level moderate to severe TBI (msTBI) outcomes and health resource utilization. Methods: We utilized linked health administrative data sources to identify adults with msTBI patients presenting to trauma centers in Ontario injured between 2009-2021. DAH at 180 days reflects the total number of days spent alive and at home excluding the days spent institutionalized in acute care, rehabilitation, inpatient mental health settings or post-acute readmissions. Construct and predictive validity were determined; we additionally estimated minimally important difference (MID) in DAH180days. Results: There were 6340 patients that met inclusion criteria. Median DAH180days were 70 days (interquartile range 0-144). Increased health resource utilization at baseline, older age, increasing cranial injury severity and major extracranial injuries were significantly associated with fewer DAH180days. DAH180days was correlated to DAH counts at 1-3 years. The average MID estimate from anchor-based and distribution-based methods was 18 days. Conclusions: We introduce DAH180days as a feasible and sufficiently responsive patient-centered outcome measure with construct, predictive and face validity in an msTBI population.

Background: Employment and personal income loss after traumatic brain injury (TBI) is a major source of post-injury stress and barrier to societal reintegration for affected patients. We sought to quantify the labor market implications for tax-filing adult TBI survivors. Methods: We performed a matched difference-in-difference analysis using a national retrospective cohort of working adult TBI survivors injured between 2007-2017. Linear and logistic mixed effects regressions were used to estimate the magnitude of personal income loss and proportion of patients displaced from the workforce in the three post-injury years (Y+1 to Y+3). Results: Among 18,050 patients identified with TBI, the adjusted average loss of personal annual income was $-7,635 dollars in Y+1 and $-5,000 in Y+3. An additional -7.8% individuals were newly unemployed compared to the pre-injury baseline. For mild, moderate, and severe TBI subgroups, income loss was $-3354, $-6750, and $-17375 respectively in Y+3; the proportion of newly unemployed individuals in Y+3 was 5.8%, 9.2%, and 20% lower than baseline. We estimated 500 million dollars of incurred labor markets losses related to TBI in Canada. Conclusions: This work represents the first national cohort data quantifying the labor market implications of TBI. These results may be used to inform post-injury care pathways and vocational rehabilitation.

Background: We aimed to develop an efficient and reliable artificial intelligence solution to automate prediction of neurosurgical intervention using acute traumatic brain injury computed tomography (CT) scans. Methods: TBI patients were identified from 2005 - 2022 at a Level 1 Canadian trauma center. Model training, validation, and testing was performed using head CT scans with patient-level labels corresponding to whether the patient received neurosurgical intervention. The finalized model was then deployed in a simulated prospective fashion on all TBI patients presenting to our center over an 18-month epoch. Results: 2,806 TBI scans were utilized for development of the Automated Surgical Intervention Support Tool (ASIST-TBI). 612 additional consecutive scans were used for simulated prospective model deployment. Prediction of neurosurgical intervention exhibited an area under receiver operating curve (AUC) of 0.92, accuracy of 0.87, sensitivity of 0.87, and specificity of 0.88 on the test dataset. On simulated prospective data, the results were: AUC 0.89, sensitivity 0.85, specificity 0.84 and accuracy of 0.84. Conclusions: We demonstrate the development and validation of ASIST-TBI, a machine learning model that accurately predicts whether TBI patients will need neurosurgical intervention. This model has potential application to optimize decision support and province-wide efficiency of inter-facility TBI triage to tertiary care centers.

Currently, dengue control relies largely on reactive vector control programmes. Proactive vector-control using a rational, well-balanced integrated vector management approach may prove more successful for dengue control. As part of the development of a cluster randomized controlled epidemiological trial, a study was conducted in Johor Bahru, Malaysia. The study included one control site (three buildings) and three intervention sites which were treated as follows: targeted outdoor residual spraying only (TORS site, two buildings); deployment of autodissemination devices only (ADD site, four buildings); and the previous two treatments combined (TORS + ADD site, three buildings). The primary entomological measurement was per cent of positive ovitraps—ovitrap index (OI). The effect of each intervention on OI was analyzed by a modified ordinary least squares regression model. Relative to the control site, the TORS and ADD sites showed a reduction in the Aedes OI (−6.5%, P = 0.04 and −8.3%, P = 0.10, respectively). Analysis by species showed that, relative to control, the Ae. aegypti OI was lower in ADD (−8.9%, P = 0.03) and in TORS (−10.4%, P = 0.02). No such effect was evident in the TORS + ADD site. The present study provides insights into the methods to be used for the main trial. The combination of multiple insecticides with different modes of action in one package is innovative, although we could not demonstrate the additive effect of TORS + ADD. Further work is required to strengthen our understanding of how these interventions impact dengue vector populations and dengue transmission.

Studies on community-acquired pneumonia (CAP) and pneumococcal pneumonia (PP) related to the 13-valent pneumococcal conjugate vaccine (PCV13) introduction in Asia are scarce. This study aimed to investigate the epidemiological and microbiological determinants of hospitalised CAP and PP after PCV13 was introduced in Japan. This observational hospital-based surveillance study included children aged ⩽15 years, admitted to hospitals in and around Chiba City, Japan. Participants had bacterial pneumonia based on a positive blood or sputum culture for bacterial pathogens. Serotype and antibiotic-susceptibility testing of Streptococcus pneumoniae and Haemophilus influenzae isolates from patients with bacterial pneumonia were assessed. The CAP hospitalisation rate per 1000 child-years was 17.7, 14.3 and 9.7 in children aged <5 years and 1.18, 2.64 and 0.69 in children aged 5–15 years in 2008, 2012 and 2018, respectively. There was a 45% and 41% reduction in CAP hospitalisation rates, between the pre-PCV7 and PCV13 periods, respectively. Significant reductions occurred in the proportion of CAP due to PP and PCV13 serotypes. Conversely, no change occurred in the proportion of CAP caused by H. influenzae. The incidence of hospitalised CAP in children aged ⩽15 years was significantly reduced after the introduction of PCV13 in Japan. Continuous surveillance is necessary to detect emerging PP serotypes.

A new planar multiple-input–multiple-output (MIMO) antenna for ultra wideband (UWB) applications is presented. The proposed antenna operates over the frequency band from 3.1 to 10.6 GHz and it consists of two identical circular monopoles on an FR4 substrate. The wide isolation is achieved through a novel planar decoupling structure that is being inserted between the dual antennas. Moreover, a center slot is etched on the common ground to further increase isolation. The effectiveness of the decoupling structure is analyzed, and performance study has been performed to investigate the mutual coupling reduction. A good isolation of more than 31 dB has been achieved through the entire UWB band (more than 12 dB improvement over the reference antenna). The proposed UWB antenna with and without the wideband decoupling structure has been investigated and verified both numerically and experimentally. The measurement results of the proposed UWB–MIMO antenna are in good agreement with the simulation results. The proposed UWB antenna has been compared with previous works regarding antenna size, geometric complexity, bandwidth, and isolation level. The proposed antenna has some outstanding characteristics such as a geometric simplicity, compact size, broad bandwidth, and low correlation which give the antenna an excellent diversity performance and a good candidate for UWB applications.

We used a bivariate animal model to investigate the genetic correlations between yield traits or days open (DO) as characters measured in cows and semen production traits as characters measured in bulls. Lactation records of 305-day milk, fat, and protein yields, and DO, from 386 809 first-lactation Holstein cows in Hokkaido, Japan, that calved between 2008 and 2014 were used. Semen production records were collected between 2005 and 2014 and included volume per ejaculate (VOL), sperm concentration (CON), number of sperm per ejaculate (NUM), progressive motility index of sperm (MOT), and MOT after freeze-thawing (A-MOT). Number of sperm per ejaculate was log-transformed into a NUM score (NUMS). A total of 30 373 semen production records from 1196 bulls were obtained. The pedigree file used for analysing the records was involving 885 345 animals. Heritability was estimated for VOL (0.42), CON (0.12), NUMS (0.37), MOT (0.08), and A-MOT (0.11). Weak and negative genetic correlations were recorded between yield traits measured in cows and VOL, CON or NUMS measured in bulls. Moderate and negative genetic correlations were obtained between DO and MOT (–0.42) or A-MOT (–0.43). Selection focused on MOT or A-MOT measured in bulls may therefore improve DO measured in cows.

Ten ice-sheet models are used to study sensitivity of the Greenland and Antarctic ice sheets to prescribed changes of surface mass balance, sub-ice-shelf melting and basal sliding. Results exhibit a large range in projected contributions to sea-level change. In most cases, the ice volume above flotation lost is linearly dependent on the strength of the forcing. Combinations of forcings can be closely approximated by linearly summing the contributions from single forcing experiments, suggesting that nonlinear feedbacks are modest. Our models indicate that Greenland is more sensitive than Antarctica to likely atmospheric changes in temperature and precipitation, while Antarctica is more sensitive to increased ice-shelf basal melting. An experiment approximating the Intergovernmental Panel on Climate Change’s RCP8.5 scenario produces additional first-century contributions to sea level of 22.3 and 8.1 cm from Greenland and Antarctica, respectively, with a range among models of 62 and 14 cm, respectively. By 200 years, projections increase to 53.2 and 26.7 cm, respectively, with ranges of 79 and 43 cm. Linear interpolation of the sensitivity results closely approximates these projections, revealing the relative contributions of the individual forcings on the combined volume change and suggesting that total ice-sheet response to complicated forcings over 200 years can be linearized.

Tensile fracture strengths of fine-grained compressed high-density snow, of compressed and metamorphosed high-density snow-ice, of fine-grained naturally settled snow, and of snow-ice artificially made from the settled snow by freezing with absorbed water, were obtained at constant deformation speeds (constant strain-rates) in a temperature range of 264 to 270K. No remarkable temperature dependence of fracture stresses was observed in this temperature range. A critical deformation speed in a tensile test above which all the snow samples, except settled snow, fractured, was 4.2 × 10–7 m s–1. The fracture strength ρ (in N m–2) varied with snow density ρ (kg m–3) as σ = 2.5 × 104 × 1.004 6ρ. In a power-law relationship between strain-rate and maximum stress, ∝ σn, the constant n obtained was 5.3 for all the unfractured snow samples.

We report on the formation of shallow junctions with high activation in both n+/p and p+/n Ge junctions using ion implantation and Flash Lamp Annealing (FLA). The shallowest junction depths (Xj) formed for the n+/p and p+/n junctions were 7.6 nm and 6.1 nm with sheet resistances (Rs) of 860 ohms/sq. and 704 ohms/sq., respectively. By reducing knocked-on oxygen during ion implantation in the n+/p junctions, Rs was decreased by between 5% and 15%. The lowest Rs observed was 235 ohms/sq. with a junction depth of 21.5 nm. Hall measurements clearly revealed that knocked-on oxygen degraded phosphorus activation (carrier concentration). In the p+/n Ge junctions, we show that ion implantation damage induced high boron activation. Using this technique, Rs can be reduced from 475 ohms/sq. to 349 ohms/sq. These results indicate that the potential for forming ultra-shallow n+/p and p+/n junctions in the nanometer range in Ge devices using FLA is very high, leading to realistic monolithically-integrated Ge CMOS devices that can take us beyond Si technology.

Documenting past changes in the East Antarctic surface mass balance is important to improve ice core chronologies and to constrain the ice-sheet contribution to global mean sea-level change. Here we reconstruct past changes in the ratio of surface mass balance (SMB ratio) between the EPICA Dome C (EDC) and Dome Fuji (DF) East Antarctica ice core sites, based on a precise volcanic synchronization of the two ice cores and on corrections for the vertical thinning of layers. During the past 216 000 a, this SMB ratio, denoted SMBEDC/SMBDF, varied between 0.7 and 1.1, being small during cold periods and large during warm periods. Our results therefore reveal larger amplitudes of changes in SMB at EDC compared with DF, consistent with previous results showing larger amplitudes of changes in water stable isotopes and estimated surface temperature at EDC compared with DF. Within the last glacial inception (Marine Isotope Stages, MIS-5c and MIS-5d), the SMB ratio deviates by up to 0.2 from what is expected based on differences in water stable isotope records. Moreover, the SMB ratio is constant throughout the late parts of the current and last interglacial periods, despite contrasting isotopic trends.

In traditional transit timing variations (TTVs) analysis of multi-planetary systems, the individual TTVs are first derived from transit fitting and later modelled using n-body dynamic simulations to constrain planetary masses. We show that fitting simultaneously the transit light curves with the system dynamics (photo-dynamical model) increases the precision of the TTV measurements and helps constrain the system architecture. We exemplify the advantages of applying this photo-dynamical model to a multi-planetary system found in K2 data very close to 3:2 mean motion resonance, K2-19. In this case the period of the larger TTV variations (libration period) is much longer (>1.5 years) than the duration of the K2 observations (80 days). However, our method allows to detect the short period TTVs produced by the orbital conjunctions between the planets that in turn permits to uniquely characterise the system. Therefore, our method can be used to constrain the masses of near-resonant systems even when the full libration curve is not observed.