This study examined associations between pregnancy and infant birth outcomes with child telomere length at age 17 years; and investigated if there are sex differences between pregnancy complications and telomere length. We utilised the population-based prospective Raine cohort study in Western Australia, Australia. 2900 pregnant women were recruited at 16–20 weeks’ gestation (Gen 1), and their children (Gen 2) were followed up over several years. Generalised linear models were used to examine relationships between pregnancy or birth outcomes (gestational diabetes, pre-eclampsia, preterm birth, low birth weight, macrosomia), and as a composite, with telomere length, measured via a DNA sample from blood at 17 years of age. Analyses were adjusted for a range of confounders. Among the 1202 included children, there were no differences in child telomere length for any of the individual maternal or birth weight pregnancy outcomes nor were there any significant interactions between each of the complications (individual or composite) and the sex of the child. However, females born from any of the 5 adverse outcomes had shorter telomeres (estimated mean (SE) = -0.159 (0.061), p = 0.010) than females born in the absence of these complications. Specifically, females born from a pre-eclamptic pregnancy had shorter telomeres than females not born from a pre-eclamptic pregnancy (estimated mean (SE) = -0.166 (0.072), p = 0.022). No relationships were observed in males. Further longitudinal studies are needed to understand mediating factors that are important in predicting offspring telomere length and the necessity to investigate females and males independently.

In this conceptual replication of Sparks and Dale ([2023]. The prediction from MLAT to L2 achievement is largely due to MLAT asessment of underlying L1 abilities. Studies in Second Language Acquisition, 1–25) utilizing a dataset previously reported by Sparks et al. ([2009]. Long-term relationships among early L1 skills, L2 aptitude, L2 affect, and later L2 proficiency. Applied Psycholinguistics, 30, 725–755.), L1 achievement scores over 1st–5th grades and L2 aptitude scores from the Modern Language Aptitude Test (MLAT) in 9th grade were examined as predictors of L2 achievement for U.S. secondary students completing L2 courses in 9th and 10th grades. The study’s focus was on the uniqueness and efficiency of MLAT with respect to measuring L1 achievement in predicting L2 achievement. All L1 measures and MLAT predicted L2 literacy and language, and L1 measures predicted MLAT scores. Word decoding was the strongest overall L1 predictor, though there was variation across the L2 measures. The unique contribution of MLAT was modest, as the majority of total prediction (77–86%) was due to L1 measures. The efficiency of MLAT in capturing predictive variance from L1 abilities was moderately high (median ∼73%) but variable across the L1 and L2 measures. Findings are generally consistent with those of Sparks and Dale (2023) showing that prediction from MLAT to L2 is largely due to MLAT’s assessment of L1 abilities, even though a substantial amount of L2 prediction-relevant L1 variance is missed by MLAT.

Despite the widespread use and effectiveness of the Modern Language Aptitude Test (MLAT) composite score in predicting individual differences in L2 achievement and proficiency, there has been little examination of MLAT subtests, although they have potential for illuminating components of L2 aptitude and the mechanism of prediction. Here we use regression commonality analysis to decompose the predictive variance from the MLAT into unique components for each subtest alone and for each possible combination of subtests (duos, trios, etc.) that may have shared variance. The results, from a longitudinal study of 307 U.S. secondary students during 2 years of Spanish learning, provide strong evidence for the role of literacy-related skills in all subtests and in predicting all L2 outcomes. These and other results support a view of L1 literacy and language skills leading to metalinguistic development, which in turn leads to stronger L2 aptitude and achievement.

Severity of personality disorder is an important determinant of future health. However, this key prognostic variable is not captured in routine clinical practice. Using a large clinical data-set, we explored the predictive validity of items from the Health of Nation Outcome Scales (HoNOS) as potential indicators of personality disorder severity. For 6912 patients with a personality disorder diagnosis, we examined associations between HoNOS items relating to core personality disorder symptoms (self-harm, difficulty in interpersonal relationships, performance of occupational and social roles, and agitation and aggression) and future health service use. Compared with those with no self-harm problem, the total healthcare cost was 2.74 times higher (95% CI 1.66–4.52; P < 0.001) for individuals with severe to very severe self-harm problems. Other HoNOS items did not demonstrate clear patterns of association with service costs. Self-harm may be a robust indicator of the severity of personality disorder, but further replication work is required.

Widespread use of the Modern Language Aptitude Test (MLAT) in L2 studies of individual differences implicitly assumes that L2 aptitude is a distinct cognitive facet. There is considerable evidence for prediction from L1 abilities to L2 learning. In this longitudinal study, L1-MLAT-L2 relations were examined in 307 US secondary students based on six L1 and six L2 measures of language and literacy, and the MLAT. Mediation and regression analyses revealed that each L1 measure individually predicted all L2 scores and MLAT; the L1 measures collectively substantially predicted MLAT scores; MLAT is a significant but moderate mediator of prediction from L1 to L2 scores; and prediction from MLAT to L2 scores is significantly and substantially due to variance in L1 abilities captured by MLAT. Overall, prediction from MLAT is due primarily to its functioning as a measure of L1 abilities, although substantial L1 variance which predicts L2 scores is not captured by the MLAT.

The herbicides that inhibit 4-hydroxyphenylpyruvate dioxygenase (HPPD) are primarily used for weed control in corn, barley, oat, rice, sorghum, sugarcane, and wheat production fields in the United States. The objectives of this review were to summarize 1) the history of HPPD-inhibitor herbicides and their use in the United States; 2) HPPD-inhibitor resistant weeds, their mechanism of resistance, and management; 3) interaction of HPPD-inhibitor herbicides with other herbicides; and 4) the future of HPPD-inhibitor-resistant crops. As of 2022, three broadleaf weeds (Palmer amaranth, waterhemp, and wild radish) have evolved resistance to the HPPD inhibitor. The predominance of metabolic resistance to HPPD inhibitor was found in aforementioned three weed species. Management of HPPD-inhibitor-resistant weeds can be accomplished using alternate herbicides such as glyphosate, glufosinate, 2,4-D, or dicamba; however, metabolic resistance poses a serious challenge, because the weeds may be cross-resistant to other herbicide sites of action, leading to limited herbicide options. An HPPD-inhibitor herbicide is commonly applied with a photosystem II (PS II) inhibitor to increase efficacy and weed control spectrum. The synergism with an HPPD inhibitor arises from depletion of plastoquinones, which allows increased binding of a PS II inhibitor to the D1 protein. New HPPD inhibitors from the azole carboxamides class are in development and expected to be available in the near future. HPPD-inhibitor-resistant crops have been developed through overexpression of a resistant bacterial HPPD enzyme in plants and the overexpression of transgenes for HPPD and a microbial gene that enhances the production of the HPPD substrate. Isoxaflutole-resistant soybean is commercially available, and it is expected that soybean resistant to other HPPD inhibitor herbicides such as mesotrione, stacked with resistance to other herbicides, will be available in the near future.

A heavy down-hole hammer actuated from the surface by a light composition rope was used to place instrumented probes into the active, 7m thick, clast-rich till underlying a site on Black Rapids Glacier, Alaska, USA, where the ice is 500m thick. A till penetration of about 2.5m was obtained, and greater depths seem possible. The probes measured pore-water pressure and two axes of tilt, which they broadcasted, without wires, to a receiver just above the ice–till interface.

Few studies on herbicide resistance report data to establish unambiguously the correlation between genotype and phenotype. Here we report on the importance of the EPSPS prolyl106 point mutation to serine (P106S) in conferring resistance to glyphosate in a goosegrass population from Davao, Mindanao Island, the Philippines (Davao). Initial rate-response studies showed clear survivors within the Davao population at glyphosate rates that completely controlled the standard sensitive goosegrass population (STD1). Assessment of potential resistance mechanisms identified the presence of P106S mutant individuals in the Davao population. Polymerase chain reaction (PCR) amplification of specific alleles (PASA) analysis established that the mixed-resistant Davao population was comprised of 39.1% homozygous proline wild-type (PP106), 3.3% heterozygous serine mutant (PS106), and 57.6% homozygous serine mutant (SS106) genotypes. Further rate-response studies on plants with a predetermined genotype estimated the Davao SS106 individuals to be approximately 2-fold more resistant to glyphosate compared to Davao PP106 individuals. Extensive analysis at different goosegrass growth stages and glyphosate rates established strong correlation (P < 0.001) between presence of P106S in EPSPS and the resistant phenotype. Importantly, no differences in the pattern of absorbed or translocated 14C–glyphosate were observed between PP106 and SS106 Davao genotypes or Davao and STD1 individuals, suggesting that glyphosate resistance in the Davao population was attributable to an altered target site mechanism. This study demonstrates that whilst P106S in EPSPS confers a moderate resistance level to glyphosate, the mechanism is sufficient to endow glyphosate failure at the recommended field rates.

Acetolactate Synthase- (ALS) inhibiting herbicides are important components for the control of ryegrass species infesting cereal-cropping systems worldwide. Although resistance to ALS herbicides in ryegrasses has evolved more than 25 yr ago, few studies have been dedicated to elucidate the molecular mechanisms involved. To this end, we have investigated the molecular basis of chlorsulfuron, sulfometuron-methyl, and imazapyr resistance in AUS5 and AUS23, two ryegrass populations from Australia. Comparison between whole-plant herbicide assays and DNA sequencing results showed that resistance to the nonmetabolizable herbicide sulfometuron-methyl was associated with four different proline mutations at ALS codon position 197 (P197) in AUS23. In addition to three P197 amino acid changes impacting on the efficacies of the two sulfonylurea herbicides, the tryptophan to leucine target-site mutation at ALS codon position 574 (W574L) was present in AUS5, conferring resistance to both sulfometuron-methyl and imazapyr. The samples were also characterized by non target-site-based resistance impacting on the metabolizable herbicide chlorsulfuron only. Interestingly, compound mutant heterozygotes threonine/serine at ALS position 197, and plants with double mutations at positions 197 and 574 were detected, thus reflecting the ability of this outcrossing species to accumulate mutant alleles. Whole-plant dose-response assays conducted on predetermined wild-type and mutant genotypes originating from the same populations allowed for a more precise estimation of the dominant and very high levels of resistance associated with the proline to serine target-site mutation at ALS codon position 197 (P197S) and W574L mutations. The two highly efficient polymerase chain reaction- (PCR) based derived cleaved amplified polymorphic sequence (dCAPS) markers developed here will allow for quick confirmation of 197 and 574 ALS target-site resistance in ryegrass species field samples and also contribute to identify populations characterized by other likely resistance mechanisms in this important weed species.

Previous observations have shown spatial covariances between microwave emission from Antarctic firn at 6 cm wavelength, physical firn temperature and firn-density stratification. Such observations motivate us to understand the physics underlying such covariances and, based on that understanding, to develop estimation methods for firn in which density, and therefore dielectric permittivity, varies randomly in discrete layers with mean thicknesses on the order of centimeters. The model accounts for depth profiles of the physical temperature, mean density and variance of random density fluctuations from layer to layer. We also present a procedure to estimate emission-model input parameters objectively from in situ density-profile observations, as well as uncertainties in the input parameters and corresponding uncertainties in theoretical brightness-temperature predictions. We compare emission-model predictions with ground-based observations at four diverse sites in Antarctica which span a range of accumulation rates and other parameters. We use coincident characterization data to estimate model inputs. At two sites, layered-medium emission-model predictions based on the most probable input parameters (i.e. with no model tuning) agree with observations to within 3.5% for incidence angles≤50°. Corresponding figures for the other two sites are 7.5% and 10%. However, uncertainties in the input parameters are substantial due to the limited length and depth resolution of the characterization data. Uncertainties in brightness-temperature predictions are correspondingly substantial. Thus brightness-temperature predictions for the last-mentioned sites based on only slightly less probable input parameters are also in close agreement with observations. The significance of agreements and discrepancies could be clarified using characterization measurements with finer depth resolution.

The implementation of a successful glyphosate resistance management strategyrequires a simple and cost-effective method for detecting resistance in keyweeds. To date, however, glyphosate resistance is still routinely confirmedvia laborious and time consuming whole-plant pot assays using seedscollected at the end of the growing season. Here, we describe a simple,early-season bioassay for detecting evolved glyphosate resistance in grassand broadleaf weeds. It involves transplanting suspected glyphosateresistant seedlings alongside known sensitive and resistant standards intoagar containing informative rates of herbicide and recording percentagesurvival 14 d after plating. The method was validated using sensitive andresistant populations of Lolium, Eleusine, Conyza, and Amaranthus speciesencompassing the main glyphosate resistance mechanisms, namely, impairedtranslocation, EPSPS gene duplication, and mutations. The whole plant potand agar-based seedling tests generated comparable resistance indices indose-response assays and percentage survival at discriminating glyphosaterates. The method was applied successfully to detect resistance in a rigidryegrass population collected from a French vineyard well before glyphosatewas applied in the field for the current season. Additionally, the test wasshown to be highly transferable to several other grass and broadleaf weedsthat have evolved resistance to glyphosate. One major attribute of themethod is that it is capable of detecting resistance regardless of themechanism involved. In addition to being very simple, quick and,cost-effective, it allows determination of glyphosate resistance in weedsprior to field application. It thus offers the opportunity for an informedchoice of herbicides for effective weed control.

Because individuals develop dementia as a manifestation of neurodegenerative or neurovascular disorder, there is a need to develop reliable approaches to their identification. We are undertaking an observational study (Ontario Neurodegenerative Disease Research Initiative [ONDRI]) that includes genomics, neuroimaging, and assessments of cognition as well as language, speech, gait, retinal imaging, and eye tracking. Disorders studied include Alzheimer’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, and vascular cognitive impairment. Data from ONDRI will be collected into the Brain-CODE database to facilitate correlative analysis. ONDRI will provide a repertoire of endophenotyped individuals that will be a unique, publicly available resource.

“Finding Your Agricultural Advantage” is a collection of four programs—one to generate case studies, one to do “trial-and-error” solutions, one to display linear programming solutions, and one to maintain case study data files. The four programs can be used together or individually as instructor preferences dictate in teaching farm planning. A step-by-step method for teaching with the software is presented as an example of its use.

A structural probit model is estimated to determine the change in the probability of selecting a milk handler. Cooperatives are thought to have lower prices and higher deductions than independent milk handlers and these factors reduce the probability that a farmer will select a cooperative by 0.39 and 0.32. Cooperatives are thought to have better services and an assured market and payment than independent milk handlers and these factors increase the probability that a farmer will select a cooperative by 0.20 and 0.26. This indicates that many cooperative members value monetary characteristics over non-monetary characteristics.

Shorter telomere length (TL) has found to be associated with lower birth weight and with lower cognitive ability and psychiatric disorders. However, the direction of causation of these associations and the extent to which they are genetically or environmentally mediated are unclear. Within-pair comparisons of monozygotic (MZ) and dizygotic (DZ) twins can throw light on these questions. We investigated correlations of within pair differences in telomere length, IQ, and anxiety/depression in an initial sample from Brisbane (242 MZ pairs, 245 DZ same sex (DZSS) pairs) and in replication samples from Amsterdam (514 MZ pairs, 233 DZSS pairs) and Melbourne (19 pairs selected for extreme high or low birth weight difference). Intra-pair differences of birth weight and telomere length were significantly correlated in MZ twins, but not in DZSS twins. Greater intra-pair differences of telomere length were observed in the 10% of MZ twins with the greatest difference in birth weight compared to the bottom 90% in both samples and also in the Melbourne sample. Intra-pair differences of telomere length and IQ, but not of TL and anxiety/depression, were correlated in MZ twins, and to a smaller extent in DZSS twins. Our findings suggest that the same prenatal effects that reduce birth weight also influence telomere length in MZ twins. The association between telomere length and IQ is partly driven by the same prenatal effects that decrease birth weight.

Studies on the role of diet in the development of chronic diseases often rely on self-report surveys of dietary intake. Unfortunately, many validity studies have demonstrated that self-reported dietary intake is subject to systematic under-reporting, although the vast majority of such studies have been conducted in industrialised countries. The aim of the present study was to investigate whether or not systematic reporting error exists among the individuals of African ancestry (n 324) in five countries distributed across the Human Development Index (HDI) scale, a UN statistic devised to rank countries on non-income factors plus economic indicators. Using two 24 h dietary recalls to assess energy intake and the doubly labelled water method to assess total energy expenditure, we calculated the difference between these two values ((self-report − expenditure/expenditure) × 100) to identify under-reporting of habitual energy intake in selected communities in Ghana, South Africa, Seychelles, Jamaica and the USA. Under-reporting of habitual energy intake was observed in all the five countries. The South African cohort exhibited the highest mean under-reporting ( − 52·1 % of energy) compared with the cohorts of Ghana ( − 22·5 %), Jamaica ( − 17·9 %), Seychelles ( − 25·0 %) and the USA ( − 18·5 %). BMI was the most consistent predictor of under-reporting compared with other predictors. In conclusion, there is substantial under-reporting of dietary energy intake in populations across the whole range of the HDI, and this systematic reporting error increases according to the BMI of an individual.