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The ignorance of the role of middle leaders as a 'key broker' between school principals and teachers in the literature has motivated this study to investigate the effects of middle leaders' learning-centred leadership on teacher professional learning through teacher mastery goals and their self-efficacy with the moderating effect of the quality of communication between middle leaders and teachers. A total of 453 data were collected from 24 primary and secondary school teachers in six districts in Kedah. This study employed partial least squares structural equation modelling approach. Findings revealed that learning-centred leadership has a significant and positive effect on teacher professional learning. Teacher mastery goals and teacher self-efficacy have significant mediating effects on teacher professional learning. The effect of learning-centred leadership on teacher professional learning is stronger when the levels of quality of communication between leaders and teachers are higher compared to their counterparts. Hence, future principal preparation programmes should equip future principals with the knowledge of learning-centred leadership that could facilitate teacher learning happening and flourishing.

Accurate determination of sodium chloride (NaCl) density in water is vital for assessing environmental impact, preventing soil salinization in agriculture, ensuring quality and consistency in industrial processes, facilitating medical treatments, and maintaining taste and preservation standards in the food and beverage industry. This paper introduces a novel microwave sensor design specifically tailored to accurately assess NaCl density in aqueous solutions. Starting with a standard solution of 10 g of salt dissolved in 100 ml of water, resulting in a molarity of approximately 1.71 M, five distinct samples are meticulously prepared. These samples cover a range of NaCl concentrations, with different ratios of salt solution and drinking water, including pure water, 10 ml of salt solution with 90 ml of water, 20 ml of salt solution with 80 ml of water, 30 ml of salt solution with 70 ml of water, and 40 ml of salt solution with 60 ml of water. Each sample undergoes analysis using the developed microwave sensor to determine its transmission coefficient. The magnitude of the transmission coefficient is closely tied to the density of the salt solution based on molarity. Through a detailed regression analysis, a strong quantitative relationship between the transmission coefficient and salt solution density is revealed. This correlation can be accurately represented by a third-order polynomial equation. This research is significant as it advances microwave sensor technology, allowing for accurate and efficient measurement of NaCl density in water.

BACKGROUND: Reference intervals of thyroid-stimulating hormone (TSH) and free thyroxine (FT4) are statistically defined by the 2·5-97·5th percentiles, without accounting for potential risk of clinical outcomes. We aimed to define the optimal healthy ranges of TSH and FT4 based on the risk of cardiovascular disease and mortality. METHODS: This systematic review and individual participant data (IPD) meta-analysis identified eligible prospective cohorts through the Thyroid Studies Collaboration, supplemented with a systematic search via Embase, MEDLINE (Ovid), Web of science, the Cochrane Central Register of Controlled Trials, and Google Scholar from Jan 1, 2011, to Feb 12, 2017 with an updated search to Oct 13, 2022 (cohorts found in the second search were not included in the IPD). We included cohorts that collected TSH or FT4, and cardiovascular outcomes or mortality for adults (aged ≥18 years). We excluded cohorts that included solely pregnant women, individuals with overt thyroid diseases, and individuals with cardiovascular disease. We contacted the study investigators of eligible cohorts to provide IPD on demographics, TSH, FT4, thyroid peroxidase antibodies, history of cardiovascular disease and risk factors, medication use, cardiovascular disease events, cardiovascular disease mortality, and all-cause mortality. The primary outcome was a composite outcome including cardiovascular disease events (coronary heart disease, stroke, and heart failure) and all-cause mortality. Secondary outcomes were the separate assessment of cardiovascular disease events, all-cause mortality, and cardiovascular disease mortality. We performed one-step (cohort-stratified Cox models) and two-step (random-effects models) meta-analyses adjusting for age, sex, smoking, systolic blood pressure, diabetes, and total cholesterol. The study was registered with PROSPERO, CRD42017057576. FINDINGS: We identified 3935 studies, of which 53 cohorts fulfilled the inclusion criteria and 26 cohorts agreed to participate. We included IPD on 134 346 participants with a median age of 59 years (range 18-106) at baseline. There was a J-shaped association of FT4 with the composite outcome and secondary outcomes, with the 20th (median 13·5 pmol/L [IQR 11·2-13·9]) to 40th percentiles (median 14·8 pmol/L [12·3-15·0]) conveying the lowest risk. Compared with the 20-40th percentiles, the age-adjusted and sex-adjusted hazard ratio (HR) for FT4 in the 80-100th percentiles was 1·20 (95% CI 1·11-1·31) for the composite outcome, 1·34 (1·20-1·49) for all-cause mortality, 1·57 (1·31-1·89) for cardiovascular disease mortality, and 1·22 (1·11-1·33) for cardiovascular disease events. In individuals aged 70 years and older, the 10-year absolute risk of composite outcome increased over 5% for women with FT4 greater than the 85th percentile (median 17·6 pmol/L [IQR 15·0-18·3]), and men with FT4 greater than the 75th percentile (16·7 pmol/L [14·0-17·4]). Non-linear associations were identified for TSH, with the 60th (median 1·90 mIU/L [IQR 1·68-2·25]) to 80th percentiles (2·90 mIU/L [2·41-3·32]) associated with the lowest risk of cardiovascular disease and mortality. Compared with the 60-80th percentiles, the age-adjusted and sex-adjusted HR of TSH in the 0-20th percentiles was 1·07 (95% CI 1·02-1·12) for the composite outcome, 1·09 (1·05-1·14) for all-cause mortality, and 1·07 (0·99-1·16) for cardiovascular disease mortality. INTERPRETATION: There was a J-shaped association of FT4 with cardiovascular disease and mortality. Low concentrations of TSH were associated with a higher risk of all-cause mortality and cardiovascular disease mortality. The 20-40th percentiles of FT4 and the 60-80th percentiles of TSH could represent the optimal healthy ranges of thyroid function based on the risk of cardiovascular disease and mortality, with more than 5% increase of 10-year composite risk identified for FT4 greater than the 85th percentile in women and men older than 70 years. We propose a feasible approach to establish the optimal healthy ranges of thyroid function, allowing for better identification of individuals with a higher risk of thyroid-related outcomes. FUNDING: None.

BACKGROUND: Various factors modulate circulating testosterone in men, affecting interpretation of testosterone measurements. PURPOSE: To clarify factors associated with variations in sex hormone concentrations. DATA SOURCES: Systematic literature searches (to July 2019). STUDY SELECTION: Prospective cohort studies of community-dwelling men with total testosterone measured using mass spectrometry. DATA EXTRACTION: Individual participant data (IPD) (9 studies; n = 21 074) and aggregate data (2 studies; n = 4075). Sociodemographic, lifestyle, and health factors and concentrations of total testosterone, sex hormone-binding globulin (SHBG), luteinizing hormone (LH), dihydrotestosterone, and estradiol were extracted. DATA SYNTHESIS: Two-stage random-effects IPD meta-analyses found a nonlinear association of testosterone with age, with negligible change among men aged 17 to 70 years (change per SD increase about the midpoint, -0.27 nmol/L [-7.8 ng/dL] [CI, -0.71 to 0.18 nmol/L {-20.5 to 5.2 ng/dL}]) and decreasing testosterone levels with age for men older than 70 years (-1.55 nmol/L [-44.7 ng/dL] [CI, -2.05 to -1.06 nmol/L {-59.1 to -30.6 ng/dL}]). Testosterone was inversely associated with body mass index (BMI) (change per SD increase, -2.42 nmol/L [-69.7 ng/dL] [CI, -2.70 to -2.13 nmol/L {-77.8 to -61.4 ng/dL}]). Testosterone concentrations were lower for men who were married (mean difference, -0.57 nmol/L [-16.4 ng/dL] [CI, -0.89 to -0.26 nmol/L {-25.6 to -7.5 ng/dL}]); undertook at most 75 minutes of vigorous physical activity per week (-0.51 nmol/L [-14.7 ng/dL] [CI, -0.90 to -0.13 nmol/L {-25.9 to -3.7 ng/dL}]); were former smokers (-0.34 nmol/L [-9.8 ng/dL] [CI, -0.55 to -0.12 nmol/L {-15.9 to -3.5 ng/dL}]); or had hypertension (-0.53 nmol/L [-15.3 ng/dL] [CI, -0.82 to -0.24 nmol/L {-23.6 to -6.9 ng/dL}]), cardiovascular disease (-0.35 nmol/L [-10.1 ng/dL] [CI, -0.55 to -0.15 nmol/L {-15.9 to -4.3 ng/dL}]), cancer (-1.39 nmol/L [-40.1 ng/dL] [CI, -1.79 to -0.99 nmol/L {-51.6 to -28.5 ng/dL}]), or diabetes (-1.43 nmol/L [-41.2 ng/dL] [CI, -1.65 to -1.22 nmol/L {-47.6 to -35.2 ng/dL}]). Sex hormone-binding globulin was directly associated with age and inversely associated with BMI. Luteinizing hormone was directly associated with age in men older than 70 years. LIMITATION: Cross-sectional analysis, heterogeneity between studies and in timing of blood sampling, and imputation for missing data. CONCLUSION: Multiple factors are associated with variation in male testosterone, SHBG, and LH concentrations. Reduced testosterone and increased LH concentrations may indicate impaired testicular function after age 70 years. Interpretation of individual testosterone measurements should account particularly for age older than 70 years, obesity, diabetes, and cancer. PRIMARY FUNDING SOURCE: Medical Research Future Fund, Government of Western Australia, and Lawley Pharmaceuticals. (PROSPERO: CRD42019139668).

Taxonomy—the classification of species—is an important branch of biology that allows us to systematically understand and study biodiversity. Conventional taxonomy relies heavily on morphological and anatomical structures for classification, but recent discoveries of potentially cryptic species and morphological plasticity in many species underscore the importance of having an alternative or complementary method for species classification. In this paper, we discuss the emerging method of classification using biochemical signals, i.e., chemotaxonomy. We also present a case study on the feasibility of biomarker-based chemotaxonomy on the marine red alga Laurencia snackeyi using halogenated snyderane-type sesquiterpenes, which were proposed in earlier studies.

Acquired drug resistance to anticancer targeted therapies remains an unsolved clinical problem. Although many drivers of acquired drug resistance have been identified1-4, the underlying molecular mechanisms shaping tumour evolution during treatment are incompletely understood. Genomic profiling of patient tumours has implicated apolipoprotein B messenger RNA editing catalytic polypeptide-like (APOBEC) cytidine deaminases in tumour evolution; however, their role during therapy and the development of acquired drug resistance is undefined. Here we report that lung cancer targeted therapies commonly used in the clinic can induce cytidine deaminase APOBEC3A (A3A), leading to sustained mutagenesis in drug-tolerant cancer cells persisting during therapy. Therapy-induced A3A promotes the formation of double-strand DNA breaks, increasing genomic instability in drug-tolerant persisters. Deletion of A3A reduces APOBEC mutations and structural variations in persister cells and delays the development of drug resistance. APOBEC mutational signatures are enriched in tumours from patients with lung cancer who progressed after extended responses to targeted therapies. This study shows that induction of A3A in response to targeted therapies drives evolution of drug-tolerant persister cells, suggesting that suppression of A3A expression or activity may represent a potential therapeutic strategy in the prevention or delay of acquired resistance to lung cancer targeted therapy.

Nanoscale zero valent iron (nZVI) is used to remediate aquifers polluted by organochlorines or heavy metals and was also suggested to eliminate harmful algal blooms. nZVI can therefore affect microorganisms in the vicinity of the application area, including microalgae. However, studies on early transcriptomic effects of microalgae after exposure to nZVI are rare. Here, we described the early physiological and transcriptomic response of the freshwater ecological indicator green microalga, Raphidocelis subcapitata ATCC 22662, to 100 mg/L of reactive nZVI and non-reactive nano-magnetite (nFe3O4). The combined effect of shading and the release of total iron from nZVI posed a short-term inhibition effect leading to 15 % of deformed cells and cytosol leakage, while cells viability increased after 24 h. nZVI triggered a more pronounced transcriptomic response with (7380 differentially expressed genes [DEGs]) compared to nFe3O4 (4601 DEGs) after 1 h. nZVI, but not nFe3O4 increased the expression of genes function in DNA repair and replication, while deactivated carbohydrate-energy metabolisms, mitochondria signaling, and transmembrane ion transport. This study highlights an early fate assessment of algal cells under nZVI and nFe3O4 exposure using next-generation risk assessment methods and will serve as valuable information for safe and sustainable application of nZVI in water remediation.

Purpose: Technological advancements and the increase in public interest in digital financial solutions have led to the rise of the cryptocurrency market. This is because cryptocurrencies are offering several advantages compared to traditional banking. However, cryptocurrency adoption among Selangor’s citizens remains low and leads to missed economic prospects. Thus, this study aims to investigate the key factors influencing the adoption of cryptocurrencies among Selangor’s citizens. Design/Methodology/Approach: This study employs a quantitative approach using surveys to gather insights from 300 Selangor citizens. This study will utilize convenience sampling techniques to administer questionnaires to 300 selected respondents from Selangor. Data analysis will be conducted using SPSS to provide in-depth statistical insights on the adoption patterns and motivations. Findings: This study is expected to reveal performance expectancy, effort expectancy, social influence and facilitating conditions are significant drivers of cryptocurrency adoption. Findings of this study will suggest that the perceived benefits, ease of use, social dynamics surrounding cryptocurrency use, and resource availability have a stronger impact on adoption decisions. Implications/Originality/Value: This study suggests that in order to encourage cryptocurrency adoption in Selangor, the Malaysian government's efforts should focus on raising awareness on cryptocurrency benefits and addressing social influences. Improving facilitating conditions and reducing the perceived complexity of cryptocurrency usage are also significant for promoting wider adoption.

Background: As people age the risk of dementia increases. Balance and strength deteriorate with ageing, but their associations with dementia are not clear. We aimed to determine relationships of balance and strength performance with incident dementia in the Health in Men Study (HIMS) cohort. Methods: We used wave 4 of the HIMS as baseline for analyses (2011–2013), following 1261 men until December 2017 via data linkage to determine incident dementia. Balance was measured using a modified Balance Outcome Measure for Elder Rehabilitation (mBOOMER) Score and strength with the knee extension test. Cox proportional hazards regression was used, adjusting for sociodemographic and health data. Strength and balance scores were analysed non-linearly using restricted cubic splines. Results: 13.7% of men were diagnosed with dementia over a mean period of 4.7 (SD 1.5) years. Higher baseline mBOOMER scores were associated with a reduced risk of incident dementia, with greater changes in risk at higher mBOOMER scores (9 vs 8: HR 0.80, 95% CI 0.73–0.88; 12 vs 11: 0.49, 95% HR 0.36–0.68). Higher baseline lower limb strength was associated with a reduced risk of incident dementia, with greater changes occurring at lower scores, plateauing at around 25 kg (5 vs 4: HR 0.93, 95% CI 0.89–0.98; 25 vs 24: HR 0.99, 95% CI 0.95–1.03). Conclusions: This study demonstrated a non-linear association of better performance in both strength and balance with reduced likelihood of incident dementia. These results raise the hypothesis that strategies to improve strength and balance could reduce the incidence of dementia in older men.

Low back pain (LBP) is a prevalent spinal issue, affecting eight out of ten individuals. Notably, lumbar intervertebral disc (IVD) abnormalities frequently contribute to LBP. To diagnose LBP, Magnetic Resonance Imaging (MRI) is crucial for obtaining detailed spinal images. This paper employs deep learning (DL) to detect and locate lumbar IVD in sagittal MR images. It further classifies lumbar IVDs as healthy or herniated, utilizing both novel convolutional neural network (CNN) and conventional CNN models. The dataset utilized comprises MR images from 32 patients, with 10 exhibiting healthy discs and the remaining 22 posing a mix of healthy and herniated discs, totaling 160 lumbar discs, incorporating 112 healthy and 48 herniated discs. In this study, ResNet-50 architecture in the Novel Lumbar IVD detection (NLID) model served as the feature extractor to segment the five lumbar IVDs from MR images. The features extracted from ResNet-50 were input into YOLOv2 for the identification of the region of interest (ROI). The findings indicate that optimal performance was achieved at the 22nd Rectified Linear Unit (ReLU) activation layer, boasting a remarkable 99.59% average precision, 97.22% F1-score, 94.59% precision, and a perfect 100% recall. This commendable performance consistently held above the 85% threshold until the 22nd ReLU activation layer. Regarding imbalanced dataset classification, AlexNet emerged as the frontrunner among other pre-trained networks, boasting the highest test accuracy of 90.63%, and an impressive F1 score of 88.77%. Meanwhile, the Novel Lumbar IVD Classification (NLIC) model achieved superior results with 93.75% test accuracy, and 92.27% F1-score. In the setting of the balanced dataset, NLIC achieved 96.88% test accuracy, and 96.46% F1-score with fewer epochs compared to AlexNet, affirming the robustness of the novel trained-from-scratch network. These findings distinctly underscore the effectiveness of CNNs in both medical image segmentation and classification.