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Re-calibrating measurements of low-cost air quality monitors using PCR-GPR air quality forecasting models

As a key tool for real-time monitoring of air pollutant concentrations, the chemical sensor, the core component of the low-cost Air Quality Monitor (AQM), is susceptible to a variety of factors during the measurement process, leading to errors in the measurement data. To enhance the measurement accuracy of chemical sensors, this paper presents a calibration method based on the PCR-GPR model. This method not only effectively enhances the measurement accuracy of chemical sensors, but also combines the interpretability of traditional statistical models with the high-precision characteristics of Gaussian Process Regression (GPR) models. First, we perform Principal Component Analysis (PCA) on the measurement data of the AQM to solve the multicollinearity problem. Through PCA, we successfully extracted 8 principal components, which not only contained 95% of the information in the original data, but also effectively eliminated the correlation between the variables, providing a more robust data base for subsequent modeling. Subsequently, we established a Principal Component Regression (PCR) model using the concentration of pollutants measured by the national monitoring station as the dependent variable and the 8 principal components extracted above as the independent variables. The PCR model can effectively extract the linear relationship between the independent and dependent variables, providing a linear part of the explanation for the calibration process. However, there are often complex nonlinear relationships between pollutant concentrations and AQM measurements. To capture these nonlinear relationships, we further established a GPR model with the residuals of the PCR model as the dependent variable and the measurement data of the AQM as the independent variable. By combining the PCR model and the GPR model, we obtained the final PCR-GPR calibration model. It is worth mentioning that this study adopted the time series cross-validation method for data grouping, an innovative approach that is more aligned with real-world scenarios and adequately captures the seasonal variations in pollutant concentrations. The experimental results show that the model exhibits excellent performance on several evaluation metrics and can calibrate the chemical sensor well, improving its measurement accuracy by 16.94% ~ 82.01%.

SCO6564, a novel 3-ketoacyl acyl carrier protein synthase III, contributes in fatty acid synthesis in Streptomyces coelicolor

The genus Streptomyces comprises gram-positive bacteria that produce large numbers of secondary metabolites, which have promising commercial applications and deserve extensive study. Most bacteria synthesize fatty acids using a type II fatty acid synthase, with each step catalyzed by a discrete protein. Fatty acid synthesis has been intensively studied in the model strain Streptomyces coelicolor, in which 3-ketoacyl-acyl carrier protein synthase III (KAS III, FabH) is essential for growth and fatty acid biosynthesis. In this study, the FabH homolog SCO6564 (named FabH2) was identified in the S. coelicolor genome by BLAST analysis. The expression of fabH2 restored the growth of Ralstonia solanacearum fabH mutant and made the mutant produce small amounts of branched-chain fatty acids. FabH2 could condense various substrates, including straight-chain and branched-chain acyl-CoAs, with malonyl-acyl carrier protein to initiate fatty acid synthesis in in vitro assays. The fabH2 deletion did not cause significant changes in the growth or fatty acid composition of S. coelicolor, indicating that fabH2 is nonessential for growth or fatty acid synthesis. However, fabH2 overexpression reduced the blue-pigmented actinorhodin production. Phylogenetic analysis of KAS III from different bacteria revealed that FabH2 belongs to a novel group of FabH-type, which is ubiquitous in Streptomyces spp.

On the interaction between implicit statistical learning and the alternation advantage: Evidence from manual and oculomotor serial reaction time tasks

In this study, we examine how implicit statistical learning (ISL) interacts with the cognitive bias of the alternation advantage in serial reaction time (SRT) tasks. Our aim was to disentangle perceptual from motor aspects of learning, as well as to shed light on the cognitive sources of this alternation effect. We developed a manual (Study 1) and an oculomotor (Study 2) two-choice SRT task, with visual stimuli following the regularities of two binary artificial grammars (Fibonacci and its modification Skip). While these grammars share some deterministic transitional regularities, they differ in their probabilistic transitional regularities and distributional properties. The pattern of manual RTs in Study 1 provide evidence for ISL, showing that subjects learned the deterministic and probabilistic transitions in the two grammars. We also found a bias toward alternation (vs. repetition) in correspondence to non-deterministic points, regardless of their statistical properties in the grammars. Study 2 provides further evidence for both ISL and the alternation advantage, in terms of shorter manual RTs and higher accuracy rates of anticipatory eye movements. Saccadic responses preceding stimulus onset allow us to argue for the perceptual nature of ISL: participants detected regularities in the string by forming S-S associations based on the sequence of the perceived stimuli. Moreover, we propose that shifts in visuospatial attention preceding oculomotor programming play a role in the occurrence of the alternation advantage, and that such an effect is driven by the spatial location of the stimulus. These findings are also discussed with respect to the presence of two (possibly interacting) parsing strategies: statistical generalizations on the string vs. local hierarchical reconstruction.

The maternal X chromosome affects cognition and brain ageing in female mice

Abstract Female mammalian cells have two X chromosomes, one of maternal origin and one of paternal origin. During development, one X chromosome randomly becomes inactivated 1–4 . This renders either the maternal X (X m ) chromosome or the paternal X (X p ) chromosome inactive, causing X mosaicism that varies between female individuals, with some showing considerable or complete skew of the X chromosome that remains active 5–7 . Parent-of-X origin can modify epigenetics through DNA methylation 8,9 and possibly gene expression; thus, mosaicism could buffer dysregulated processes in ageing and disease. However, whether X skew or its mosaicism alters functions in female individuals is largely unknown. Here we tested whether skew towards an active X m chromosome influences the brain and body—and then delineated unique features of X m neurons and X p neurons. An active X m chromosome impaired cognition in female mice throughout the lifespan and led to worsened cognition with age. Cognitive deficits were accompanied by X m -mediated acceleration of biological or epigenetic ageing of the hippocampus, a key centre for learning and memory, in female mice. Several genes were imprinted on the X m chromosome of hippocampal neurons, suggesting silenced cognitive loci. CRISPR-mediated activation of X m -imprinted genes improved cognition in ageing female mice. Thus, the X m chromosome impaired cognition, accelerated brain ageing and silenced genes that contribute to cognition in ageing. Understanding how X m impairs brain function could lead to an improved understanding of heterogeneity in cognitive health in female individuals and to X-chromosome-derived pathways that protect against cognitive deficits and brain ageing.

Exploring short-term memory and listening effort in two-talker conversations: The influence of soft and moderate background noise

Listening to conversations and remembering their content is a highly demanding task, especially in noisy environments. Previous research has mainly focused on short-term memory using simple cognitive tasks with unrelated words or digits. The present study investigates the listeners’ short-term memory and listening effort in conversations under different listening conditions, with and without soft or moderate noise. To this end, participants were administered a dual-task paradigm, including a primary listening task, in which conversations between two talkers were presented, and an unrelated secondary task. In Experiment 1, this secondary task was a visual number-judgment task, whereas in Experiments 2 and 3, it was a vibrotactile pattern recognition task. All experiments were conducted in a quiet environment or under continuous broadband noise. For the latter, the signal-to-noise ratio in Experiments 1 and 2 was +10 dB (soft-noise condition), while in Experiment 3 it was -3 dB (moderate-noise condition). In Experiments 1 and 2, short-term memory of running speech and listening effort were unaffected by soft-noise listening conditions. In Experiment 3, however, the moderate-noise listening condition impaired performance in the primary listening task, while performance in the vibrotactile secondary task was unaffected. This pattern of results could suggest that the moderate-noise listening condition, with a signal-to-noise ratio of -3 dB, required increased listening effort compared to the soft-noise and quiet listening conditions. These findings indicate that listening situations with moderate noise can reduce short-term memory of heard conversational content and increase listening effort, even when the speech signals remain highly intelligible.

Mapping forest cover change and estimating carbon stock using satellite-derived vegetation indices in Alemsaga forest, Ethiopia

Deforestation and forest degradation are significant threats, leading to a decline in forest cover change, biomass and carbon storage, a crucial factor in mitigating climate change. Remote sensing techniques using satellite imagery offer a valuable tool for efficiently monitoring forest cover and biomass over different areas. This study aimed to map and quantify the forest cover change, biomass and carbon stored in the Alemsaga forest, Ethiopia. The study employed Landsat satellite images from four different periods (1992, 2003, 2013, and 2022) to track changes in forest cover and construct carbon storage maps for the Alemsaga forest. The findings from this study can be used to develop better forest conservation and management strategies. The study revealed a significant increase in dense forest cover in Alemsaga (35.34%) between 1992 and 2022, now encompassing 48.25% of the total forest area. Notably, satellite-derived vegetation indices (NDVI & DVI) exhibited a strong correlation with ground observations (R2 = 0.80), and statistical analysis confirmed this relation with above-ground carbon levels (R2 = 0.84). This enabled the creation of carbon storage maps, revealing a substantial increase from 159.31 t/ha in 1992 to 323.84 t/ha by 2022. It’s important to acknowledge that while NDVI/DVI proved effective, other factors might influence carbon storage. However, the study clearly shows that satellite imaging has the capacity to map forest cover change, biomass and estimating carbon stock accurately, which is an important first step toward a better understanding of how forests contribute to climate change.

Mitochondrial swap from cancer to immune cells thwarts anti-tumour defences

Application of principles of cognitive psychology in teaching: Perspectives from undergraduate medical and dental students

Introduction Principles of cognitive psychology (CP) aim to shed light on the fundamentals of perception, attention, and knowledge extraction used for critical thinking, learning, and recollection of information. These principles were incorporated to educate undergraduate medical and dental students, and the study aims to assess the perspectives of medical and dental students regarding applying these principles. Methods The descriptive cross-sectional study was carried out among 555 Bachelor of Dental Surgery (BDS) and Bachelor of Medicine, Bachelor of Surgery (MBBS) students using a validated questionnaire with purposive sampling. Data was analyzed on SPSS version 21. Results The study population comprised 555 undergraduate medical and dental students, with a mean age of 20.55 ± 1.86 years. Of these, 63.4% were pursuing MBBS, and 36.6% were BDS students. The sample included 320 (57.65%) female and 235 (42.35%) male students. MBBS and BDS students exhibited high confidence levels in most aspects of CP principles required for interactive learning. However, they expressed lower confidence in facilitator-student interaction, receiving feedback within large classes, and experiencing online teaching elements. A significant difference was observed between the two groups. In five of six CP attributes, MBBS students demonstrated significantly higher perceptions than BDS students: overcoming cognitive and emotional challenges, recognizing and overcoming ineffective learning strategies, paying attention in class, and integrating knowledge (p < 0.05). Conclusion The current study reveals that MBBS students perceived the application of CP principles more positively than BDS students in key interactive learning areas. Furthermore, the integration of CP principles enhanced session interactivity, student engagement, attention, and retention. To optimize learning outcomes, institutions should consider adopting blended learning strategies, curricular innovations, and active learning methodologies (such as case-based, team-based, and problem-solving approaches) aligned with CP principles. Future longitudinal research could provide deeper insights into the long-term impact of CP principles on student learning and perception.

A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning

Autonomous transportation systems have the potential to greatly impact the way we travel. A vital aspect of these systems is their connectivity, facilitated by intelligent transport applications. However, the safety ensured by the vehicular network can be easily compromised by malicious traffic with the exponential growth of IoT devices. One aspect is malicious traffic identification in Vehicular networks. We proposed a hybrid approach uses automated feature engineering via correlation-based feature selection (CFS) and principal component analysis (PCA)-based dimensionality reduction to reduce feature matrix size before a series of dense layers are used for classification. The intended use of CFS and PCA in the machine learning pipeline serves two folds benefit, first is that the resultant feature matrix contains attributes that are most useful for recognizing malicious traffic, and second that after CFS and PCA, the feature matrix has a smaller dimensionality which in turn means that smaller number of weights need to be trained for the dense layers (connections are required for the dense layers) which resulting in smaller model size. Furthermore, we show the impact of post-training model weight quantization to further reduce the model size. Results demonstrate the effectiveness of feature engineering which improves the classification f1score from 96.48% to 98.43%. It also reduces the model size from 28.09 KB to 20.34 KB thus optimizing the model in terms of both classification performance and model size. Post-training quantization further optimizes the model size to 9 KB. The experimental results using CICIDS2017 dataset demonstrate that proposed hybrid model performs well not only in terms of classification performance but also yields trained models that have a low parameter count and model size. Thus, the proposed low-complexity models can be used for intrusion detection in VANET scenario.

The Food Resources and Kitchen Skills intervention: Protocol of a randomized controlled trial

Introduction Individuals with food insecurity are disproportionately burdened by hypertension (HTN) and type 2 diabetes and face greater barriers to self-managing these conditions. Methods Food Resources and Kitchen Skills (FoRKS) is an ongoing 2-arm parallel randomized controlled trial (RCT) that will enroll 200 adults (35–75 y) with food insecurity and elevated systolic blood pressure (≥120 mmHg) at a large federally qualified health center (FQHC) network in Central Indiana. Blood pressure is measured using an ambulatory blood pressure monitoring (ABPM) device. The (FoRKS, N = 100) intervention integrates hypertension self-management education and support (SMES) with a home-delivered ingredient kit and cooking skills program (16 weeks). Enhanced Usual Care (EUC, N = 100) includes usual care services by the FQHC network, SMES classes (separate from FoRKS), and grocery assistance. This paper describes the protocol for this RCT that will: 1) test the efficacy of FoRKS compared to EUC for reducing systolic blood pressure using an intention to treat protocol, 2) identify behavior change levers (e.g., engagement, social support) and their associations with change in food insecurity, diet quality, and systolic blood pressure, 3) examine the maintenance of outcomes, and 4) assess cost-effectiveness. Conclusions Establishing that a food insecurity and SMES intervention, compared to usual care services, is feasible in FQHCs and efficacious for improving blood pressure and related outcomes would have important public health implications. Understanding the behavior change levers of FoRKS that are associated with changes in health outcomes, whether these outcomes are maintained, and its cost-effectiveness will inform future efforts to address health disparities.

Land cover classification of high-resolution remote sensing images based on improved spectral clustering

Applying unsupervised classification techniques on remote sensing images enables rapid land cover classification. Using remote sensing imagery from the ZY1-02D satellite’s VNIC and AHSI cameras as the basis, multi-source feature information encompassing spectral, edge shape, and texture features was extracted as the data source. The Lanczos algorithm, which determines the largest eigenpairs of a high-order matrix, was integrated with the spectral clustering algorithm to solve for eigenvalues and eigenvectors. The results indicate that this method can quickly and effectively classify land cover. The classification accuracy was significantly improved by incorporating multi-source feature information, with a kappa coefficient reaching 0.846. Compared to traditional classification methods, the improved spectral clustering algorithm demonstrated better adaptability to data distribution and superior clustering performance. This suggests that the method has strong recognition capabilities for pixels with complex spatial shapes, making it a high-performance, unsupervised classification approach.

Drug-induced autoimmune-like hepatitis: A disproportionality analysis based on the FAERS database

Background Drug-induced autoimmune-like hepatitis (DI-ALH) is a potentially life-threatening condition that can lead to acute liver failure and necessitate liver transplantation. While the association between certain drugs and DI-ALH has been documented, a comprehensive analysis of drug-related signals in a large, real-world pharmacovigilance database is lacking. This study aimed to systematically identify drugs linked to DI-ALH by analyzing adverse event reports from the U.S. Food and Drug Administration’s (FDA) Adverse Event Reporting System (FAERS) database. Methods We searched the FAERS database for the term "autoimmune hepatitis" and extracted DI-ALH reports from the first quarter of 2004 to the first quarter of 2024. Positive signal drugs were identified using Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). To confirm a significant drug-adverse event association, each method had to meet predefined thresholds: for PRR and ROR, values were considered significant if the lower 95% confidence interval (CI) was greater than 1 and at least three reports were identified; for BCPNN, an Information Component (IC025) greater than 0 indicated a signal; for EBGM, a value greater than 2 for the lower 95% confidence interval (EBGM05) was used to denote a positive signal. Results A total of 5,723 DI-ALH reports were extracted from the FAERS database. Disproportionality analysis identified 50 drugs with strong associations to DI-ALH, with biologics, statins, antibiotics, and antiviral drugs representing the most common categories. Among these, nitrofurantoin (ROR 94.79, CI 78.53–114.41), minocycline (ROR 77.82, CI 65.09–93.05), and nivolumab (ROR 47.12, CI 15.06–147.39) exhibited the strongest signals. Additionally, several previously unreported drugs, including mesalazine, aldesleukin, onasemnogene abeparvovec-xioi, and nefazodone, were identified as having strong associations with DI-ALH. These findings were consistent across all four signal detection methods, further validating the robustness of the associations. Conclusion This study provides a comprehensive assessment of drugs associated with DI-ALH through a rigorous analysis of the FAERS database using multiple signal detection methods. By identifying both well-known and previously underreported drugs, this study contributes to a more complete understanding of drug-induced liver injury. The findings have important implications for pharmacovigilance strategies and clinical risk assessment. However, limitations inherent in the FAERS database, such as underreporting and the potential for reporting bias, should be considered. Further clinical validation is warranted to confirm these associations.

Cost drivers associated with autologous stem-cell transplant (ASCT) in patients with relapsed/refractory diffuse large B-cell lymphoma in a Japanese real-world setting: A structural equation model (SEM) analysis 2012–2022

Diffuse large B-cell lymphoma (DLBCL) is the most prevalent non-Hodgkin lymphoma, with increasing incidence, in Japan. It is associated with substantial economic burden and relatively poor survival outcomes for relapsed/ refractory (r/r) DLBCL patients. Despite its association with economic burden and the relatively limited number of eligible patients in Japan as reported in previous real-world studies, Japanese clinical guidelines recommend stem-cell transplantation (SCT) for transplant-eligible r/r DLBCL patients. This is the first study to elucidate the total healthcare cost, associated cost drivers and healthcare resource use of SCT among patients with r/r DLBCL in a nationwide setting. The study design included a follow-up period of up to 24 months with subsequent lines of therapies using retrospective nationwide claims data from the Medical Data Vision Co., Ltd. Health Insurance Association from April 2012 to August 2022. Included patients had a confirmed diagnosis of DLBCL, received allogeneic SCT (allo-SCT) or autologous SCT (ASCT) after the first DLBCL diagnosis, and received high-dose chemotherapy during the 6-month look-back period. The results confirmed that no patients had allo-SCT, hence only ASCT was included in the analysis. Structural equation modeling was used to identify potential total healthcare cost drivers by evaluating direct, indirect, and total effects and provide a benchmark reference for future innovative therapies. A total of 108 patients (3.8%) among all DLBCL patients who received SCT met the eligibility criteria and were considered ASCT patients; majority of which were males (n = 63, 58.33%), with a mean [median] (SD) age of 52.04 [55] (9.88) years. A total of 15 patients (13.89%) received subsequent therapies. The most frequent subsequent therapy was GDP-based with or without rituximab (n = 8, 7.41%). The mean [median] (SD) number of follow-up hospitalizations on or after SCT-related hospitalizations was 1.66 [1] (1.36), with a mean [median] (SD) length of hospital stay being 36.88 [34] (12.95) days. The total mean [median] (SD) healthcare cost after adjustment incurred per patient per year during follow-up was $79,052.44 [$42,722.82] ($121,503.65). Number of hospitalizations and Charlson Comorbidity Index scores (+5) were the key drivers of total healthcare costs in patients with r/r DLBCL. Index years 2020–2022 and heart disease as a complication were other statistically significant factors that had positive effects as increase on total healthcare costs.

X chromosome passed from mother to daughter influences brain ageing

Identification and prioritization of novel therapeutic candidates against glutamate racemase from Klebsiella pneumoniae

Background Klebsiella pneumoniae, a gram-negative bacterium in the Enterobacteriaceae family, is non-motile, encapsulated, and a major cause of nosocomial infections, particularly in intensive care units. The bacterium possesses a thick polysaccharide capsule and fimbriae, which contribute to its virulence, resistance to phagocytosis, and attachment to host cells. The bacterium has developed serious resistance to most antibiotics currently in use. Objective This study aims to investigate the structural properties of MurI (glutamate racemase) from Klebsiella pneumoniae and to identify potential candidate inhibitors against the protein, which will help in the development of new strategies to combat the infections related to MDR strains of Klebsiella pneumoniae. Methods The 3D structure of the protein was modelled using SWISS-MODEL, which utilizes the homology modelling technique. After refinement, the structure was subjected to virtual high throughput screening on the TACC server using Enamine AC collection. The obtained molecules were then put through various screening parameters to obtain promising lead candidates, and the selected molecules were then subjected to MD simulations. The data obtained from MD simulations was then assessed with the help of different global dynamics analyses. The protein-ligand complexes were also subjected to MM/PBSA-based binding free energy calculation using the g_mmpbsa program. Results The screening parameters employed on the molecules obtained via virtual screening from the TACC server revealed that Z1542321346 and Z2356864560 out of four molecules have better potential to act as potential inhibitors for MurI protein. The binding free energy values, which came out to be -27.26±3.06 kcal/mol and -29.53±4.29 kcal/mol for Z1542321346 and Z2356864560 molecules, respectively, favoured these molecules in terms of inhibition potential towards targeted protein. Conclusion The investigation of MurI via computational approach and the subsequent analysis of potential inhibitors can pave the way for developing new therapeutic strategies to combat the infections and antibiotic resistance of Klebsiella pneumoniae. This study could significantly help the medical fraternity in the treatment of infections caused by this multidrug-resistant pathogen.

Protocol on a systematic review of nomenclature and outcomes in children with complex critical illness in Paediatric Critical Care: The basis for consensus definition

Introduction Paediatric Critical Care (PCC) supports the recovery of children with severe illness. In the UK, there are 30 PCC units with a total of approximately 400 beds. There is constant demand for these beds with a mean five-day length of stay and admissions increasing at a greater rate than age-specific population growth. Prolonged stay patients account for approximately half of all PCC patient bed days. Children with complex critical illness (CCI) need input from multiple different teams alongside support for their family. CCI often become prolonged PCC-stay patients too. Internationally, there is variation in the definition of CCI, this creates service variation and tensions around what resources can be provided including discharge planning, provision, and support. Objective: The face of Paediatric Critical Care, in the UK and internationally has changed over the last ten years with a growing cohort of complex critically ill patients. This systematic review aims to look at current nomenclature, criteria, and outcome measures of priority in this undefined patient population. Methods and materials Inclusion criteria: All types of studies examining children with complex critical illness (age <18 years) admitted to any paediatric critical care. The review is registered on Prospero. Medline, Embase, Maternity and Infant care, The Cochrane Library, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the Trip database will be searched from 2014 to May 2024. The search was limited to ten years as children with complex critical illness are a relatively new concept within PCC. Therefore, the timeline was limited to increase the accuracy and applicability of the review. Search limits included all languages, excluded the setting of neonatal intensive care, and age>18 years old. The final search strategy was developed in Medline and peer-reviewed by a health research librarian not involved in the study. This was translated to other databases as appropriate. Four independent reviewers will screen citations for eligible studies and perform data extraction. Discussion A systematic review methodology has been used to develop a broad understanding of the literature which will be used to develop further work in this area. Using a rigorous and stepwise approach, the whole spectrum of scientific publications on children with complex critical illness in paediatric intensive care will be reviewed, ensuring this study is as comprehensive as possible. This includes quantitative, qualitative, theoretical, and grey literature. A limitation of this systematic review is the use of many terms to describe children with complex critical illness in the literature resulting in a high number of publications on this topic.

Aspartate signalling drives lung metastasis via alternative translation

E-B-ocimene and brood cannibalism: Interplay between a honey bee larval pheromone and brood regulation in summer dearth colonies

Honey bees balance colony populations against available food resources by adjusting brood rearing during nutritionally-stressed periods. Workers limit colony populations primarily through brood cannibalism of eggs and young larvae but often resume brood rearing when conditions improve. However, extended brood cannibalism reduces brood and removes brood signals that mediate brood rearing, such as E-β-ocimene, a volatile pheromone produced by eggs, young larvae, prepupae and ovipositing queens. We examined the effects of pollen supplementation on ocimene signaling in nutritionally-stressed colonies. Pollen-deprived colonies showed declines in ocimene emissions that coincided with sustained brood cannibalism of pheromone-producing brood. In contrast, pollen-supplemented colonies reared more brood and released more ocimene. Twelve day old workers that completed adult development in pollen-deprived colonies had less well developed hypopharyngeal glands and fat bodies than workers that matured in pollen-supplemented colonies. Given that ocimene emissions increased once brood rearing resumed, we considered the possibility that ocimene may help suppress brood cannibalism and support egg retention in nutritionally stressed nuc colonies. Broodless nucleus frames were treated with synthetic ocimene releases equivalent to 3,744 L2-L3 larvae. All ocimene-supplemented nucs retained large numbers of eggs and young larvae four days after initial treatment. By contrast, half of the unsupplemented nucs cannibalized all of their eggs and L1 larvae. Most of the remaining unsupplemented nuc colonies retained fewer eggs and L1 larvae than ocimene supplemented nuc colonies. E-B-ocimene may prime nutritionally stressed workers to increase brood rearing during dearth periods by projecting the presence of healthy eggs and young larvae.

Clinical, immune and genetic risk factors of malaria-associated acute kidney injury in Zambian children: A study protocol

Background Acute kidney injury (AKI) affects nearly half of children with severe malaria and increases the risk of adverse outcomes such as death and poor cognitive function. The pathogenesis and predictors of malaria-associated acute kidney injury (MAKI) are not fully described. This study aims to determine the clinical, immune, and genetic correlates of risk to AKI in Zambian children admitted with malaria. In addition, we intend to assess a modified renal angina index (mRAI), kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and soluble urokinase receptor (suPAR), when done on the first day of admission, for the ability to predict AKI two days later (day 3) in children admitted with malaria. Methods This is an unmatched case-control study with a nested prospective observational study. A case-to-control ratio of 1:1 is used and 380 children with malaria and aged less than 16 years are being recruited from two hospitals in Zambia. Eligible children are recruited after obtaining written informed consent. Recruitment occurs during the malaria season and began on 6 th March 2024 and will continue until July 2025. AKI is defined using the 2012 KIDGO AKI creatinine criteria, and cases are defined as children admitted with malaria who develop AKI within 72 hours of admission, while controls are children admitted with malaria but with no AKI. Serum creatinine is collected on Day 1 within 24 hours of admission, on Day 3 and then again on discharge or day 7, whichever comes sooner. Baseline biomarker concentrations will be determined using the Luminex multiplex Elisa system or high-sensitivity ELISA. SPSS version 29 will be used for data analysis. Descriptive statistics and inferential statistical tests will be run as appropriate. A p ≤ 0.05 will be considered as significant. The sensitivity, specificity, and estimates of the area under the curve (AUC) for the renal angina score will be determined.

Acupuncture as an independent or adjuvant therapy to standard management for menopausal insomnia: A systematic review and meta-analysis

Objective This systematic review aimed to clarify if acupuncture is more effective for menopausal insomnia compared with sham acupuncture, standard care (sedative hypnotics and/or MHT) or waitlist control. Methods Seven literature databases were searched on April 30, 2024, to identify RCTs assessing the effectiveness of acupuncture. The methodological quality was assessed by the Cochrane Collaboration, and meta-analyses were conducted to calculate comparative effects using Rev Man software. Results 28 RCTs were analyzed. Six sham acupuncture-controlled RCTs were notable because of their high quality, and they showed that acupuncture significantly lowered PSQI scores, increased TST, sleep efficiency, and reduced WASO. The effect of acupuncture was maintained at a 4-week follow-up. Sixteen RCTs compared acupuncture with standard care, which showed acupuncture significantly reduced PSQI scores, KI scores, HAMD and HAMA scores. However, the subgroup analysis showed that there was no obviously difference between acupuncture and western medication in the treatment duration >8 weeks. Five RCTs assessed acupuncture combined with standard care and showed a favorable reduction in the PSQI score than standard care. One RCT showed that acupuncture significantly reduced PSQI and KI scores than a waitlist control. The GRADE assessment demonstrated that the level of evidence was very low to moderate, probably for the poor methodological quality and substantial heterogeneity among studies. Conclusion The results showed that acupuncture may play a positive role in patients with menopausal insomnia.