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Background Appropriate storage and transport conditions are crucial for ensuring bacterial viability within biological specimens. Nasopharyngeal carriage studies are common for Streptococcus pneumoniae . However, storing or transporting specimens at ultra-low temperatures as recommended by the World Health Organization is not possible in all settings. Here, we assess the impact of alternative storage conditions on pneumococcal viability and density using laboratory-prepared samples. Methods Flocked swabs were inoculated with low (n = 395) or medium (n = 395) loads of single pneumococcal isolates. Twenty different serotypes were tested. Swabs were stored in skim milk, tryptone, glucose and glycerol (STGG) medium at -80°C (gold standard), -20°C and 4°C, and in silica desiccant packets (SDPs) at 4°C and 30°C. Viable counts were performed at inoculation (baseline), and 2, 7, 14, 21 and 28 days post storage. A subset of samples from baseline and 28 days post storage were assessed for pneumococcal detection and density using culture-independent, molecular methods. Results Using culture-based methods, pneumococcal recovery was high (≥ 80%) up to 28 days when samples were stored at -20°C and − 80°C in STGG. Samples stored at 4°C in both STGG and SDPs had inconsistent recovery (< 80%) by 28 days, and samples stored at 30°C in SDPs had very low recovery (< 15%) at all timepoints. Overall, when compared by culture to the inoculum load, density was substantially reduced when alternative storage conditions were used. When density was assessed by lytA qPCR, pneumococci could be detected for most (99%) samples in select storage conditions. Conclusions Improper storage of specimens may lead to underestimations of pneumococcal prevalence and density, especially when culture-based methods are used. Given this, study outcomes and methods of testing should be considered when determining feasible transport and storage conditions. We identified alternative storage conditions to the gold standard that could enable studies in remote or complex settings.
BACKGROUND Ciprofloxacin resistant Klebsiella pneumoniae is common or emerging in many geographies, and knowledge of local resistance rates is important for empirical therapy. Whilst there are known K. pneumoniae ciprofloxacin resistance determinants, there is a lack of systematic data on the effect of determinants, alone and in combination, and there are no publicly accessible tools for predicting resistance from whole genome sequence data. METHODS The KlebNET-GSP AMR Genotype-Phenotype Group aggregated a matched genotype-phenotype dataset of n=12,167 K. pneumoniae species complex ( Kp SC) isolates from 27 countries between 2001-2021. We developed a rules-based classifier to predict ciprofloxacin resistance by categorizing the number of quinolone resistance determining regions mutations in gyrA and parC , the number of plasmid-mediated quinolone resistance genes, and the presence/absence of aac(6ʹ)-Ib-cr (which can acetylate ciprofloxacin). Predictive performance was assessed using the discovery dataset, for which we re-phenotyped discrepant isolates; and validated using externally contributed datasets (n=7,030 Kp SC isolates). RESULTS The rules-based classifier predicted R vs S/I with categorical agreement, sensitivity, and specificity >96%, and major/very major error rates <4%. Performance was similar across diverse Kp SC sources (human, animal, other), species, and intra-species lineages. External validation of the classifier yielded overall 93.12% categorical agreement [95% confidence interval (CI), 92.50-93.74%], 8.65% major errors [95% CI, 7.34-9.97%], and 6.20% very major errors [95% CI, 5.51-6.90%]. We implemented the classifier in Kleborate, a command-line tool that is integrated into the Pathogenwatch web platform. Using this to assess the global distribution of ciprofloxacin resistance determinants in Kp SC genomes available in Pathogenwatch (n=31,319, from 109 countries between years 2000-2023), we observed a significant positive association between national quinolone consumption rates and predicted ciprofloxacin resistance (R2=0.20, p=0.004). CONCLUSIONS Ciprofloxacin resistance phenotypes can be reasonably predicted from genotypes, which is sufficient for informing surveillance. However, unexplained resistance remains and accuracy is insufficient for clinical applications. We demonstrate the value of aggregating genotype-phenotype data to explore resistance mechanisms and develop predictors, but highlight complexities in combining phenotype data from different assays and standards. ### Competing Interest Statement The authors have declared no competing interest. Bill & Melinda Gates Foundation, INV025280, INV077266 Wellcome Trust, 226432/Z/22/Z European Union‘s Horizon 2020 Research and Innovation Programme, 773830 Trond Mohn Foundation, TMF2019TMT03 SARA project (Surveillance of Antimicrobial Resistance in Africa, through a grant from the French Ministry of Europe and Foreign Affairs within the Fonds de solidarité pour les projets innovants (FSPI) Academy of Medical Sciences Health Foundation UK Vietnam MRC Newton Fund, MR/N029399/1 RG83380 National Institute for Health and Care Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, NIHR207397
The Asian tiger mosquito, Aedes albopictus, is currently the most widespread invasive mosquito species in the world. It poses a significant threat to human health, as it is a vector for several arboviruses. We used a SNP chip to genotype 748 Ae. albopictus mosquitoes from 41 localities across Europe, 28 localities in the native range in Asia, and 4 in the Americas. Using multiple algorithms, we examined population genetic structure and differentiation within Europe and across our global dataset to gain insight into the origin of the invasive European populations. We also compared results from our SNP data to those obtained using genotypes from 11 microsatellite loci (N = 637 mosquitoes from 25 European localities) to explore how sampling effort and the type of genetic marker used may influence conclusions about Ae. albopictus population structure. While some analyses detected more than 20 clusters worldwide, we found mosquitoes could be grouped into 7 distinct genetic clusters, with most European populations originating in East Asia (Japan or China). Interestingly, some populations in Eastern Europe did not share genetic ancestry with any populations from the native range or Americas, indicating that these populations originated from areas not sampled in this study. The SNP and microsatellite datasets found similar patterns of genetic differentiation in Europe, but the microsatellite dataset could not detect the more subtle genetic structure revealed using SNPs. Overall, data from the SNP chip offered a higher resolution for detecting the genetic structure and the potential origins of invasions.
Purpose This study aims to survey depression prevalence and identify key influencing factors. Design/methodology/approach In 2022, 2.304 students completed an online questionnaire over six months. The survey included the PHQ-9 assessment tool, social media addiction and COVID-19-related factors. One-way ANOVA and post hoc tests analyzed correlations between socio-demographic factors, depression levels and social media addiction. Findings The study found a severe depression rate of 34%, with freshmen and females particularly affected. Health field students had the highest severe depression rate (52%). Social media addiction was significant among freshmen (29%) and health students (54.4%). Factors such as family infections, study pressure, studying in public places and social media addiction were strongly correlated with increased depression levels. Conversely, spending time with friends and studying at home were protective. Social media addiction notably heightens depression risk. Among those affected, 33.3% experienced severe depression, 18.89% moderately severe, 14.44% moderate and 21.1% mild depression. The study highlights the impact of family COVID-19 infections, academic pressures, studying environments, hometowns, social media usage and limited social interactions on depression. However, causal relationships could not be established due to the cross-sectional design. Research limitations/implications This study had some limitations. As a cross-sectional study, causal relationships between variables could not be determined. The smaller sample size from the central and northern regions may not accurately represent those areas. Therefore, this paper did not conduct a comparison between regions in this study. While this study revealed differences in depression ratios among disciplines, this paper lacked sufficient data for causal analysis. Furthermore, the depression levels among health subjects were higher compared to those of other disciplines, possibly due to a higher response rate. However, future studies may delve deeper into these causes across various disciplines, potentially mitigating their impact factors. Originality/value The results revealed that individuals with family members infected by COVID-19 experienced higher levels of depression. Moreover, experiencing pressure in the study and studying in public places were linked to an increased level of depression, while spending more time communicating with friends was associated with lower levels of depression. Notably, social media addiction was found to be a significant factor contributing to elevated levels of depression. These findings highlight the importance of targeted interventions and support systems to address these factors and promote mental well-being and the overall quality of life for university students. Universities need to provide support services for students, including mental health awareness programs in study spaces, increased community activities, dedicated study areas and access to mental health support hotlines. Further research is needed to develop deeper into the underlying mechanism and develop evidence-based strategies for the prevention, early detection and treatment of depression in this specific population.
Opioids remain indispensable for pain management but their use is limited by significant side effects, including respiratory depression, constipation, tolerance, addiction, and immunosuppression. Although much is known about their mechanism of action, the effects of acute opioid exposure on transcriptional responses have not yet been fully characterized.We performed a transcriptomic analysis of differentiated neuron-like SH-SY5Y cells exposed to five opioid ligands, namely, morphine, TRV130, metamorphine, β-endorphin, and naloxone. After incubation for 15 minutes, the cells were harvested and processed for RNA sequencing via the Illumina NovaSeq 6000 platform. Differential gene expression analysis was performed with DESeq2, and pathway enrichment was conducted via GO, KEGG and Reactome.Individual comparisons between each opioid-treated group and the control group revealed no statistically significant transcriptional changes. However, when all the agonist-treated samples were pooled and compared with the control samples, we identified several significantly downregulated genes (adjusted p < 0.05). Specifically, we observed alterations in the expression of the genes CACNA1F, RASAL1, GARIN4, and TRIM56, which are involved in calcium signaling, synaptic plasticity, the immune response, and reproductive function. CACNA1F downregulation may affect neuronal excitability and retinal signaling; RASAL1 suppression could impact synaptic maturation and memory; GARIN4 is associated with sperm morphology; and TRIM56 downregulation has an immunomodulatory effect, all of which aligns with known opioid-induced side effects.Our findings demonstrate that even short-term opioid exposure can initiate subtle but functionally relevant transcriptional changes. These early responses highlight the potential of transcriptomic profiling to uncover the molecular mechanisms underlying opioid pharmacodynamics and side effects. This approach offers deeper insights into opioid action and supports the development of safer analgesics with fewer systemic adverse effects.
