Tag: pubmed

JBRA Assist Reprod. 2025 Feb 21. doi: 10.5935/1518-0557.20240095. Online ahead of print.

ABSTRACT

OBJECTIVE: Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder in women of reproductive age, being one of the main causes of infertility. Anti-Müllerian hormone (AMH) is an important marker of ovarian reserve and has been proposed as an alternative criterion for the diagnosis of PCOS. This study verifies whether AMH and body mass index (BMI) values are predictors of pregnancy in infertile women with PCOS undergoing artificial insemination (AI), a less invasive and painless technique of assisted reproductive technologies (ART).

METHODS: This retrospective observational study involved 220 women with PCOS who underwent AI between 2010 and 2022. Participants were categorized into three groups based on BMI and serum AMH levels. To categorize the three AMH classes, the 25th (4.08ng/mL) and 75th (8.99ng/mL) AMH percentiles were defined as cut-offs, and the words ‘low’, ‘middle’, and ‘high’ were utilized to define the groups.

RESULTS: There was a tendency towards a decrease in reproductive outcomes (number of inseminations with positive human-chorionic gonadotropin, number of live births, and number of term births) with an increase in the BMI value. All of these outcomes were also slightly higher in women with ‘middle’ AMH levels compared to women with ‘low’ and ‘high’ AMH. However, none of these results were statistically significant.

CONCLUSIONS: This study suggests BMI may be an important predictive factor for pregnancy and there appears to be a range of biological normality for AMH values, where ‘low’ and ‘high’ levels of this hormone could constitute a marker of poor reproductive prognosis, in women with PCOS undergoing AI.

PMID:39983029 | DOI:10.5935/1518-0557.20240095

Traffic Inj Prev. 2025 Feb 21:1-5. doi: 10.1080/15389588.2025.2456942. Online ahead of print.

ABSTRACT

OBJECTIVES: Alcohol and excessive speeding are both linked to elevated crash risk. Alcohol-related and speeding-related crashes are recorded and treated as distinct, with separate etiologies. Yet, speeding and alcohol use are interrelated. We speculate that speeding might account for some of the crash risk associated with drunk driving.

METHODS: Data from the Crash Investigation Sampling System were analyzed. Vehicle speeds, measured moments before crashes, were estimated from driver blood alcohol concentrations (BACs) for different levels of injury severity. We first applied a previously published formula to estimate the relative crash risk associated with speeds that occur at different BACs. Then, from the literature we obtained relative crash risk odds ratios associated with different BACs. Finally, for BACs of 0.08 g/dl and 0.16 g/dl, separately for serious injury and fatality crashes, we created ratios to estimate what portion of the alcohol-crash risk might be attributed to higher travel speeds.

RESULTS: A statistically significant BAC × Injury Severity interaction indicated that crash drivers with higher BACs drove faster than their sober counterparts, and that this was exacerbated for more serious injuries. Among drivers with fatal injuries, those with BACs of 0.16 g/dl were traveling over 10 mph faster than their sober counterparts. Finally, using this information, for drivers at different BACs, we compared the crash risk attributable to speed with the crash risk as a function of alcohol levels. Accordingly, we estimate that at 0.08 g/dl, higher speeds accounted for nearly 50% of the fatality crash risk attributed to alcohol, and 25% of the fatality crash risk at 0.16 g/dl. For serious injuries, estimates were 39% and 16%, respectively.

CONCLUSIONS: The literature on alcohol-related crashes widely attributes the increased crash risk to impaired driving skills, such as attention, coordination and reaction time. Our analysis suggests that speeding alone might account for some of this elevated risk. This has implications for understanding the etiology of alcohol-related crashes. We also suggest that speed control may be a viable means of reducing the harm from alcohol-related crashes.

PMID:39983026 | DOI:10.1080/15389588.2025.2456942

JMIR Public Health Surveill. 2025 Feb 21;11:e67050. doi: 10.2196/67050.

ABSTRACT

BACKGROUND: The increase in emerging and re-emerging infectious disease outbreaks underscores the need for robust early warning systems (EWSs) to guide mitigation and response measures. Administrative health care databases provide valuable epidemiological insights without imposing additional burdens on health services. However, these datasets are primarily collected for operational use, making data quality assessment essential to ensure an accurate interpretation of epidemiological analysis. This study focuses on the development and implementation of a data quality index (DQI) for surveillance integrated into an EWS for influenza-like illness (ILI) outbreaks using Brazil’s a nationwide Primary Health Care (PHC) dataset.

OBJECTIVE: We aimed to evaluate the impact of data completeness and timeliness on the performance of an EWS for ILI outbreaks and establish optimal thresholds for a suitable DQI, thereby improving the accuracy of outbreak detection and supporting public health surveillance.

METHODS: A composite DQI was established to measure the completeness and timeliness of PHC data from the Brazilian National Information System on Primary Health Care. Completeness was defined as the proportion of weeks within an 8-week rolling window with any register of encounters. Timeliness was calculated as the interval between the date of encounter and its corresponding registry in the information system. The backfilled PHC dataset served as the gold standard to evaluate the impact of varying data quality levels from the weekly updated real-time PHC dataset on the EWS for ILI outbreaks across 5570 Brazilian municipalities from October 10, 2023, to March 10, 2024.

RESULTS: During the study period, the backfilled dataset recorded 198,335,762 ILI-related encounters, averaging 8,623,294 encounters per week. The EWS detected a median of 4 (IQR 2-5) ILI outbreak warnings per municipality using the backfilled dataset. Using the real-time dataset, 12,538 (65%) warnings were concordant with the backfilled dataset. Our analysis revealed that 100% completeness yielded 76.7% concordant warnings, while 80% timeliness resulted in at least 50% concordant warnings. These thresholds were considered optimal for a suitable DQI. Restricting the analysis to municipalities with a suitable DQI increased concordant warnings to 80.4%. A median of 71% (IQR 54%-71.9%) of municipalities met the suitable DQI threshold weekly. Municipalities with ≥60% of weeks achieving a suitable DQI demonstrated the highest concordance between backfilled and real-time datasets, with those achieving ≥80% of weeks showing 82.3% concordance.

CONCLUSIONS: Our findings highlight the critical role of data quality in improving the EWS’ performance based on PHC data for detecting ILI outbreaks. The proposed framework for real-time DQI monitoring is a practical approach and can be adapted to other surveillance systems, providing insights for similar implementations. We demonstrate that optimal completeness and timeliness of data significantly impact the EWS’ ability to detect ILI outbreaks. Continuous monitoring and improvement of data quality should remain a priority to strengthen the reliability and effectiveness of surveillance systems.

PMID:39983017 | DOI:10.2196/67050

Genome Biol Evol. 2025 Feb 3;17(2):evae275. doi: 10.1093/gbe/evae275.

ABSTRACT

Evolution by natural selection occurs at its most basic through the change in frequencies of alleles; connecting those genomic targets to phenotypic selection is an important goal for evolutionary biology in the genomics era. The relative abundance of gene products expressed in a tissue can be considered a phenotype intermediate to the genes and genomic regulatory elements themselves and more traditionally measured macroscopic phenotypic traits such as flowering time, size, or growth. The high dimensionality, low sample size nature of transcriptomic sequence data is a double-edged sword, however, as it provides abundant information but makes traditional statistics difficult. Machine learning (ML) has many features which handle high-dimensional data well and is thus useful in genetic sequence applications. Here, we examined the association of fitness components with gene expression data in Ipomoea hederacea (Ivyleaf morning glory) grown under field conditions. We combine the results of two different ML approaches and find evidence that expression of photosynthesis-related genes is likely under selection. We also find that genes related to stress and light responses were overall important in predicting fitness. With this study, we demonstrate the utility of ML models for smaller samples and their potential application for understanding natural selection.

PMID:39983007 | DOI:10.1093/gbe/evae275

Sci Adv. 2025 Feb 21;11(8):eadq3173. doi: 10.1126/sciadv.adq3173. Epub 2025 Feb 21.

ABSTRACT

Intense rain can trigger flashfloods in Arabia. Torrential rains in 2024 sowed widespread chaos in the region. Sediment-loaded plumes discharged by flashfloods deposit onto the seabed. Burrowing animals disrupt these flood layers, erasing the paleorainfall record. Fortuitously, we discovered an anoxic deep-sea brine pool sited close enough to shore to chronicle floods, yet be otherwise undisturbed by animals. Cores retrieved from the pool delivered a 1600-year rainfall record. We merge these core-layer histories with modern rainfall statistics, satellite observations, and simulations to deliver a high-resolution quantitative Late Holocene hydroclimate record for Arabia. We find that the modern era is 2.5 times drier than the last 1.6 thousand years. The Little Ice Age stands out as particularly wet. That period experienced a fivefold increase in rainfall intensity compared to today. Though hyperarid now, the flood layers demonstrate that climate shifts can generate weather conditions unwitnessed in the modern era. Such long-range insight is crucial for framing uncertainties surrounding future hydroclimate forecasts.

PMID:39982992 | DOI:10.1126/sciadv.adq3173

PLOS Glob Public Health. 2025 Feb 21;5(2):e0003956. doi: 10.1371/journal.pgph.0003956. eCollection 2025.

ABSTRACT

The African continent has some of the world’s lowest COVID-19 vaccination rates. While the limited availability of vaccines is a contributing factor, COVID-19 vaccine hesitancy among healthcare providers (HCP) is another factor that could adversely affect efforts to control infections on the continent. We sought to understand the extent of COVID-19 vaccine hesitancy among HCP, and its contributing factors in Africa. We evaluated COVID-19 vaccine hesitancy among 1,499 HCP enrolled in a cross-sectional study conducted as a telephone survey in Burkina Faso, Ethiopia, Nigeria, Tanzania, and Ghana between July to December of 2021. We defined COVID-19 vaccine hesitancy among HCP as self-reported responses of definitely not, maybe, unsure, or undecided on whether to get the COVID-19 vaccine, compared to definitely getting the vaccine. We used log-binomial or modified Poisson regression models to evaluate factors influencing vaccine hesitancy among HCP. Approximately 65.6% of the HCP interviewed were nurses and the mean age (±SD) of participants was 35.8 (±9.7) years. At least 67% of the HCP reported being vaccinated. COVID-19 vaccine hesitancy affected 45.7% of the HCP in Burkina Faso, 25.7% in Tanzania, 9.8% in Ethiopia, 9% in Ghana and 8.1% in Nigeria. Among unvaccinated HCP reasons for low vaccine uptake included concern about vaccine effectiveness, side effects, and fear of receiving experimental and unsafe vaccines. HCP reporting that COVID-19 vaccines are very effective (RR: 0.21, 95% CI: 0.08, 0.55), and older HCP (45 or older vs.20-29 years, RR: 0.65, 95% CI: 0.44, 0.95) were less likely to be vaccine-hesitant. Nurses were more likely to be vaccine-hesitant (RR 1.38, 95% CI: 1.01, 1.89) than doctors. Information asymmetry among HCP, beliefs about vaccine effectiveness, and the endorsement of vaccines by public health institutions may be important. Efforts to address hesitancy should consider information and knowledge gaps among different cadres of HCP alongside efforts to increase vaccine supply.

PMID:39982973 | DOI:10.1371/journal.pgph.0003956

Health Soc Care Deliv Res. 2025 Feb;13(3):1-51. doi: 10.3310/HYRT9622.

ABSTRACT

BACKGROUND: The increasing size of the ageing English prison population means that non-communicable diseases such as cancer are being more commonly diagnosed in this setting. Little research has so far considered the incidence of cancer in the English prison population, the treatment patients receive when they are diagnosed in a prison setting, their care costs and outcomes or their experiences of care compared with those of people diagnosed in the general population. This is the first mixed-methods study that has been designed to investigate these issues in order to inform recommendations for cancer practice, policy and research in English prisons.

METHODS: We compared cancer diagnoses made in prison between 1998 and 2017 with those made in the general population using a cohort comparison. We then used a cohort comparison approach to patients’ treatment, survival, care experiences and costs of care between 2012 and 2017. We also conducted qualitative interviews with 24 patients diagnosed or treated in prison, and 6 custodial staff, 16 prison health professionals and 9 cancer professionals. Findings were presented to senior prison and cancer stakeholders at a Policy Lab event to agree priority recommendations.

RESULTS: By 2017 cancer incidence in prison had increased from lower levels than in the general population to similar levels. Men in prison developed similar cancers to men outside, while women in prison were more likely than women outside to be diagnosed with preinvasive cervical cancer. In the comparative cohort study patients diagnosed in prison were less likely to undergo curative treatment, particularly surgery, and had a small but significantly increased risk of death. They also had fewer but slightly longer emergency hospital admissions, lower outpatient costs and fewer planned inpatient stays. While secondary care costs were lower for patients in prison, when security escorts costs were added, emergency care and total costs were higher. Control and choice, communication, and care and custody emerged as key issues from the qualitative interviews. People in prison followed a similar diagnostic pathway to those in the general population but experienced barriers arising from lower health literacy, a complex process for booking general practitioner appointments, communication issues between prison staff, surgical, radiotherapy and oncology clinicians and a lack of involvement of their family and friends in their care. These issues were reflected in patient experience survey results routinely collected as part of the annual National Cancer Patient Experience Survey. The four priorities developed and agreed at the Policy Lab event were giving clinical teams a better understanding of the prison system, co-ordinating and promoting national cancer screening programmes, developing ‘health champions’ in prison and raising health literacy and awareness of cancer symptoms among people in prison.

LIMITATIONS: We could not identify patients who had been diagnosed with cancer before entering prison.

CONCLUSION: Healthcare practices and policies both within prisons and between prisons and NHS hospitals need to be improved in a range of ways if the cancer care received by people in prison is to match that received by the general population.

FUTURE WORK: Evaluating new policy priorities.

FUNDING: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/52/53) and is published in full in Health and Social Care Delivery Research; Vol. 13, No. 3. See the NIHR Funding and Awards website for further award information.

PMID:39982760 | DOI:10.3310/HYRT9622

J Chem Inf Model. 2025 Feb 21. doi: 10.1021/acs.jcim.4c02095. Online ahead of print.

ABSTRACT

To predict the partial molar excess enthalpy, entropy at infinite dilution, and phase equilibria, the availability of an infinite dilution activity coefficient is vital. The “quantitative structure-activity/property relationship” (QSAR/QSPR) approach has been used for the prediction of infinite dilution activity coefficient of water in ionic liquids using an extensive data set. The data set comprised 380 data points including 68 unique ILs at a wide range of temperatures, which is more extensive than previously published data sets. Moreover, new predictive QSAR/QSPR models including novel molecular descriptors, called “COSMO-RS descriptors”, have been developed. Using two different techniques of external validation, the data set was divided to the training set for the development of models and to the validation set for external validation. Unlike former available models, internal validation using leave one/multi out-cross validations (LOO-CV/LMO-CV) and Y-scrambling methods were performed on the models using statistical parameters for further assessment. According to the obtained results of statistical parameters (R² = 0.99 and Q²_LOO-CV = 0.99), the predictive capability of the developed QSPR model was excellent for training set. Regarding the external validation, other statistical parameters such as AAD = 0.283 and AARD % = 30 were also satisfactory for the validation set. While the values of γ_H2O^∞ increase or decrease with increasing temperature, the QSAR/QSPR models based on the van’t Hoff equation takes into account the negative and positive effects of temperature on the γ_H2O^∞ in ILs well, depending on the nature of ILs. It was also shown that γ_H2O^∞ in some new ILs which had not been experimentally studied before can be predicted using the QSPR model.

PMID:39982758 | DOI:10.1021/acs.jcim.4c02095

Foodborne Pathog Dis. 2025 Feb 21. doi: 10.1089/fpd.2024.0175. Online ahead of print.

ABSTRACT

Staphylococcus aureus is a foodborne zoonotic pathogen that threatens food safety and public health. However, few people have conducted long-term and systematic studies on S. aureus contamination in food in Yantai City. To investigate the contamination situation of S. aureus in food and improve the ability of early warning and control of foodborne diseases, a total of 2384 samples from 17 categories were collected from 13 monitoring points in Yantai City, from 2010 to 2023. Forty-four samples were positively detected for S. aureus, with a detection rate of 1.85% (44/2384). The detection rate of S. aureus was highest in Zhifu District (4.12%), followed by Penglai District (2.45%), Zhaoyuan District (2.37%), Kaifa District (2.19%), and Longkou District (1.98%). Positive detection rates were higher in frozen rice and flour products at 8.82% (6/68), quick-frozen dishes at 5.56% (1/18), aquatic products at 4.05% (3/74), and meat and meat products at 3.55% (27/760). Positive detection rates in samples from the first, second, third, and fourth quarters were 0% (0/44), 2.21% (20/906), 2.13% (22/1033), and 0.50% (2/401), respectively. Positive detection rates in bulk and prepackaged samples were 2.33% (36/1546) and 0.95% (8/838), respectively, with statistically significant differences (χ² = 5.66, p < 0.05). Positive detection rates were significantly different for samples collected from different sampling stages, of which at production and processing stages was 7.78% (20/257), catering stages 1.38% (10/727), and distribution stages 1% (14/1400) (χ² = 56.41, p < 0.05). Frozen rice and flour products, quick-frozen dishes, aquatic products, and meat and meat products are the main food products contaminated with S. aureus, and the resulting secondary contamination is a hidden danger for the occurrence of foodborne diseases, which should be given sufficient attention.

PMID:39982751 | DOI:10.1089/fpd.2024.0175

Proc Natl Acad Sci U S A. 2025 Feb 25;122(8):e2401868122. doi: 10.1073/pnas.2401868122. Epub 2025 Feb 21.

ABSTRACT

Random packings of stiff rods are self-supporting mechanical structures stabilized by long-range interactions induced by contacts. To understand the geometrical and topological complexity of the packings, we first deploy X-ray computerized tomography to unveil the structure of the packing. This allows us to directly visualize the spatial variations in density, orientational order, and the entanglement, a mesoscopic field that we define in terms of a local average crossing number, a measure of the topological complexity of the packing. We find that increasing the aspect ratio of the constituent rods in a packing leads to a proliferation of regions of strong entanglement that eventually percolate through the system and correlated with a sharp transition in the mechanical stability of the packing. To corroborate our experimental findings, we use numerical simulations of contacting elastic rods and characterize their stability to static and dynamic loadings. Our experiments and computations lead us to an entanglement phase diagram which we also populate using published experimental data from pneumatically tangled filaments, worm blobs, and bird nests along with additional numerical simulations using these datasets. Together, these show the regimes associated with mechanically stable entanglement as a function of the statistics of the packings and loading, with lessons for a range of systems from reconfigurable architectures and textiles to active morphable filamentous assemblies.

PMID:39982741 | DOI:10.1073/pnas.2401868122