Trichloroethylene: Johnson et al.’s Response

The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

The Need for Large Clinical Studies in Perioperative Medicine

BackgroundDiabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycaemia, affecting various metabolic processes and leading to multiple complications, particularly in wound healing. This study aims to evaluate the impact of diabetes on the healing of extraction sockets in non-diabetic, prediabetic, and type 2 diabetic patients in Saudi Arabia.MethodologyA prospective observational study was conducted with 72 participants who were divided equally (n = 24 for each group) into three groups, viz. non-diabetic, prediabetic, and diabetic groups based on glycated hemoglobin (HbA1c) and random blood glucose levels. Tooth extractions were performed by an experienced maxillofacial surgeon. Healing outcomes were assessed by measuring extraction socket size, post-operative pain, discharge, swelling, infection, erythema, dry socket occurrence, and analgesic consumption over one week. Initially descriptive statistics were calculated and one way Analysis of Variance (ANOVA) test was done to compare the reduction in socket size between groups. The level of statistical significance was set at P ≤ 0.05.ResultsOut of 275 screened participants, 104 provided informed consent, and 72 completed the study. Significant differences were found in socket size reduction, with non-diabetic patients showing a 62.5% reduction, prediabetic 56.4%, and diabetic 48.6% (p < 0.001). Diabetic patients experienced more post-operative pain (p = 0.039) and a higher incidence of complications such as swelling, infection, and discharge, although not statistically significant (p = 0.141).ConclusionDiabetes significantly affects post-operative healing in dental extractions, leading to less socket size reduction, higher pain levels, and increased complications. These findings underscore the necessity for specialized post-operative care for diabetic patients, including stringent infection control and pain management strategies. Further research with larger sample sizes and extended follow-up periods is recommended to better understand the long-term impacts of diabetes on oral health.

Very high strain-rate response of a NiTi shape-memory alloy

Task Force IV: Scientific responsibility and integrity in medical research

Amaç: Özgül Öğrenme Güçlüğü görülen ilköğretim çağındaki öğrencilerin akran ilişkilerini ve özgül öğrenme güçlüğünün alt tiplerinin akran ilişkilerindeki farklılıklarını incelemek amacıyla bu çalışma gerçekleştirilmiştir. Gereç ve Yöntem: Çalışmaya 8-14 yaş aralığında 89 özgül öğrenme güçlüğü görülen öğrenci ve 95 sağlıklı öğrenci dahil edilmiştir. Öğrencilerin akran ilişkilerini incelemek için Akran İlişkileri Ölçeği kullanılmıştır. İstatistiksel anlamlılık düzeyi p&amp;lt;0,05 olarak kabul edilmiştir. Sonuçlar: Bağlılık, Güven ve Özdeşim, Kendini Açma ve Sadakat alt alanlarını içeren Akran İlişkileri Ölçeği’nde araştırma ve kontrol gurubu karşılaştırıldığında özgül öğrenme güçlüğü görülen öğrencilerin akran ilişkilerinin sağlıklı öğrencilere göre istatistiksel açıdan anlamlı olarak daha zayıf olduğu saptanmıştır (p&amp;lt;0,05). Öğrenme güçlüğü alt alanlarında, disleksi görülen öğrencilerin akran ilişkilerinin ise disgrafili ve diskalkulili öğrencilere göre istatistiksel açıdan anlamlı olarak daha zayıf olduğu tespit edilmiştir (p&amp;lt;0,05). Tartışma: Çalışmanın sonuçlarına göre ilköğretim çağındaki öğrencilerde özgül öğrenme güçlüğü görülmesi akran ilişkilerini olumsuz yönde etkilemektedir. Bu çalışmanın ilköğretim çağı öğrencilerinin akran ilişkilerinin zayıf olduğunu göstermesi, ileride ergoterapistler tarafından hazırlanacak müdahale programlarında akran ilişkilerinin dikkate alınması gerektiğini göstermektedir. Ancak, bu konuda daha büyük örneklem gruplarının yer aldığı çalışmalara ihtiyaç vardır.

The greater part of Legendre & Dutilleul (1991)'s comments are devoted to illustrating the problems involved in estimating confidence intervals for small samples of autocorrelated data. I do not disagree; rather that is why I wrote an article (Boyle, 1991) proposing an alternative approach. As Legendre & Dutilleul thoroughly demonstrate, the problems are greatly reduced if sample size is large. So rather than estimate variance from a small sample, I propose estimating it from a large sample of similar data, and assuming this figure to be valid for the smaller sample. There are obvious dangers with this approach, but it does permit realistic estimation of confidence interval when sample size is very small. The direct approach advocated by Legendre & Dutilleul results in greatly exaggerated confidence intervals for such samples because of the uncertainty about the variance estimate. In considering which transformation should be used, I looked only at the two commonly used forms (log-transformation and no transformation). I do not disagree with Legendre & Dutilleul's contention that for any specific study, a normalizing function which fits better could be found. Demonstrating that such a transformation is more appropriate would be harder. In reply to some specific objections by Legendre & Dutilleul: I use chi-square and K-S distance only to compare degree of fit; I did not test for normality hence no reference to tables. I stated that weekly sampled data showed significant autocorrelation; I did not claim that autocorrelation coefficients of 0.40 ad 0.52 are negligible. I pointed out that because of the relatively large sample sizes, the consequences even of the statistically significant autocorrelations were minor; Legendre & Dutilleul's calculations support this. The monthly sampled data have smaller autocorrelations and less bias. I used z instead of t in the confidence interval equation because a population parameter is assumed. Legendre & Dutilleul's inappropriate use of t in this equation results in a gross overestimation of the confidence interval.

97/05132 Toxic substances from coal combustion: laboratory studies: Senior, C. L. et al. Proc. Annu. Int. Pittsburgh Coal Conf., 1996, 13, (2), 1344–1349

Support vector machines (SVM) are attractive for the classification of remotely sensed data with some claims that the method is insensitive to the dimensionality of the data and, therefore, does not require a dimensionality-reduction analysis in preprocessing. Here, a series of classification analyses with two hyperspectral sensor data sets reveals that the accuracy of a classification by an SVM does vary as a function of the number of features used. Critically, it is shown that the accuracy of a classification may decline significantly (at 0.05 level of statistical significance) with the addition of features, particularly if a small training sample is used. This highlights a dependence of the accuracy of classification by an SVM on the dimensionality of the data and, therefore, the potential value of undertaking a feature-selection analysis prior to classification. Additionally, it is demonstrated that, even when a large training sample is available, feature selection may still be useful. For example, the accuracy derived from the use of a small number of features may be noninferior (at 0.05 level of significance) to that derived from the use of a larger feature set providing potential advantages in relation to issues such as data storage and computational processing costs. Feature selection may, therefore, be a valuable analysis to include in preprocessing operations for classification by an SVM.

Carol Brayne: studying dementia in the brain and in populations

Rethinking potentially inappropriate medication use in nursing homes within the Chinese population

Introduction Patients with confirmed venous thromboembolism (VTE) are often managed with oral anticoagulation. There have been reports of prescribing, particularly dose-related, administration, and dispensing errors associated with direct oral anticoagulants (DOACs), with error rate ranging from 5.3% to 37.3% (1). The evidence on the appropriate prescribing of DOACs post completion of VTE treatment period is lacking as most studies review prescribing errors in patients with atrial fibrillation. Aim To evaluate prescribing practice of DOACs for patients with confirmed VTE following a discharge from a large teaching hospitals Trust in the North of England. Methods This retrospective audit covered a period from 1st April 2020 to 31st March 2021. Electronic medical records of adult patients with confirmed VTE, admitted to a large Teaching hospitals Trust, and newly prescribed DOAC on discharge were included. Extracted pseudo-anonymised data was analysed descriptively using Microsoft Excel. Creatinine clearance (CrCl) was calculated using the Cockcroft-Gault equation for patients with recorded weight. Results The initial list of patients diagnosed with VTE included 1119 entries, which after cleansing was reduced to 502 unique patients meeting the eligibility criteria. The mean age (±standard deviation) was 66±16 years (range 20-99) and 52% (n=260) were male. Documented diagnosis included PE (85%, n=428), DVT (10%, n=49), DVT with PE (4%, n=21), and no clear diagnosis (&amp;lt;1%, n=4). The weight was recorded and CrCl was possible to calculate for 67% (n=334). Out of these, 98% (n=328) had appropriate doses for their level of renal function. Treatment duration was clearly documented for 81% (n=406) patients and 22% (n=108) were planned for a long-term prophylaxis on discharge. Out of all patients, 37% (n=187) had treatment stopped after completing the treatment period (3 or 6 months), 23% (n=113) continued treatment dose following completion of treatment period without other comorbidity warranting the treatment dose to continue, 21% (n=104) were changed to recommended prophylaxis dose, 15% (n=76) were excluded due to missing data or dying within six months of admission, and 4% (n=22) had atrial fibrillation and continued on an appropriate dose. Conclusion Our study highlighted that potentially inappropriate treatment dose use after completing the planned treatment period (3 or 6 months) was prevalent in nearly a quarter of patients. The potentially unnecessary continuation of treatment dose of DOAC can increase the risk of bleeding events, add to medicine expenditure costs, and contribute to waste in the healthcare system. Education of prescribers in primary and secondary care on VTE treatment and prophylaxis management, harnessing the pharmacist’s role in primary and secondary care, and including explicit dosing and duration of DOAC use in hospital discharge letters could improve patient safety and reduce non-recommended DOAC use. The main strengths of the study included the use of patients’ routine data and a relatively large sample size. The data generalisability and analysis were limited by the accuracy of the electronic patients’ care records and using data from one NHS Trust.

On Issues of Validity and Especially on the Misery of Convergent Validity

Background: Antibiotic resistance poses a significant global health challenge, often exacerbated by inappropriate antibiotic use and poor patient adherence to prescribed regimens. Understanding the factors influencing antibiotic knowledge and adherence among outpatients is critical to improving treatment outcomes and mitigating resistance development. This study aimed to analyze the relationship between patients’ knowledge and their adherence to antibiotic use at Puskesmas Gadung Kab. Buol Methods: A cross-sectional descriptive study was conducted involving 42 outpatient respondents between January and February 2024. Data on sociodemographic characteristics, knowledge of antibiotics, and adherence behavior were collected using structured questionnaires. Descriptive statistics and Spearman’s rho correlation test were applied to analyze the data Result: The findings revealed that a substantial proportion of respondents demonstrated moderate to good knowledge about antibiotics, with a notable association between higher knowledge levels and better adherence to antibiotic regimens. The majority of participants complied with prescribed antibiotic use, particularly those with sufficient understanding of antibiotic resistance and appropriate usage. The study also identified that demographic factors such as age, gender, education, and occupation influenced both knowledge and adherence behaviors. The statistical analysis confirmed a significant positive correlation between knowledge and adherence, underscoring the importance of patient education Conclusion: In conclusion, enhancing patients’ knowledge about antibiotics is essential to improving adherence and combating antibiotic resistance. Healthcare providers should prioritize continuous educational interventions and counseling to reinforce correct antibiotic use among outpatients. Future research with larger samples and diverse settings is recommended to generalize the findings and explore additional factors influencing adherence.

Self-medication is usually used by the community to treat minor illnesses, especially during the COVID-19 pandemic, such as fever, dizziness, cough, flu, pain, ulcers, diarrhea, and others. Most self-medication leads to inappropriate drug use. Self-medicated knowledge is the key to prevent unwanted events, one of the example is by providing education about traditional medicine for self-medication. In addition, making a plantation pharmacy is also a solution to make it easier for people to obtain traditional medicines. The method of implementing this community service activity is to provide counseling on using traditional medicine for self-medication and planting pharmacy plantation. An overview of knowledge of traditional medicine for self-medication in the community in the era of the COVID-19 pandemic is descriptive research by looking at primary data (from questionnaires) taken in a cross-sectional manner. Based on the data obtained, it can be concluded that most people have a sufficient level of knowledge (59.09%). The community has a positive attitude towards traditional medicine self-medication as evidenced by the number of respondents who answered agree from these statements. Therefore, research can be carried out as well as counseling, education and health promotion to society with a larger sample.