A comparison of methods to harmonize cortical thickness measurements across scanners and sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants\u27 demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LM

Genome sequencing of the sweetpotato whitefly Bemisia tabaci MED/Q

The sweetpotato whitefly Bemisia tabaci is a highly destructive agricultural and ornamental crop pest. It damages host plants through both phloem feeding and vectoring plant pathogens. Introductions of B. tabaci are difficult to quarantine and eradicate because of its high reproductive rates, broad host plant range, and insecticide resistance. A total of 791 Gb of raw DNA sequence from whole genome shotgun sequencing, and 13 BAC pooling libraries were generated by Illumina sequencing using different combinations of mate-pair and pair-end libraries. Assembly gave a final genome with a scaffold N50 of 437 kb, and a total length of 658 Mb. Annotation of repetitive elements and coding regions resulted in 265.0 Mb TEs (40.3%) and 20 786 protein-coding genes with putative gene family expansions, respectively. Phylogenetic analysis based on orthologs across 14 arthropod taxa suggested that MED/Q is clustered into a hemipteran clade containing A. pisum and is a sister lineage to a clade containing both R. prolixus and N. lugens. Genome completeness, as estimated using the CEGMA and Benchmarking Universal Single-Copy Orthologs pipelines, reached 96% and 79%. These MED/Q genomic resources lay a foundation for future ‘pan-genomic’ comparisons of invasive vs. noninvasive, invasive vs. invasive, and native vs. exotic Bemisia, which, in return, will open up new avenues of investigation into whitefly biology, evolution, and management

Long-term gastrointestinal outcomes of COVID-19

A comprehensive evaluation of the risks and 1-year burdens of gastrointestinal disorders in the post-acute phase of COVID-19 is needed but is not yet available. Here we use the US Department of Veterans Affairs national health care databases to build a cohort of 154,068 people with COVID-19, 5,638,795 contemporary controls, and 5,859,621 historical controls to estimate the risks and 1-year burdens of a set of pre-specified incident gastrointestinal outcomes. We show that beyond the first 30 days of infection, people with COVID-19 exhibited increased risks and 1-year burdens of incident gastrointestinal disorders spanning several disease categories including motility disorders, acid related disorders (dyspepsia, gastroesophageal reflux disease, peptic ulcer disease), functional intestinal disorders, acute pancreatitis, hepatic and biliary disease. The risks were evident in people who were not hospitalized during the acute phase of COVID-19 and increased in a graded fashion across the severity spectrum of the acute phase of COVID-19 (non-hospitalized, hospitalized, and admitted to intensive care). The risks were consistent in comparisons including the COVID-19 vs the contemporary control group and COVID-19 vs the historical control group as the referent category. Altogether, our results show that people with SARS-CoV-2 infection are at increased risk of gastrointestinal disorders in the post-acute phase of COVID-19. Post-covid care should involve attention to gastrointestinal health and disease

Long-term neurologic outcomes of COVID-19

The neurologic manifestations of acute COVID-19 are well characterized, but a comprehensive evaluation of postacute neurologic sequelae at 1 year has not been undertaken. Here we use the national healthcare databases of the US Department of Veterans Affairs to build a cohort of 154,068 individuals with COVID-19, 5,638,795 contemporary controls and 5,859,621 historical controls; we use inverse probability weighting to balance the cohorts, and estimate risks and burdens of incident neurologic disorders at 12 months following acute SARS-CoV-2 infection. Our results show that in the postacute phase of COVID-19, there was increased risk of an array of incident neurologic sequelae including ischemic and hemorrhagic stroke, cognition and memory disorders, peripheral nervous system disorders, episodic disorders (for example, migraine and seizures), extrapyramidal and movement disorders, mental health disorders, musculoskeletal disorders, sensory disorders, Guillain-Barré syndrome, and encephalitis or encephalopathy. We estimated that the hazard ratio of any neurologic sequela was 1.42 (95% confidence intervals 1.38, 1.47) and burden 70.69 (95% confidence intervals 63.54, 78.01) per 1,000 persons at 12 months. The risks and burdens were elevated even in people who did not require hospitalization during acute COVID-19. Limitations include a cohort comprising mostly White males. Taken together, our results provide evidence of increased risk of long-term neurologic disorders in people who had COVID-19

Risks of mental health outcomes in people with covid-19: Cohort study

OBJECTIVE: To estimate the risks of incident mental health disorders in survivors of the acute phase of covid-19. DESIGN: Cohort study. SETTING: US Department of Veterans Affairs. PARTICIPANTS: Cohort comprising 153 848 people who survived the first 30 days of SARS-CoV-2 infection, and two control groups: a contemporary group (n=5 637 840) with no evidence of SARS-CoV-2, and a historical control group (n=5 859 251) that predated the covid-19 pandemic. MAIN OUTCOMES MEASURES: Risks of prespecified incident mental health outcomes, calculated as hazard ratio and absolute risk difference per 1000 people at one year, with corresponding 95% confidence intervals. Predefined covariates and algorithmically selected high dimensional covariates were used to balance the covid-19 and control groups through inverse weighting. RESULTS: The covid-19 group showed an increased risk of incident anxiety disorders (hazard ratio 1.35 (95% confidence interval 1.30 to 1.39); risk difference 11.06 (95% confidence interval 9.64 to 12.53) per 1000 people at one year), depressive disorders (1.39 (1.34 to 1.43); 15.12 (13.38 to 16.91) per 1000 people at one year), stress and adjustment disorders (1.38 (1.34 to 1.43); 13.29 (11.71 to 14.92) per 1000 people at one year), and use of antidepressants (1.55 (1.50 to 1.60); 21.59 (19.63 to 23.60) per 1000 people at one year) and benzodiazepines (1.65 (1.58 to 1.72); 10.46 (9.37 to 11.61) per 1000 people at one year). The risk of incident opioid prescriptions also increased (1.76 (1.71 to 1.81); 35.90 (33.61 to 38.25) per 1000 people at one year), opioid use disorders (1.34 (1.21 to 1.48); 0.96 (0.59 to 1.37) per 1000 people at one year), and other (non-opioid) substance use disorders (1.20 (1.15 to 1.26); 4.34 (3.22 to 5.51) per 1000 people at one year). The covid-19 group also showed an increased risk of incident neurocognitive decline (1.80 (1.72 to 1.89); 10.75 (9.65 to 11.91) per 1000 people at one year) and sleep disorders (1.41 (1.38 to 1.45); 23.80 (21.65 to 26.00) per 1000 people at one year). The risk of any incident mental health diagnosis or prescription was increased (1.60 (1.55 to 1.66); 64.38 (58.90 to 70.01) per 1000 people at one year). The risks of examined outcomes were increased even among people who were not admitted to hospital and were highest among those who were admitted to hospital during the acute phase of covid-19. Results were consistent with those in the historical control group. The risk of incident mental health disorders was consistently higher in the covid-19 group in comparisons of people with covid-19 not admitted to hospital versus those not admitted to hospital for seasonal influenza, admitted to hospital with covid-19 versus admitted to hospital with seasonal influenza, and admitted to hospital with covid-19 versus admitted to hospital for any other cause. CONCLUSIONS: The findings suggest that people who survive the acute phase of covid-19 are at increased risk of an array of incident mental health disorders. Tackling mental health disorders among survivors of covid-19 should be a priority

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable

Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt

Long-term cardiovascular outcomes of COVID-19

The cardiovascular complications of acute coronavirus disease 2019 (COVID-19) are well described, but the post-acute cardiovascular manifestations of COVID-19 have not yet been comprehensively characterized. Here we used national healthcare databases from the US Department of Veterans Affairs to build a cohort of 153,760 individuals with COVID-19, as well as two sets of control cohorts with 5,637,647 (contemporary controls) and 5,859,411 (historical controls) individuals, to estimate risks and 1-year burdens of a set of pre-specified incident cardiovascular outcomes. We show that, beyond the first 30 d after infection, individuals with COVID-19 are at increased risk of incident cardiovascular disease spanning several categories, including cerebrovascular disorders, dysrhythmias, ischemic and non-ischemic heart disease, pericarditis, myocarditis, heart failure and thromboembolic disease. These risks and burdens were evident even among individuals who were not hospitalized during the acute phase of the infection and increased in a graded fashion according to the care setting during the acute phase (non-hospitalized, hospitalized and admitted to intensive care). Our results provide evidence that the risk and 1-year burden of cardiovascular disease in survivors of acute COVID-19 are substantial. Care pathways of those surviving the acute episode of COVID-19 should include attention to cardiovascular health and disease

Human Blood Identification in Crime Scene as a Forensic Clue

مقدمة: الدم هو أحد أكثر الأدلة شيوعًا التي يعثر  عليها في مسرح الجريمة. يتم تشخيص الدم البشري وفقا للسياق الاتي   أولاً موقع بقع الدم ، ثم إجراء الاختبارات الافتراضية ، ثم يتم عمل الاختبارات التاكيدية . تعتبر الاختبارات الجينية والاختبارات المصلية من الاختبارات المهمة في الطب الشرعي.. طرق العمل: تم جمع ثلاثين عينة دم في أنابيب EDTA ، تم جمع 25 منها من البشر وخمس عينات من الأغنام. استمرت هذه الدراسة خمسة أشهر من 23/3 إلى 22/8/2022. أجريت هذه الدراسة في جامعة بابل - كلية العلوم - قسم الأحياء. كان الهدف من هذه الدراسة هو تقييم طقم Hightop للكشف عن الدم البشري. تم تعريض الدم  لظروف جوية مختلفة . ثم فحص باستخدام هذه العدة  لتحديد قدرة المستضد على تحمل الظروف المختلفة وحساسية القياس لهذه العدة. النتائج: أظهرت  النتائج الإيجابية لبقع الدم التي تعرضت لظروف جوية مختلفة لمدة 30 يومًا باستثناء بقع الدم التي وضعت   على سطح أملس اظهرت  نتائج سلبية بعد 10 أيام من التعرض عكس التي كانت مدفونة بالتربة او البقع الدموية على الملابس التي تحملت الضروف الجوية مدة 30 يوما الاستنتاجات: من نتائج  تبين عدة  Hightop مناسبًا في مجال الطب الشرعي لتحديد دم الإنسان الذي يتعرض لظروف بيئية قاسية و كذلك لها القابلية لتميز الدم البشري عن الدم الحيواني و المستضد الهدف لها يتحمل الظروف الجوية.Background: Blood is one of the most common clues found at crime scenes. Human blood is diagnosed according to the following context: first, the location of the blood spots, then virtual tests, then confirmatory tests. Genetic testing and serological testing are important tests in forensic medicine.. Materials and Methods: Thirty blood samples were collected in EDTA tubes, of which 25 were collected from humans and five from sheep. This study lasted five months from 23/3 to 22/8/2022. This study was conducted at Babylon University - College of Science - Department of Biology. The aim of this study was to evaluate the Hightop kit for detection of human blood. The blood was exposed to different weather conditions. Then it was examined using this kit to determine the ability of the antigen to withstand different conditions and the sensitivity of the measurement for this kit. Results: The positive results of blood stains that were exposed to different weather conditions for 30 days, except for blood stains that were placed on a smooth surface, showed negative results after 10 days of exposure, as opposed to those that were buried in the soil or blood stains on clothes that endured weather conditions for 30 days.. Conclusion: The  Hightop kit is suitable in the field of forensic medicine to determine human blood that is exposed to harsh environmental conditions, as well as the ability to distinguish human blood from animal blood and its target antigen bears the weather conditions

Hubungan Kesepian dengan Kebutuhan Afiliasi pada Remaja Akhir di Media Sosial Facebook

Remaja memiliki tugas perkembangan untuk menjalin relasi dengan orang lain. Jika proses ini tidak berhasil maka remaja akan merasa terisolasi, dimana isolasi yang diterima oleh remaja menjadi salah satu penyebab terjadinya kesepian. Pengguna internet di Indonesia di dominasi oleh remaja dengan prosentase sebesar 80%. Remaja memanfaatkan internet salah satunya untuk mengatasi kesepian yang dialami dengan mencari pertemanan untuk memenuhi kebutuhan afiliasinya. Penelitian ini bertujuan untuk mengetahui hubungan kesepian dengan kebutuhan afiliasi pada remaja akhir di media sosial facebook. Pada penelitian ini merupakan penelitian korelasional menggunakan teknik sampling non probability sampling dengan sampel berjumlah 152 remaja akhir dengan kriteria usia 18-21 tahun yang menggunakan dan mempunyai facebook. Instrumen penelitian ini menggunakan UCLA Loneliness Scale Version 3 dan Skala Kebutuhan Afiliasi. Hasil uji hipotetis menunjukan terdapat hubungan yang negatif kesepian dengan kebutuhan afiliasi pada remaja akhir di media sosial facebook