Peramalan Tingkat Kematian Indonesia Akibat Covid-19 Menggunakan Model Arima

Penelitian ini bertujuan untuk mendapatkan informasi penting dalam merencanakan penanggulangan pandemi, salah satunya adalah informasi terkait kematian akibat virus ini. Studi ini mencoba memprediksi angka kematian akibat virus corona di Indonesia. Studi ini menggunakan data kematian Indonesia akibat virus corona dari Maret 2020 hingga Desember 2020 untuk membentuk model ARIMA. Kemudian menggunakan model ARIMA untuk memprediksi angka kematian akibat virus corona hingga Januari 2021. Gunakan MAE untuk mengevaluasi keakuratan hasil prediksi, dan hasil prediksi MAE adalah 0,0007. Diharapkan hasil prediksi ini dapat digunakan pemerintah untuk merumuskan rencana pandemi virus corona

Analisis Spasial Tingkat Kerusakan Kawasan Suaka Margasatwa Padang Sugihan Sumatera Selatan

Kawasan Suaka Margasatwa Padang Sugihan merupakan habitat penting bagi gajah sumatera. Namun demikian kondisinya saat ini terus mengalami tekanan terutama akibat kebakaran, pembalakan liar, dan penguasan lahan oleh oknum masyarakat. Penelitian ini bertujuan untuk melakukan pemetaan tingkat kerusakan Suaka Margasatwa Padang Sugihan dan mengidentifikasi penyebab kerusakan sebagai bagian kegiatan perencanaan pemulihan ekosistem. Analisis kerusakan kawasan menggunakan sistem informasi geografis dengan metode skoring tumpeng susun dan pembobotan terhadap parameter-parameter yang berpengaruh terhadap kerusakan kawasan, yaitu tutupan lahan, frekuensi kebakaran, areal berkanal dan lahan gambut, sensivitas ekologi dan sensivitas sosial. Setiap parameter akan memiliki bobot yang berbeda berdasarkan pengaruhnya terhadap kerusakan kawasan dan kelangsungan hidup spesies kunci. Hasil penelitian menunjukkan kawasan dengan tingkat kerusakan berat seluas 13.219,60 Ha (15%), rusak sedang seluas 31.867,20 Ha (36%), dan rusak ringan seluas 42.555,91 Ha (49%). Areal yang mengalami kerusakan berat merupakan area yang diusulkan menjadi prioritas utama kegiatan pemulihan ekosistem. Kerusakan ekosistem di SM Padang Sugihan terutama disebabkan oleh kebakaran hutan yang terjadi secara berulang, pembalakan hutan, dan pembukaan kanal drainase. Ketiga faktor tersebut menyebabkan hilangnya masa gambut dan berkurang/ hilangnya komposisi vegetasi asli

Global ocean lipidomes show a universal relationship between temperature and lipid unsaturation

Global-scale surveys of plankton communities using "omics" techniques have revolutionized our understanding of the ocean. Lipidomics has demonstrated the potential to add further essential insights on ocean ecosystem function but has yet to be applied on a global scale. We analyzed 930 lipid samples across the global ocean using a uniform high-resolution accurate-mass mass spectrometry analytical workflow, revealing previously unknown characteristics of ocean planktonic lipidomes. Focusing on 10 molecularly diverse glycerolipid classes, we identified 1151 distinct lipid species, finding that fatty acid unsaturation (i.e., number of carbon-carbon double bonds) is fundamentally constrained by temperature. We predict substantial declines in the essential fatty acid eicosapentaenoic acid over the next century, which are likely to have serious deleterious effects on economically critical fisheries

Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry

Abstract Background Polycystic ovary syndrome (PCOS) is a complex multifactorial disorder with a substantial genetic component. However, the clinical manifestations of PCOS are heterogeneous with notable differences between lean and obese women, implying a different pathophysiology manifesting in differential body mass index (BMI). We performed a meta-analysis of genome-wide association study (GWAS) data from six well-characterised cohorts, using a case–control study design stratified by BMI, aiming to identify genetic variants associated with lean and overweight/obese PCOS subtypes. Results The study comprised 254,588 women (5,937 cases and 248,651 controls) from individual studies performed in Australia, Estonia, Finland, the Netherlands and United States of America, and separated according to three BMI stratifications (lean, overweight and obese). Genome-wide association analyses were performed for each stratification within each cohort, with the data for each BMI group meta-analysed using METAL software. Almost half of the total study population (47%, n = 119,584) were of lean BMI (≤ 25 kg/m2). Two genome-wide significant loci were identified for lean PCOS, led by rs12000707 within DENND1A (P = 1.55 × 10–12) and rs2228260 within XBP1 (P = 3.68 × 10–8). One additional locus, LINC02905, was highlighted as significantly associated with lean PCOS through gene-based analyses (P = 1.76 × 10–6). There were no significant loci observed for the overweight or obese sub-strata when analysed separately, however, when these strata were combined, an association signal led by rs569675099 within DENND1A reached genome-wide significance (P = 3.22 × 10–9) and a gene-based association was identified with ERBB4 (P = 1.59 × 10–6). Nineteen of 28 signals identified in previous GWAS, were replicated with consistent allelic effect in the lean stratum. There were less replicated signals in the overweight and obese groups, and only 4 SNPs were replicated in each of the three BMI strata. Conclusions Genetic variation at the XBP1, LINC02905 and ERBB4 loci were associated with PCOS within unique BMI strata, while DENND1A demonstrated associations across multiple strata, providing evidence of both distinct and shared genetic features between lean and overweight/obese PCOS-affected women. This study demonstrated that PCOS-affected women with contrasting body weight are not only phenotypically distinct but also show variation in genetic architecture; lean PCOS women typically display elevated gonadotrophin ratios, lower insulin resistance, higher androgen levels, including adrenal androgens, and more favourable lipid profiles. Overall, these findings add to the growing body of evidence supporting a genetic basis for PCOS as well as differences in genetic patterns relevant to PCOS BMI-subtype

Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry.

Funder: Eris M.Field Chair in Diabetes Research and NIDDK P30-DK063481BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex multifactorial disorder with a substantial genetic component. However, the clinical manifestations of PCOS are heterogeneous with notable differences between lean and obese women, implying a different pathophysiology manifesting in differential body mass index (BMI). We performed a meta-analysis of genome-wide association study (GWAS) data from six well-characterised cohorts, using a case-control study design stratified by BMI, aiming to identify genetic variants associated with lean and overweight/obese PCOS subtypes. RESULTS: The study comprised 254,588 women (5,937 cases and 248,651 controls) from individual studies performed in Australia, Estonia, Finland, the Netherlands and United States of America, and separated according to three BMI stratifications (lean, overweight and obese). Genome-wide association analyses were performed for each stratification within each cohort, with the data for each BMI group meta-analysed using METAL software. Almost half of the total study population (47%, n = 119,584) were of lean BMI (≤ 25 kg/m2). Two genome-wide significant loci were identified for lean PCOS, led by rs12000707 within DENND1A (P = 1.55 × 10-12) and rs2228260 within XBP1 (P = 3.68 × 10-8). One additional locus, LINC02905, was highlighted as significantly associated with lean PCOS through gene-based analyses (P = 1.76 × 10-6). There were no significant loci observed for the overweight or obese sub-strata when analysed separately, however, when these strata were combined, an association signal led by rs569675099 within DENND1A reached genome-wide significance (P = 3.22 × 10-9) and a gene-based association was identified with ERBB4 (P = 1.59 × 10-6). Nineteen of 28 signals identified in previous GWAS, were replicated with consistent allelic effect in the lean stratum. There were less replicated signals in the overweight and obese groups, and only 4 SNPs were replicated in each of the three BMI strata. CONCLUSIONS: Genetic variation at the XBP1, LINC02905 and ERBB4 loci were associated with PCOS within unique BMI strata, while DENND1A demonstrated associations across multiple strata, providing evidence of both distinct and shared genetic features between lean and overweight/obese PCOS-affected women. This study demonstrated that PCOS-affected women with contrasting body weight are not only phenotypically distinct but also show variation in genetic architecture; lean PCOS women typically display elevated gonadotrophin ratios, lower insulin resistance, higher androgen levels, including adrenal androgens, and more favourable lipid profiles. Overall, these findings add to the growing body of evidence supporting a genetic basis for PCOS as well as differences in genetic patterns relevant to PCOS BMI-subtype