Occurrence, diversity and morphology of poroid wood decay by Ganoderma spp. from tropical moist deciduous forest region of Bangladesh

There are many hot spots in tropical moist deciduous forest region where wood decay fungi grow naturally. An investigation was carried  out  to  collect, identify  and  preserve wood decay Ganoderma spp. on the basis of morphological characteristics  from Pabna,  Dhaka and  Rajshahi under tropical  moist deciduous  forest  region in Bangladesh during  June  to September  2016 and July to October  2017. This study was conducted to  record the  morphological  variability,  distribution,  habitat  and diversity of  the Ganoderma  population. A  total  of  40 Ganoderma  samples  were  collected  and identified to nine species  under  Ganodermataceae family.  The samples were collected from the sites by walking through the area following standard method. The field data and laboratory analytical data was recorded during sample collection and in the laboratory, respectively.The highest density of occurrence (23%) was recorded for Ganoderma lucidum and Ganoderma oregonense followed by Ganoderma applanatum (20%), Ganoderma praelongum (19%), Ganoderma lesklokorka (18.5%), Ganoderma pfeifferi (17%), Ganoderma boninense (15%), Ganoderma lipsiense (13%) and Ganoderma tsugae (11%). The highest frequency of occurrence (10%) was recorded for Ganoderma applanatum and Ganoderma oregonense followed by Ganoderma lucidum (9%), Ganoderma pfeifferi (8%), Ganoderma boninense (8%), Ganoderma praelongum (7%), Ganoderma lesklokorka (7%),Ganoderma tsugae (6%) and  Ganoderma lipsiense (5%). During survey, Koroi (Albizia procera), Aurjun (Terminalia arjuna), Sisso plant (Dalbergia sissoo), Neem (Azadirachta indica), Golden shower (Acacia auriculiformis) and Rain tree (Albizia lebbeck) were found as hosts of Ganoderma spp. The specimens were preserved in the SAU Herbarium of Macro Fungi (SHMF) and might be useful in mushroom breeding and development program for medicine and food industry sector in future

Risk stratification of newly diagnosed multiple myeloma patients

Background: Multiple Myeloma is a neoplastic proliferation of plasma cells, associated with an M (monoclonal) protein in serum and/or urine and evidence of organ damage. Despite advances in treatment, the disease remains heterogeneous, necessitating a comprehensive understanding of its risk stratification. Risk-adapted initial therapy, maintenance therapy, refractory disease management and prognosis varies according to risk group. The aim of our study is to categorize the newly diagnosed MM patients according to their risk groups. Methods: This cross-sectional observational study was conducted at the Department of Haematology of Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh, from August 2019 to July 2020. A total of 31 newly diagnosed MM patients were enrolled based on specific inclusion and exclusion criteria. Risk stratification was performed using ISS, R-ISS, mSMART criteria and Avets risk group categorization. Result: The majority of the patients were male (64.52%) and aged between 55-64 years (45.16%). Clinical features predominantly included low back pain (74.19%) and general weakness (38.71%). Cytogenetic abnormalities were noted in 38.7% of the patients, with del (13q) being the most common (32.30%). Most patients were in ISS Stage III (70.97%) and R-ISS Stage II (48.39%). According to mSMART criteria, 80.65% were at standard risk while Avet's risk stratification identifies 58.06% were at intermediate risk. Conclusion: The study reveals a high prevalence of patients in advanced ISS stages and intermediate to high-risk categories, emphasizing the need for early and personalized intervention strategies

Pneumococcal Conjugate Vaccine impact assessment in Bangladesh [version 1; referees: 1 approved, 2 approved with reservations]

The study examines the impact of the introduction of 10-valent Pneumococcal Conjugate Vaccine (PCV10) into Bangladesh’s national vaccine program. PCV10 is administered to children under 1 year-old; the scheduled ages of administration are at 6, 10, and 18 weeks. The study is conducted in ~770,000 population containing ~90,000 <5 children in Sylhet, Bangladesh and has five objectives: 1) To collect data on community-based pre-PCV incidence rates of invasive pneumococcal diseases (IPD) in 0-59 month-old children in Sylhet, Bangladesh; 2) To evaluate the effectiveness of PCV10 introduction on Vaccine Type (VT) IPD in 3-59 month-old children using an incident case-control study design. Secondary aims include measuring the effects of PCV10 introduction on all IPD in 3-59 month-old children using case-control study design, and quantifying the emergence of Non Vaccine Type IPD; 3) To evaluate the effectiveness of PCV10 introduction on chest radiograph-confirmed pneumonia in children 3-35 months old using incident case-control study design. We will estimate the incidence trend of clinical and radiologically-confirmed pneumonia in 3-35 month-old children in the study area before and after introduction of PCV10; 4) To determine the feasibility and utility of lung ultrasound for the diagnosis of pediatric pneumonia in a large sample of children in a resource-limited setting. We will also evaluate the effectiveness of PCV10 introduction on ultrasound-confirmed pneumonia in 3-35 month-old children using an incident case-control design and to examine the incidence trend of ultrasound-confirmed pneumonia in 3-35 month-old children in the study area before and after PCV10 introduction; and 5) To determine the direct and indirect effects of vaccination status on nasopharyngeal colonization on VT pneumococci among children with pneumonia.  This paper presents the methodology. The study will allow us to conduct a comprehensive and robust assessment of the impact of national introduction of PCV10 on pneumococcal disease in Bangladesh

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42\ub74% vs 44\ub72%; absolute difference \u20131\ub769 [\u20139\ub758 to 6\ub711] p=0\ub767; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5\u20138] vs 6 [5\u20138] cm H2O; p=0\ub70011). ICU mortality was higher in MICs than in HICs (30\ub75% vs 19\ub79%; p=0\ub70004; adjusted effect 16\ub741% [95% CI 9\ub752\u201323\ub752]; p&lt;0\ub70001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0\ub780 [95% CI 0\ub775\u20130\ub786]; p&lt;0\ub70001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status. Funding: No funding

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

Prediction of gestational age using urinary metabolites in term and preterm pregnancies.

Assessment of gestational age (GA) is key to provide optimal care during pregnancy. However, its accurate determination remains challenging in low- and middle-income countries, where access to obstetric ultrasound is limited. Hence, there is an urgent need to develop clinical approaches that allow accurate and inexpensive estimations of GA. We investigated the ability of urinary metabolites to predict GA at time of collection in a diverse multi-site cohort of healthy and pathological pregnancies (n = 99) using a broad-spectrum liquid chromatography coupled with mass spectrometry (LC-MS) platform. Our approach detected a myriad of steroid hormones and their derivatives including estrogens, progesterones, corticosteroids, and androgens which were associated with pregnancy progression. We developed a restricted model that predicted GA with high accuracy using three metabolites (rho = 0.87, RMSE = 1.58 weeks) that was validated in an independent cohort (n = 20). The predictions were more robust in pregnancies that went to term in comparison to pregnancies that ended prematurely. Overall, we demonstrated the feasibility of implementing urine metabolomics analysis in large-scale multi-site studies and report a predictive model of GA with a potential clinical value

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18 : a modelling study

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2 ·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676· 5 (513· 6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8–8120·3]) cases per 100000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0–1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81· 1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. Interpretation: Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas

Association of maternal prenatal copper concentration with gestational duration and preterm birth: a multicountry meta-analysis

Background Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). Objectives This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. Methods Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. Results The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. Conclusions Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB