Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-Temporal Variability of Peat CH4 and N2O Fluxes and Their Contribution to Peat GHG Budgets in Indonesian Forests and Oil Palm Plantations

Land-use change in tropical peatlands substantially impacts peat emissions of methane (CH4) and nitrous oxide (N2O) in addition to emissions of carbon dioxide (CO2). However, assessments of full peat greenhouse gas (GHG) budgets are scarce and CH4 and N2O contributions remain highly uncertain. The objective of our research was to assess changes in peat GHG flux and budget associated with peat swamp forest disturbance and conversion to oil palm plantation and to evaluate drivers of variation in trace gas fluxes. Over a period of one and a half year, we monitored monthly CH4 and N2O fluxes together with environmental variables in three undrained peat swamp forests and three oil palm plantations on peat in Central Kalimantan. The forests included two primary forests and one 30-year-old secondary forest. We calculated the peat GHG budget in both ecosystems using soil respiration and litterfall rates measured concurrently with CH4 and N2O fluxes, site-specific soil respiration partitioning ratios, and literature-based values of root inputs and dissolved organic carbon export. Peat CH4 fluxes (kg CH4 ha−1 year−1) were insignificant in oil palm (0.3 ± 0.4) while emissions in forest were high (14.0 ± 2.8), and larger in wet than in dry months. N2O emissions (kg N2O ha−1 year−1) were highly variable spatially and temporally and similar across land-uses (5.0 ± 3.9 and 5.2 ± 3.7 in oil palm and forest). Temporal variation of CH4 was controlled by water table level and soil water-filled pore space in forest and oil palm, respectively. Monthly fluctuations of N2O were linked to water table level in forest. The peat GHG budget (Mg CO2 equivalent ha−1 year−1) in oil palm (31.7 ± 8.6) was nearly eight times the budget in forest (4.0 ± 4.8) owing mainly to decreased peat C inputs and increased peat C outputs. The GHG budget was also ten times higher in the secondary forest (10.2 ± 4.5) than in the primary forests (0.9 ± 3.9) on the account of a larger peat C budget and N2O emission rate. In oil palm 96% of emissions were released as CO2 whereas in forest CH4 and N2O together contributed 65% to the budget. Our study highlights the disastrous atmospheric impact associated with forest degradation and conversion to oil palm in tropical peatlands and stresses the need to investigate GHG fluxes in disturbed undrained lands.
Isotopically Light Cd in Sediments Underlying Oxygen Deficient Zones

Cadmium is a trace metal of interest in the ocean partly because its concentration mimics that of phosphate. However, deviations from the global mean dissolved Cd/PO4 relationship are present in oxygen deficient zones, where Cd is depleted relative to phosphate. This decoupling has been suggested to result from cadmium sulphide (CdS) precipitation in reducing microenvironments within sinking organic matter. We present Cd concentrations and Cd isotope compositions in organic-rich sediments deposited at several upwelling sites along the northeast Pacific continental margin. These sediments all have enriched Cd concentrations relative to crustal material. We calculate a net accumulation rate of Cd in margin settings of between 2.6 to 12.0 × 107 mol/yr, higher than previous estimates, but at the low end of a recently published estimate for the magnitude of the marine sink due to water column CdS precipitation. Cadmium in organic-rich sediments is isotopically light (δ 114/110CdNIST-3108 = +0.02 ± 0.14‰, n = 26; 2 SD) compared to deep seawater (+0.3 ± 0.1‰). However, isotope fractionation during diagenesis in continental margin settings appears to be small. Therefore, the light Cd isotope composition of organic-rich sediments is likely to reflect an isotopically light source of Cd. Non-quantitative biological uptake of light Cd by phytoplankton is one possible means of supplying light Cd to the sediment, which would imply that Cd isotopes could be used as a tracer of past ocean productivity. However, water column CdS precipitation is also predicted to preferentially sequester light Cd isotopes from the water column, which could obfuscate Cd as a tracer. We also observe notably light Cd isotope compositions associated with elevated solid phase Fe concentrations, suggesting that scavenging of Cd by Fe oxide phases may contribute to the light Cd isotope composition of sediments. These multiple possible sources of isotopically light Cd to sediments, along with evidence for complex particle cycling of Cd in the water column, bring into question the straightforward application of Cd isotopes as a paleoproductivity proxy.
Benefits of Mobile Contact Tracing on COVID-19: Tracing Capacity Perspectives

For effectively suppressing COVID-19’s spread, contact tracing has been widely used to identify, isolate, and follow-up with those who have come in close contact with an infected person (or “close contacts”). Traditionally, contact tracers in local health offices interview an infected person to identify visited places (or hotspots) and then check any close contacts. For the accurate recall of travel history, several countries including South Korea corroborate multiple data sources, such as cell location or credit card transactions (1). Beside this traditional approach, various mobile apps were introduced to help improve travel history tracking including automated GPS tracking (e.g., Israel’s HaMagen) and manual place QRcode scanning (e.g., New Zealand’s NZ COVID Tracer and Korea’s KI Pass). Alternatively, mobile apps maintain individuals’ “encounter history” (instead of place visit history) by leveraging peerto-peer wireless beaconing (i.e., self-announcing its presence to nearby devices) with Bluetooth Low Energy (BLE) in smartphones, such as Google-Apple’s Exposure Notification and Singapore’s BlueTrace and TraceTogether. This encounter history can be used later to judge whether a user had a risky encounter with an infected person. We argue that traditional manual contact tracing can be greatly improved by leveraging the wisdom of crowds. Local community members install mobile apps to self-collect “breadcrumbs” for contact tracing, such as GPS traces, place QR-codes, and wireless encounter histories, which can offer near real-time assessment (2). However, there is a systematic lack of adoption of mobile apps in many countries, and success stories of mobile apps are scarce. This is partly because local health authorities are unsure about the benefits of mobile apps, mostly worrying that a lack of app adoption fails to achieve digital herd immunity (3). We emphasize the importance of adopting contact tracing apps via “contact tracing capacity modeling. ” Our model clearly demonstrates that the adoption of contact tracing model apps can potentially increase contact tracing capacity. Furthermore, this capacity increment thanks to crowd participation will greatly help local authorities to better handle confirmed cases in the early or late phases of the pandemics. In the following, we present our approach of contact tracing capacity modeling and its benefits for contact tracing. We then discuss practical challenges related to application adoptions by citizens and health authorities as well as technical implementation issues.
Patient Reported Outcomes in Chronic Inflammatory Diseases: Current State, Limitations and Perspectives

Chronic inflammatory diseases (CID) are emerging disorders which do not only affect specific organs with respective clinical symptoms but can also affect various aspects of life, such as emotional distress, anxiety, fatigue and quality of life. These facets of chronic disease are often not recognized in the therapy of CID patients. Furthermore, the symptoms and patient-reported outcomes often do not correlate well with the actual inflammatory burden. The discrepancy between patient-reported symptoms and objectively assessed disease activity can indeed be instructive for the treating physician to draw an integrative picture of an individual’s disease course. This poses a challenge for the design of novel, more comprehensive disease assessments. In this mini-review, we report on the currently available patient-reported outcomes, the unmet needs in the field of chronic inflammatory diseases and the challenges of addressing these.
Potential Mechanism Underlying the Role of Mitochondria in Breast Cancer Drug Resistance and Its Related Treatment Prospects

Breast cancer incidence and mortality rates have been consistently high among women. The use of diverse therapeutic strategies, including chemotherapy, endocrine therapy, targeted therapy, and immunotherapy, has improved breast cancer prognosis. However, drug resistance has become a tremendous obstacle in overcoming breast cancer recurrence and metastasis. It is known that mitochondria play an important role in carcinoma cell growth, invasion and apoptosis. Recent studies have explored the involvement of mitochondrial metabolism in breast cancer prognosis. Here, we will provide an overview of studies that investigated mitochondrial metabolism pathways in breast cancer treatment resistance, and discuss the application prospects of agents targeting mitochondrial pathways against drug-resistant breast cancer.
Identification of an Immune-Related Risk Signature Correlates With Immunophenotype and Predicts Anti-PD-L1 Efficacy of Urothelial Cancer

Immune checkpoint inhibitor (ICI) treatment has been used to treat advanced urothelial cancer. Molecular markers might improve risk stratification and prediction of ICI benefit for urothelial cancer patients. We analyzed 406 cases of bladder urothelial cancer from The Cancer Genome Atlas (TCGA) data set and identified 161 messenger RNAs (mRNAs) as differentially expressed immunity genes (DEIGs). Using the LASSO Cox regression model, an eight-mRNA-based risk signature was built. We validated the prognostic and predictive accuracy of this immune-related risk signature in 348 metastatic urothelial cancer (mUC) samples treated with anti-PD-L1 (atezolizumab) from IMvigor210. We built an immune-related risk signature based on the eight mRNAs: ANXA1, IL22, IL9R, KLRK1, LRP1, NRG3, SEMA6D, and STAP2. The eight-mRNA-based risk signature successfully categorizes patients into high-risk and low-risk groups. Overall survival was significantly different between these groups, regardless if the initial TCGA training set, the internal TCGA testing set, all TCGA set, or the ICI treatment set. The hazard ratio (HR) of the high-risk group to the low-risk group was 3.65 (p < 0.0001), 2.56 (p < 0.0001), 3.36 (p < 0.0001), and 2.42 (p = 0.0009). The risk signature was an independent prognostic factor for prediction survival. Moreover, the risk signature was related to immunity characteristics. In different tumor mutational burden (TMB) subgroups, it successfully categorizes patients into high-risk and low-risk groups, with significant differences of clinical outcome. Our eight-mRNA-based risk signature is a stable biomarker for urothelial cancer and might be able to predict which patients benefit from ICI treatment. It might play a role in precision individualized immunotherapy.
Sex Influence on the Functional Recovery Pattern After a Graded Running Race: Original Analysis to Identify the Recovery Profiles

This study investigated the sex influence on the acute and delayed fatigue effects of a 20 km graded running race. Eighteen recreational runners, 10 women and 8 men, completed the race. The testing protocol included five sessions: a week before the race (PRE), 35 ± 15 min after (POST), 2 h, 2 and 4 days (2D and 4D) later. Each session included uni- and bilateral maximal isometric voluntary contractions of the knee extensors (MVC), a squat jump (SJ), and a drop jump (DJ). Acute and delayed muscle soreness (DOMS) were evaluated for the quadriceps, hamstring and triceps surae muscle groups. The 2D and 4D sessions included also a horizontal force-velocity test (HF-V) performed under five resistive conditions. For each test, a set of key variables was computed to characterize the lower limb functional recovery. Mixed ANOVA analyses revealed significant (sex × time) interactions, with larger acute drops for men in MVCs and earlier recovery for women in the bilateral MVC (p < 0.001) and DJ (p < 0.05) tests. Only women reported DOMS for the hamstrings at 2D (p < 0.001) and showed small improvements in pure concentric SJ (p < 0.05) and HF-V (p < 0.01) tests at 4D. As expected, DOMS disappeared prior to the complete functional recovery. These results confirmed the combined influence of testing task and sex on the functional recovery pattern while supporting a lesser and faster recovery in women. The originality of this study lies in the complexity and sex-dependence of the functional recovery pattern revealed by a multiple factorial analysis which was used to identify the most discriminating tests and variables in the recovery pattern. The obtained clusters highlighted some recovery profiles associated with greater risks of injury when starting to run again. However, the lack of sex × time interaction for normalized values emphasizes the major influence of men’s initially higher functional values compared to women.
Mapping Micro-Level Decision-Making for Alligator Management in North Carolina

Human-carnivore interactions represent a grand challenge to conservation decision-making and legitimacy across all levels of governance. Human populations continue to encroach upon and devastate carnivore habitats and populations, intensifying interactions between a variety of biodiversity interests and beneficiaries. As a result, carnivores most intensely impact those living in their midst, demanding increased attention by local decision makers, who are often best suited to catering to the needs of communities most affected. Their views and desires can serve as a forerunner of public trust and acceptance of policies created. However, due to the complexity of decisions about carnivores, these actors are often overlooked in the formal decision process. To address this need, we applied multi-criteria decision analysis (MCDA) to a case study of American alligator (Alligator mississippiensis) conservation in 10 coastal North Carolina counties to identify and postulate legitimate outcomes. We surveyed 25 local decision makers who are or may be responsible for management decisions concerning the American alligator and asked them to evaluate and indicate the level of importance of salient alligator management elements. Results indicate that decision makers strongly favored the wildlife and social factors when making alligator management decisions, as well as the criteria human well-being, attitudes toward alligators, education programs, and storm mitigation. Respondents favored highly managed and balanced management alternatives to maximize preferred criteria and achieve legitimate alligator management at the local level. These results demonstrate that local decision makers are capable of identifying what is important to alligator management decisions, and can provide an insightful look at trade-offs that need to or could be made to achieve optimal alligator outcomes. We conclude that local decision makers should become more involved in shaping carnivore outcomes to enhance legitimacy of alligator policy and help achieve conservation targets. Future research will need to further expand understandings of local decision makers' decision-making process in other carnivore contexts. Researchers will want to consider using and refining decision analysis to cut through the complexity of carnivore conservation decision-making that exists across wide geopolitical expanses.
Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics

Background Clinical and epidemiological studies have suggested systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are comorbidities and common genetic etiologies can partly explain such coexistence. However, shared genetic determinations underlying the two diseases remain largely unknown. Methods Our analysis relied on summary statistics available from genome-wide association studies of SLE (N = 23,210) and RA (N = 58,284). We first evaluated the genetic correlation between RA and SLE through the linkage disequilibrium score regression (LDSC). Then, we performed a multiple-tissue eQTL (expression quantitative trait loci) weighted integrative analysis for each of the two diseases and aggregated association evidence across these tissues via the recently proposed harmonic mean P-value (HMP) combination strategy, which can produce a single well-calibrated P-value for correlated test statistics. Afterwards, we conducted the pleiotropy-informed association using conjunction conditional FDR (ccFDR) to identify potential pleiotropic genes associated with both RA and SLE. Results We found there existed a significant positive genetic correlation (rg = 0.404, P = 6.01E-10) via LDSC between RA and SLE. Based on the multiple-tissue eQTL weighted integrative analysis and the HMP combination across various tissues, we discovered 14 potential pleiotropic genes by ccFDR, among which four were likely newly novel genes (i.e., INPP5B, OR5K2, RP11-2C24.5, and CTD-3105H18.4). The SNP effect sizes of these pleiotropic genes were typically positively dependent, with an average correlation of 0.579. Functionally, these genes were implicated in multiple auto-immune relevant pathways such as inositol phosphate metabolic process, membrane and glucagon signaling pathway. Conclusion This study reveals common genetic components between RA and SLE and provides candidate associated loci for understanding of molecular mechanism underlying the comorbidity of the two diseases.
Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting

Background The prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting. Methods 28,171 adult inpatients suspected of having PTB in China were retrospectively analyzed. Bronchoalveolar lavage fluid (BALF) and/or sputum were used for acid-fast bacilli (AFB) smear, Xpert MTB/RIF (Xpert), and culture. A positive mycobacterial culture was used as the reference standard. Peripheral blood mononuclear cells (PBMC) were used for T-SPOT.TB. We analyzed specimen types’ effect on these assays’ performance, determined the number of smears for diagnosing PTB, and evaluated the ability of these assays performed alone, or in combination, to diagnose PTB and nontuberculous mycobacteria (NTM) infections. Results Sputum and BALF showed moderate to substantial consistency when they were used for AFB smear or Xpert, with a higher positive detection rate by BALF. 3-4 smears had a higher sensitivity than 1-2 smears. Moreover, simultaneous combination of AFB and Xpert correctly identified 44/51 of AFB+/Xpert+ and 6/7 of AFB+/Xpert- cases as PTB and NTM, respectively. Lastly, when combined with AFB/Xpert sequentially, T-SPOT showed limited roles in patients that were either AFB+ or Xpert+. However, T-SPOTMDC (manufacturer-defined cut-off) showed a high negative predicative value (99.1%) and suboptimal sensitivity (74.4%), and TBAg/PHA (ratio of Mycobacterium tuberculosis-specific antigens to phytohaemagglutinin spot-forming cells, which is a modified method calculating T-SPOT.TB assay results) ≥0.3 demonstrated a high specificity (95.7%) and a relatively low sensitivity (16.3%) in AFB-/Xpert- patients. Conclusions Concurrently performing AFB smear (at least 3 smears) and Xpert on sputum and/or BALF could aid in rapid diagnosis of PTB and NTM infections in a real-world high-burden setting. If available, BALF is preferred for both AFB smear and Xpert. Expanding this algorithm, PBMC T-SPOTMDC and TBAg/PHA ratios have a supplementary role for PTB diagnosis in AFB-/Xpert- patients (moderately ruling out PTB and ruling in PTB, respectively). Our findings may also inform policy makers’ decisions regarding prevention and control of TB in a high burden setting.
The Effects of Tai Chi Exercise Among Adults With Chronic Heart Failure: An Overview of Systematic Review and Meta-Analysis

Background: Tai chi (TC) is a popular form of exercise among adults with chronic heart failure (CHF), yet services are greatly underutilized. The aim of the current study was to identify and summarize the existing evidence and to systematically determine the clinical effectiveness of Tai Chi in the management of CHF using a systematic overview. Methods: Both English and Chinese databases were searched for systematic reviews (SRs)/meta-analyses (MAs) on TC for CHF from their inception to June 2020. The methodological quality, reporting quality, and risk of bias of SRs/MAs were assessed using Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR-2), the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, and Risk of Bias in Systematic reviews (ROBIS), respectively. The evidence quality of outcome measures was assessed by the Grades of Recommendations, Assessment, Development and Evaluation (GRADE). Results: Six SRs/MAs using a quantitative synthesis to assess various outcomes of TC in CHF were included in this overview. The methodological quality, reporting quality and risk of bias of the SRs/MAs and the evidence quality of the outcome measures are generally unsatisfactory. The limitations of the past SRs/MAs included the lack of either the protocol or registration, the list of excluded studies, and the computational details of meta-analysis were inadequately reported. The critical problems were that qualitative data synthesis relied on trials with small sample sizes and critical low quality. Conclusions: TC may be a promising complementary treatment for CHF. However, further rigorous and comprehensive SRs/MAs and RCTs are required to provide robust evidence for definitive conclusions.