Miracle-dz/UniFAR-FTUs huggingface dataset:
Hospital length of stay: A cross-specialty analysis and Beta-geometric model

The typical hospital Length of Stay (LOS) distribution is known to be right-skewed, to considerably vary across Diagnosis Related Groups (DRG), and to contain markedly high values, in significant proportions. These very long stays are often considered outliers, and thin-tailed statistical distributions are assumed. Moreover, modeling is typically performed by Diagnosis Related Group (DRG) and is consequently based on small empirical samples, thus justifying the previous assumption. However, resource consumption and planning occur at the level of medical specialty departments covering multiple DRG, and when considered at this decision-making scale, extreme LOS values represent a significant component of the distribution of LOS (the right tail) that determines many of its statistical properties. Through a study of 46,364 electronic health records over four medical specialty departments (Pediatrics, Obstetrics/Gynecology, Surgery, and Rehabilitation Medicine) in the largest hospital in Thailand (Siriraj Hospital in Bangkok), we show that the distribution of LOS exhibits a tail behavior that is consistent with a subexponential distribution. We analyze some empirical properties of such a distribution that are of relevance to cost and resource planning, notably the concentration of resource consumption among a minority of admissions/patients, an increasing residual LOS, where the longer a patient has been admitted, the longer they would, counter-intuitively, be expected to remain admitted, and a slow convergence of the Law of Large Numbers, making empirical estimates of moments (e.g. mean, variance) unreliable. Consequently, we propose a novel Beta-Geometric model that shows a good fit with observed data and reproduces these empirical properties of LOS. Finally, we use our findings to make practical recommendations regarding the pricing and management of LOS.
Time to Initiation of Renal Replacement Therapy Among Critically Ill Patients With Acute Kidney Injury: A Current Systematic Review and Meta-Analysis

Supplemental Digital Content is available in the text. OBJECTIVES: The optimal time to initiate renal replacement therapy in critically ill patients with acute kidney injury is controversial. We investigated the effect of such earlier versus later initiation of renal replacement therapy on the primary outcome of 28-day mortality and other patient-centered secondary outcomes. DESIGN: We searched MEDLINE (via PubMed), EMBASE, and Cochrane databases to July 17, 2020, and included randomized controlled trials comparing earlier versus later renal replacement therapy. SETTING: Multiple centers involved in eight trials. PATIENTS: Total of 4,588 trial participants. Intervention: Two independents investigators screened and extracted data using a predefined form. We selected randomized controlled trials in critically ill adult patients with acute kidney injury and compared of earlier versus later initiation of renal replacement therapy regardless of modality. MEASUREMENTS AND MAIN RESULTS: Overall, 28-day mortality was similar between earlier and later renal replacement therapy initiation (38.43% vs 38.06%, respectively; risk ratio, 1.01; [95% CI, 0.94–1.09]; I2 = 0%). Earlier renal replacement therapy, however, shortened hospital length of stay (mean difference, –2.14 d; [95% CI, –4.13 to –0.14]) and ICU length of stay (mean difference, –1.18 d; [95% CI, –1.95 to –0.42]). In contrast, later renal replacement therapy decreased the use of renal replacement therapy (relative risk, 0.69; [95% CI, 0.58–0.82]) and lowered the risk of catheter-related blood stream infection (risk ratio, 0.50, [95% CI, 0.29–0.86). Among survivors, renal replacement therapy dependence at day 28 was similar between earlier and later renal replacement therapy initiation (risk ratio, 0.98; [95% CI, 0.66–1.40]). CONCLUSIONS: Earlier or later initiation of renal replacement therapy did not affect mortality. However, earlier renal replacement therapy was associated with significantly shorter ICU and hospital length of stay, whereas later renal replacement therapy was associated with decreased use of renal replacement therapy and decreased risk of catheter-related blood stream infection. These findings can be used to guide the management of critically ill patients with acute kidney injury.
CHK2 Inhibition Provides a Strategy to Suppress Hematologic Toxicity from PARP Inhibitors

Patients with cancer treated with PARP inhibitors (PARPi) experience various side effects, with hematologic toxicity being most common. Short-term treatment of mice with olaparib resulted in depletion of reticulocytes, B-cell progenitors, and immature thymocytes, whereas longer treatment induced broader myelosuppression. We performed a CRISPR/Cas9 screen that targeted DNA repair genes in Eμ-Myc pre-B lymphoma cell lines as a way to identify strategies to suppress hematologic toxicity from PARPi. The screen revealed that single-guide RNAs targeting the serine/threonine kinase checkpoint kinase 2 (CHK2) were enriched following olaparib treatment. Genetic or pharmacologic inhibition of CHK2-blunted PARPi response in lymphoid and myeloid cell lines, and in primary murine pre-B/pro-B cells. Using a Cas9 base editor, we found that blocking CHK2-mediated phosphorylation of p53 also impaired olaparib response. Our results identify the p53 pathway as a major determinant of the acute response to PARPi in normal blood cells and demonstrate that targeting CHK2 can short circuit this response. Cotreatment with a CHK2 inhibitor did not antagonize olaparib response in ovarian cancer cell lines. Selective inhibition of CHK2 may spare blood cells from the toxic influence of PARPi and broaden the utility of these drugs. Implications: We reveal that genetic or pharmacologic inhibition of CHK2 may offer a way to alleviate the toxic influence of PARPi in the hematologic system.
Consensus-Based Cooperative Algorithms for Training Over Distributed Data Sets Using Stochastic Gradients

In this article, distributed algorithms are proposed for training a group of neural networks with private data sets. Stochastic gradients are utilized in order to eliminate the requirement for true gradients. To obtain a universal model of the distributed neural networks trained using local data sets only, consensus tools are introduced to derive the model toward the optimum. Most of the existing works employ diminishing learning rates, which are often slow and impracticable for online learning, while constant learning rates are studied in some recent works, but the principle for choosing the rates is not well established. In this article, constant learning rates are adopted to empower the proposed algorithms with tracking ability. Under mild conditions, the convergence of the proposed algorithms is established by exploring the error dynamics of the connected agents, which provides an upper bound for selecting the constant learning rates. Performances of the proposed algorithms are analyzed with and without gradient noises, in the sense of mean square error (MSE). It is proved that the MSE converges with bounded errors determined by the gradient noises, and the MSE converges to zero if the gradient noises are absent. Simulation results are provided to validate the effectiveness of the proposed algorithms.
Predicting Surgical Margins in Patients With Borderline Resectable and Locally Advanced Pancreatic Cancer Undergoing Resection

Background Many patients with borderline resectable/locally advanced pancreatic ductal adenocarcinoma (borderline resectable [BR]/locally advanced [LA] pancreatic ductal adenocarcinoma [PDAC]) undergoing resection will have positive resection margins (R1), which is associated with poor prognosis. It might be useful to preoperatively predict the margin (R) status. Methods Data from patients with BR/LA PDAC who underwent a pancreatectomy between 2008 and 2018 at Brigham and Women’s Hospital were retrospectively reviewed. Logistic regression analysis was used to evaluate the association between R status and relevant preoperative factors. Significant predictors of R1 resection on univariate analysis (P < .1) were entered into a stepwise selection using the Akaike information criterion to define the final model. Results A total of 142 patients with BR/LA PDAC were included in the analysis, 60(42.3%) had R1 resections. In stepwise selection, the following factors were identified as positive predictors of an R1 resection: evidence of lymphadenopathy at diagnosis (OR = 2.06, 95% CI: 0.99-4.36, P = .056), the need for pancreaticoduodenectomy (OR = 3.81, 96% CI: 1.15-15.70, P = .040), extent of portal vein/superior mesenteric vein involvement at restaging (<180°, OR = 3.57, 95% CI: 1.00-17.00, P = .069, ≥180°, OR = 7,32, 95% CI: 1.75-39.87, P = .010), stable CA 19-9 serum levels (less than 50% decrease from diagnosis to restaging, OR = 2.27, 95% CI: 0.84-6.36 P = .107), and no preoperative FOLFIRINOX (OR = 2.17, 95% CI: 0.86-5.64, P = .103). The prognostic nomogram based on this model yielded a probability of achieving an R1 resection ranging from <5% (0 factors) to >70% (all 5 factors). Conclusions Relevant preoperative clinicopathological characteristics accurately predict positive resection margins in patients with BR/LA PDAC before resection. With further development, this model might be used to preoperatively guide surgical decision-making in patients with BR/LA PDAC.
Adherence to highly active antiretroviral therapy among people living with HIV and associated high-risk behaviours and clinical characteristics: A cross-sectional survey in Vietnam

Although Vietnam has promoted the utilisation of highly active antiretroviral therapy (HAART) towards HIV elimination targets, adherence to treatment has remained under-investigated. We aimed to describe high-risk behaviours and clinical characteristics by adherence status and to identify the factors associated with non-adherence. We included 426 people living with HIV (PLWH) currently or previously involved in HAART. Most participants were men (75.4%), young (33.6 years), with low income and low education levels. Non-adherent PLWH (11.5%) were more likely to have a larger number of sex partners (p-value = 0.053), sex without condom use (p-value = 0.007) and not receive result at hospital or voluntary test centre (p-value = 0.001). Multiple logistic regression analysis showed that demographic (education levels), sexual risk behaviours (multiple sex partners and sex without using condom) and clinical characteristics (time and facility at first time received HIV-positive result) were associated with HAART non-adherence. There are differences in associated factors between women (education levels and place of HIV testing) and men (multiple sex partners). Gender-specific programs, changing risky behaviours and reducing harms among PLWH may benefit adherence. We highlight the need to improve the quantity and quality of HIV/AIDS services in Vietnam, especially in pre- and post-test counselling, to achieve better HAART adherence, working towards ending AIDS in 2030.
Stability and Synchronization of Nonautonomous Reaction–Diffusion Neural Networks With General Time-Varying Delays

This article investigates the stability and synchronization of nonautonomous reaction–diffusion neural networks with general time-varying delays. Compared with the existing works concerning reaction–diffusion neural networks, the main innovation of this article is that the network coefficients are time-varying, and the delays are general (which means that fewer constraints are posed on delays; for example, the commonly used conditions of differentiability and boundedness are no longer needed). By Green’s formula and some analytical techniques, some easily checkable criteria on stability and synchronization for the underlying neural networks are established. These obtained results not only improve some existing ones but also contain some novel results that have not yet been reported. The effectiveness and superiorities of the established criteria are verified by three numerical examples.
Symbiont Genomic Features and Localization in the Bean Beetle Callosobruchus maculatus

From supplementing essential nutrients to detoxifying plant secondary metabolites and insecticides, bacterial symbionts are a key source of adaptations for herbivorous insect pests. Despite the pervasiveness and geographical range of the bean beetle, Callosobruchus maculatus, the role of microbial symbioses in its natural history remains understudied. ABSTRACT A pervasive pest of stored leguminous products, the bean beetle Callosobruchus maculatus (Coleoptera: Chrysomelidae) associates with a simple bacterial community during adulthood. Despite its economic importance, little is known about the compositional stability, heritability, localization, and metabolic potential of the bacterial symbionts of C. maculatus. In this study, we applied community profiling using 16S rRNA gene sequencing to reveal a highly conserved bacterial assembly shared between larvae and adults. Dominated by Firmicutes and Proteobacteria, this community is localized extracellularly along the epithelial lining of the bean beetle’s digestive tract. Our analysis revealed that only one species, Staphylococcus gallinarum (phylum Firmicutes), is shared across all developmental stages. Isolation and whole-genome sequencing of S. gallinarum from the beetle gut yielded a circular chromosome (2.8 Mb) and one plasmid (45 kb). The strain encodes complete biosynthetic pathways for the production of B vitamins and amino acids, including tyrosine, which is increasingly recognized as an important symbiont-supplemented precursor for cuticle biosynthesis in beetles. A carbohydrate-active enzyme search revealed that the genome codes for a number of digestive enzymes, reflecting the nutritional ecology of C. maculatus. The ontogenic conservation of the gut microbiota in the bean beetle, featuring a “core” community composed of S. gallinarum, may be indicative of an adaptive role for the host. In clarifying symbiont localization and metabolic potential, we further our understanding and study of a costly pest of stored products. IMPORTANCE From supplementing essential nutrients to detoxifying plant secondary metabolites and insecticides, bacterial symbionts are a key source of adaptations for herbivorous insect pests. Despite the pervasiveness and geographical range of the bean beetle Callosobruchus maculatus, the role of microbial symbioses in its natural history remains understudied. Here, we demonstrate that the bean beetle harbors a simple gut bacterial community that is stable throughout development. This community localizes along the insect’s digestive tract and is largely dominated by Staphylococcus gallinarum. In elucidating symbiont metabolic potential, we highlight its possible adaptive significance for a widespread agricultural pest.
Association between white matter hyperintensity load and grey matter atrophy in mild cognitive impairment is not unidirectional

Neuroimaging measures of Alzheimer’s disease (AD) include grey matter volume (GMV) alterations in the Default Mode Network (DMN) and Executive Control Network (ECN). Small-vessel cerebrovascular disease, often visualised as white matter hyperintensities (WMH) on MRI, is often seen in AD. However, the relationship between WMH load and GMV needs further examination. We examined the load-dependent influence of WMH on GMV and cognition in 183 subjects. T1-MRI data from 93 Mild Cognitive Impairment (MCI) and 90 cognitively normal subjects were studied and WMH load was categorized into low, medium and high terciles. We examined how differing loads of WMH related to whole-brain voxel-wise and regional DMN and ECN GMV. We further investigated how regional GMV moderated the relationship between WMH and cognition. We found differential load-dependent effects of WMH burden on voxel-wise and regional atrophy in only MCI. At high load, as expected WMH negatively related to both ECN and DMN GMV, however at low load, WMH positively related to ECN GMV. Additionally, negative associations between WMH and memory and executive function were moderated by regional GMV. Our results demonstrate non-unidirectional relationships between WMH load, GMV and cognition in MCI.
Prediagnostic use of estrogen-only therapy is associated with improved colorectal cancer survival in menopausal women: a Swedish population-based cohort study

Abstract Background Menopausal hormone therapy (MHT) reduces the risk of developing colorectal cancer (CRC), yet it is largely unclear whether it could also influence survival in women with CRC. Therefore, we aimed to investigate the influence of prediagnostic MHT use on CRC-specific and all-cause mortality in women with CRC. Methods This nationwide nested cohort study, within a large population-based matched cohort, included all women diagnosed with incident CRC between January 2006 and December 2012 (N = 7814). A total of 1529 women had received at least one dispensed prescription of systemic MHT before CRC diagnosis, and 6285 CRC women with CRC did not receive MHT during the study period, as ascertained from the Swedish Prescribed Drug Registry. Multivariable Cox regression models provided adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for CRC-specific mortality and all-cause mortality. Results Past use of prediagnostic estrogen-only therapy (E-MHT) was associated with lower CRC-specific (HR = 0.67, 95%CI 0.44–0.99) and all-cause mortality (HR = 0.68, 95%CI 0.59–0.93). However, all-cause mortality (HR = 1.23, 95%CI 1.02–1.48) was elevated among current prediagnostic E-MHT users who were 70+ years at diagnosis. Current estrogen combined progestin therapy (EP-MHT) was associated with higher CRC-specific mortality (HR = 1.61, 95%CI 1.06–2.44) in older women, but no association was shown for all-cause mortality. Conclusions Our findings suggest that E-MHT, but not EP-MHT use, might be associated with improved CRC survival, indicating a potential role of estrogens in sex hormone-related cancers. However, association of MHT use with grade of cancer remains unclear.
Differential recognition of HIV-stimulated IL-1β and IL-18 secretion through NLR and NAIP signalling in monocyte-derived macrophages

Macrophages are important drivers of pathogenesis and progression to AIDS in HIV infection. The virus in the later phases of the infection is often predominantly macrophage-tropic and this tropism contributes to a chronic inflammatory and immune activation state that is observed in HIV patients. Pattern recognition receptors of the innate immune system are the key molecules that recognise HIV and mount the inflammatory responses in macrophages. The innate immune response against HIV-1 is potent and elicits caspase-1-dependent pro-inflammatory cytokine production of IL-1β and IL-18. Although, NLRP3 has been reported as an inflammasome sensor dictating this response little is known about the pattern recognition receptors that trigger the “priming” signal for inflammasome activation, the NLRs involved or the HIV components that trigger the response. Using a combination of siRNA knockdowns in monocyte derived macrophages (MDMs) of different TLRs and NLRs as well as chemical inhibition, it was demonstrated that HIV Vpu could trigger inflammasome activation via TLR4/NLRP3 leading to IL-1β/IL-18 secretion. The priming signal is triggered via TLR4, whereas the activation signal is triggered by direct effects on Kv1.3 channels, causing K+ efflux. In contrast, HIV gp41 could trigger IL-18 production via NAIP/NLRC4, independently of priming, as a one-step inflammasome activation. NAIP binds directly to the cytoplasmic tail of HIV envelope protein gp41 and represents the first non-bacterial ligand for the NAIP/NLRC4 inflammasome. These divergent pathways represent novel targets to resolve specific inflammatory pathologies associated with HIV-1 infection in macrophages.
Evaluation of the relationship between laboratory parameters and pulmonary function tests in COVID‐19 patients

The novel coronavirus SARS‐CoV‐2 (COVID‐19) rapidly escalated from its origin in an animal market in Wuhan, China in December 2019 to a global pandemic, and the lungs are the most frequently affected organ. The aim of this study was to investigate the relationship between pulmonary function test parameters and laboratory parameters in COVID‐19.
Antimicrobial and resource utilization with T2 magnetic resonance for rapid diagnosis of bloodstream infections: systematic review with meta-analysis of controlled studies

ABSTRACT Objectives: To compare antimicrobial and resource utilization with T2 Magnetic Resonance (T2MR) versus blood culture (BC) in patients with suspected bloodstream infection. Methods: We systematically searched MEDLINE, EMBASE, and CENTRAL for randomized trials or observational controlled studies of patients with suspected bloodstream infection receiving a diagnosis with T2MR or BC. Using an inverse variance meta-analysis model, we reported mortality using the risk ratio (RR) and the remaining outcomes as the mean difference (MD). Results: Fourteen studies were included in the meta-analysis. Time to detection (MD = −81 hours; p < 0.001) and time to species identification (MD = −77 hours; p < 0.001) were faster with T2MR. Patients testing positive on T2MR received targeted antimicrobial therapy faster (−42 hours; p < 0.001) and patients testing negative on T2MR were de-escalated from empirical therapy faster (−7 hours; p = 0.02) vs. BC. Length of intensive care unit stay (MD = −5.0 days; p = 0.03) and hospital stay (MD = −4.8 days; p = 0.03) were shorter with T2MR. Mortality rates were comparable between T2MR and BC (28.9% vs. 29.9%, RR = 1.02, p = 0.86). Conclusion: Utilization of T2MR for identification of bloodstream pathogens provides faster time to detection, faster transition to targeted microbial therapy, faster de-escalation of empirical therapy, shorter ICU and hospital stay, and with comparable mortality rate versus BC.
Improving the design of an oxidative stress sensing biosensor in yeast

ABSTRACT Transcription factor (TF)-based biosensors have proven useful for increasing biomanufacturing yields, large-scale functional screening, and in environmental monitoring. Most yeast TF-based biosensors are built from natural promoters, resulting in large DNA parts retaining considerable homology to the host genome, which can complicate biological engineering efforts. There is a need to explore smaller, synthetic biosensors to expand the options for regulating gene expression in yeast. Here, we present a systematic approach to improving the design of an existing oxidative stress sensing biosensor in Saccharomyces cerevisiae based on the Yap1 transcription factor. Starting from a synthetic core promoter, we optimized the activity of a Yap1-dependent promoter through rational modification of a minimalist Yap1 upstream activating sequence. Our novel promoter achieves dynamic ranges of activation surpassing those of the previously engineered Yap1-dependent promoter, while reducing it to only 171 base pairs. We demonstrate that coupling the promoter to a positive-feedback-regulated TF further improves the biosensor by increasing its dynamic range of activation and reducing its limit of detection. We have illustrated the robustness and transferability of the biosensor by reproducing its activity in an unconventional probiotic yeast strain, Saccharomyces boulardii. Our findings can provide guidance in the general process of TF-based biosensor design.