Miracle-dz/UniFAR-FTUs huggingface dataset:
ElNoury–Webster bundle: a preemptive surgical approach with a modified lower B-Lynch compression suture to manage morbidly low or adherent placenta

Abstract Objective To report the technique and outcomes of a surgical care bundle, which preemptively and prophylactically reduces intrapartum bleeding during cesarean sections for these conditions and hence reducing the risk for a cesarean hysterectomy. Methods In this report, we present the surgical and clinical outcomes of a case series of 16 patients presenting with a morbidly low or adherent placenta on whom this technique was piloted. Results Seven of the sixteen patients (44%) required a blood transfusion ranging from 1 to 5 units of packed RBCs. None of the neonates required neonatal unit admissions. One woman had a subsequent pregnancy, with normal placentation and an uncomplicated delivery by cesarean section. None of the patients in our series had a hysterectomy, needed to return to theater after the initial surgery or had secondary postpartum hemorrhage. Conclusions The ElNoury–Webster Bundle is a stepwise surgical technique for the conservative management of morbidly low or adherent placenta particularly in low and middle-income healthcare settings.
Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values

Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guide decisions such as intensive-care unit admission (ICUA). The objective of this study is two-fold, one substantive and one methodological: substantively to evaluate the association of demographic and health records with two related, yet different, outcomes of severe COVID-19 (viz., death and ICUA); methodologically to compare interpretations based on logistic regression and on gradient-boosted decision tree (GBDT) predictions interpreted by means of the Shapley impacts of covariates. Very different association of some factors, e.g., obesity and chronic respiratory diseases, with death and ICUA may guide review of practice. Shapley explanation of GBDTs identified varying effects of some factors among patients, thus emphasising the importance of individual patient assessment. The results of this study are also relevant for the evaluation of complex automated clinical decision systems, which should optimise prediction scores whilst remaining interpretable to clinicians and mitigating potential biases.
Prevalence and risk factors of depression symptoms among Chinese seafarers during the COVID-19 pandemic: a cross-sectional study

Background To curb the spread of COVID-19, most countries have adopted measures such as banning shore leave at ports and placed restrictions on crew change. Seafarers may bear an excess pressure during the COVID-19 pandemic. This study aimed to investigate the prevalence and risk factors associated with depression symptoms among Chinese seafarers during the COVID-19 pandemic. Design Cross-sectional study. Methods This field survey-based study was conducted at Rongcheng Port, Shandong Province, China, from 10 June 2020 to 25 July 2020. Sociodemographic and occupational characteristics and health-related behaviours were collected through a face-to-face questionnaire. The Self-Rating Depression Scale was used to evaluate depression status during the preceding week. Logistic regression models were used to explore factors related to depression. Results 441 male Chinese seafarers were enrolled. Overall, the proportions of seafarers with low, moderate and severe depression symptoms were 23.35%, 9.30% and 9.07%, respectively. Compared with those with good self-rated health (SRH), seafarers with poor SRH had higher odds of depression (OR, 2.24, 95% CI 1.22 to 4.11). Less leisure time or physical exercise was associated with more severe self-reported depression symptoms (1–3 per week vs ≥4 per week: OR, 1.72, 95% CI 0.71 to 4.14; none vs ≥4 per week: OR, 3.93, 95% CI 1.67 to 9.26). Poor sleep quality was associated with higher likelihood of reporting severe depression (fair vs good: OR, 2.78, 95% CI 1.54 to 5.01; poor vs good: OR, 4.30, 95% CI 1.65 to 11.24). The more frequent seafarers worked overtime a week, the higher the likelihood of reporting severe depression symptoms (1–2 per week vs none: OR, 1.82, 95% CI 1.04 to 3.18; ≥3 per week vs none: OR, 2.49, 95% CI 1.05 to 5.92). Also, high perceived work stress was linked to higher odds of being depressed (intermediate vs low: OR, 2.06, 95% CI 0.78 to 5.46; high vs low: OR, 3.83, 95% CI 1.35 to 10.90). Conclusions There is a high burden of depression associated with COVID-19 among seafarers. Special interventions that protect the mental health of seafarers are more critical than ever in the context of the pandemic.
Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types.

Leaf trait relationships are widely used to predict ecosystem function in Terrestrial Biosphere Models (TBMs), in which leaf maximum carboxylation capacity (Vc,max ), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-Vc,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (Vc,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between Vc,max and the four morphological and biochemical traits (R2 ≤0.15), indicated by significantly changing slopes and intercepts across forest types. In contrast, reflectance spectroscopy effectively collapsed the differences in the trait-Vc,max relationships across three forest biomes into a single robust model for Vc,max (R2 =0.77), and also accurately estimated the four traits (R2 =0.75-0.94). These findings challenge the traditional use of empirical trait-Vc,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterizing Vc,max and multi-trait variability, with critical insights into ecosystem modeling and functional trait ecology.
What Is the Failure Rate After Arthroscopic Repair of Bucket-Handle Meniscal Tears? A Systematic Review and Meta-analysis

Background: Meniscal repair has become the treatment of choice for meniscal tears, especially in the subset of bucket-handle meniscal tears (BHMTs). However, a comprehensive estimate of the corresponding failure rate is not available, thus maintaining doubts about the healing potential of these tears. Furthermore, a wide range of factors to predict high failure rates have been reported but with conflicting evidence. Purpose: To determine the failure rate after arthroscopic repair of BHMTs as reported in the literature, compare this with the failure rate of simple meniscal tears extracted from the same studies, and analyze the influence of factors previously reported to be predictive of meniscal repair failure. Study Design: Systematic review and meta-analysis; Level of evidence, 4. Methods: A systematic search was conducted by 2 independent reviewers using principal bibliographic databases (PubMed, Scopus, Cochrane Library, and EMBASE). After a stepwise exclusion process, 38 articles met the inclusion criteria. Failure rate data were analyzed with a random-effects proportional meta-analysis (weighted for individual study size), and forest plots were constructed to determine any statistically significant differences between BHMTs versus simple tears (longitudinal, radial, or horizontal), medial versus lateral BHMTs, isolated procedures versus repairs with concomitant anterior cruciate ligament reconstruction, and tears in red-red versus red-white zones. Moreover, a meta-regression analysis was conducted to evaluate the effect of patient age and sex, suture technique (in-out or all-inside), time from injury to surgery, mean number of stitches, and length of follow-up on failure rates. Results: The pooled failure rate was 14.8% (95% CI, 11.3%-18.3%; I2 = 77.2%). A total of 17 studies provided failure rates of both BHMT repairs (46/311 repairs) and simple tear repairs (54/546 repairs), demonstrating a significantly higher failure rate for BHMT repairs (risk ratio [RR] = 1.50; 95% CI, 1.05-2.15; I2 = 0%; P = .03). Medial BHMT repairs (RR = 1.94; 95% CI, 1.25-3.01; I2 = 0%; P = .003) and isolated repairs (RR = 1.77; 95% CI, 1.15-2.72; I2 = 0%; P = .009) had statistically higher risk of failure, but no statistically significant difference was found between tears in red-red versus red-white zones. Among the other factors evaluated with meta-regression, only the mean number of stitches showed a statistically significant effect on failure rates. Conclusion: Based on the currently available literature, this systematic review provides a reasonably comprehensive analysis of failure rate after arthroscopic BHMT repair; failure is estimated to occur in 14.8% of cases. Medial tears and isolated repairs were the 2 major predictors of failure.
Prognosis of Patients With Early Breast Cancer Receiving 5 Years vs 2 Years of Adjuvant Bisphosphonate Treatment: A Phase 3 Randomized Clinical Trial.

Importance Bisphosphonate treatment in patients with early breast cancer has become part of care, but the optimal treatment duration is still unclear. Objective To compare 2 vs 5 years of zoledronate treatment following adjuvant chemotherapy in patients with early breast cancer. Design, Setting, and Participants The SUCCESS A phase 3 multicenter randomized open-label clinical trial with a 2 × 2 factorial design enrolled 3754 patients from September 21, 2005, to March 12, 2007 (last patient out, May 7, 2014). Final data analysis was conducted from September 2019 to October 2020. In 250 German study centers, patients were eligible for participation in the SUCCESS A trial if they had either node-positive or high-risk node-negative (defined as at least 1 of the following: tumor size ≥ pT2, histologic grade 3, negative hormone receptor status, or age ≤35 years) primary invasive breast cancer. Interventions Patients were first randomized to adjuvant chemotherapy with 3 cycles of fluorouracil, epirubicin, and cyclophosphamide followed by 3 cycles of docetaxel with or without gemcitabine (not presented in this report). After chemotherapy, patients underwent a second randomization of 5 years of zoledronate treatment (4 mg intravenously every 3 months for 2 years, followed by 4 mg intravenously every 6 months for 3 years) vs 2 years of zoledronate treatment (4 mg intravenously every 3 months for 2 years). Main Outcomes and Measures The primary end point of the study was disease-free survival; secondary end points were overall survival, distant disease-free survival, and the incidence of skeletal-related adverse events. Survival times were measured from 2 years after the start of zoledronate treatment (landmark analysis). Results Overall, data on 2987 patients were available for analysis; median age was 53 (range, 21-86) years. Disease-free survival, overall survival, and distant disease-free survival did not differ significantly between the 2 treatment arms (5 vs 2 years) as shown by adjusted multivariable Cox proportional hazards regression models (disease-free survival: hazard ratio [HR], 0.97; 95% CI, 0.75-1.25; P = .81; overall survival: HR, 0.98; 95% CI, 0.67-1.42; P = .90; distant disease-free survival: HR, 0.87; 95% CI, 0.65-1.18; P = .38). Adverse events were observed more often in the 5-year (46.2%) vs 2-year (27.2%) zoledronate treatment arm, which was particularly true for the skeletal-related events bone pain (5 years, 8.3% vs 2 years, 3.7%) and arthralgia (5 years, 5.1% vs 2 years, 3.1%). Conclusions and Relevance The results of this phase 3 randomized clinical trial indicate that extending the zoledronate treatment beyond 2 years does not improve the prognosis of high-risk patients with early breast cancer receiving chemotherapy, suggesting that the currently recommended bisphosphonate treatment duration of 3 to 5 years could be reduced. Trial Registration ClinicalTrials.gov Identifier: NCT02181101.
The association of in utero tobacco smoke exposure, quantified by serum cotinine, and Autism Spectrum Disorder

Previous studies on in utero exposure to maternal environmental tobacco smoke (ETS) or maternal active smoking and Autism Spectrum Disorder (ASD) have not been entirely consistent, and no studies have examined in utero cotinine concentrations as an exposure classification method. We measured cotinine in stored second trimester maternal serum for 498 ASD cases and 499 controls born in California in 2011–2012. We also obtained self‐reported maternal cigarette smoking during and immediately prior to pregnancy, as well as covariate data, from birth records. Using unconditional logistic regression, we found no association between log10 cotinine concentrations and odds for developing ASD among children of non‐smokers (aOR: 0.93 [95% CI: 0.69, 1.25] per ng/ml), which represents exposure to ETS, though there may be a possible interaction with race. We found no association between cotinine‐defined smoking (≥3.08 ng/ml vs. <3.08 ng/ml) (adjusted odds ratio [aOR]: 0.73 (95% confidence interval [95% CI]: 0.35, 1.54)) or self‐reported smoking (aOR: 1.64 [95% CI: 0.65, 4.16]) and ASD. In one of the few studies of ETS and the first with measured cotinine, our results indicate no overall relationship between in utero exposure to tobacco smoke from maternal ETS exposure or active smoking, and development of ASD.
Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis

Background This study sought to assess the prognostic factors for leiomyosarcoma (LMS) patients with lung metastasis and construct web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS). Method Patients diagnosed with LMS combined with lung metastasis between 2010 and 2016 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into a training set and a testing set. The X-tile analysis provides the best age and tumor size cut-off point, and changes continuous variables into categorical variables. The independent prognostic factors were determined by Cox regression analysis, and 2 nomograms were established. Receiver operating characteristic curves and calibration curves were used to evaluate the nomograms. Based on the nomograms, 2 web-based nomograms were established. Results Two hundred and twenty-eight cases were included in the OS nomogram construction, and were randomly divided into a training set (n=160) and a validation set (n=68). Age, T stage, bone metastasis, surgery, chemotherapy, marital status, tumor size, and tumor site were found to be correlated with OS. One hundred and eighty-three cases were enrolled in the CSS nomogram construction, and randomly divided into a training set (n=129) and a validation set (n=54). Age, bone metastasis, surgery, chemotherapy, tumor size, and tumor site were found to be correlated with CSS. Two nomograms were established to predict OS and CSS. In the training set, the areas under the curve of the nomogram for predicting 1-, 2-, and 3-year OS were 0.783, 0.830, and 0.832, respectively, and those for predicting 1-, 2-, and 3-year CSS were 0.889, 0.777, and 0.884, respectively. Two web-based nomograms were established to predict OS (https://wenn23.shinyapps.io/lmslmosapp/), and CSS (https://wenn23.shinyapps.io/lmslmcssapp/). Conclusion The developed web-based nomogram is a useful tool for accurately analyzing the prognosis of LMS patients with lung metastasis, and could help clinical doctors to make personalized clinical decisions.
Oleuropein-Induced Acceleration of Cytochrome P450–Catalyzed Drug Metabolism: Central Role for Nuclear Receptor Peroxisome Proliferator-Activated Receptor α

Oleuropein (OLE), the main constituent of Olea europaea, displays pleiotropic beneficial effects in health and disease, which are mainly attributed to its anti-inflammatory and cardioprotective properties. Several food supplements and herbal medicines contain OLE and are available without a prescription. This study investigated the effects of OLE on the main cytochrome P450s (P450s) catalyzing the metabolism of many prescribed drugs. Emphasis was given to the role of peroxisome proliferator-activated receptor α (PPARα), a nuclear transcription factor regulating numerous genes including P450s. 129/Sv wild-type and Ppara-null mice were treated with OLE for 6 weeks. OLE induced Cyp1a1, Cyp1a2, Cyp1b1, Cyp3a14, Cyp3a25, Cyp2c29, Cyp2c44, Cyp2d22, and Cyp2e1 mRNAs in liver of wild-type mice, whereas no similar effects were observed in Ppara-null mice, indicating that the OLE-induced effect on these P450s is mediated by PPARα. Activation of the pathways related to phosphoinositide 3-kinase/protein kinase B (AKT)/forkhead box protein O1, c-Jun N-terminal kinase, AKT/p70, and extracellular signal-regulated kinase participates in P450 induction by OLE. These data indicate that consumption of herbal medicines and food supplements containing OLE could accelerate the metabolism of drug substrates of the above-mentioned P450s, thus reducing their efficacy and the outcome of pharmacotherapy. Therefore, OLE-induced activation of PPARα could modify the effects of drugs due to their increased metabolism and clearance, which should be taken into account when consuming OLE-containing products with certain drugs, in particular those of narrow therapeutic window. SIGNIFICANCE STATEMENT This study indicated that oleuropein, which belongs to the main constituents of the leaves and olive drupes of Olea europaea, induces the synthesis of the major cytochrome P450s (P450s) metabolizing the majority of prescribed drugs via activation of peroxisome proliferator-activated receptor α. This effect could modify the pharmacokinetic profile of co-administered drug substrates of the P450s, thus altering their therapeutic efficacy and toxicity.
Prediction of the number of metastatic axillary lymph nodes in breast cancer by radiomic signature based on dynamic contrast-enhanced MRI

Background The number of metastatic axillary lymph nodes (ALNs) play a crucial role in the staging, prognosis and therapy of patients with breast cancer. Purpose To predict the number of metastatic ALNs in breast cancer via radiomics. Material and Methods We enrolled 197 patients with breast cancer who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 3386 radiomic features were extracted from the early- and delayed-phase subtraction images. To classify the number of metastatic ALNs, logistic regression was used to develop a radiomic signature and nomogram. Results The radiomic signature were constructed to distinguish the N0 group from the N+ (metastatic ALNs ≥ 1) group, which yielded area under the curve (AUC) values of 0.82 and 0.81 in the training and test group, respectively. Based on the radiomic signature and BI-RADS category, a nomogram was further developed and showed excellent predictive performance with AUC values of 0.85 and 0.89 in the training and test groups, respectively. Another radiomic signature was constructed to distinguish the N1 (1–3 ALNs) group from the N2–3 (≥4 metastatic ALNs) group and showed encouraging performance with AUC values of 0.94 and 0.84 in training and test group, respectively. Conclusions We developed a nomogram and a radiomic signature that can be used to predict ALN metastasis and distinguish the N1 from the N2-3 group. Both nomogram and radiomic signature may be potential tools to assist clinicians in assessing ALN metastasis in patients with breast cancer.
Telocytes: An Emerging Component of Stem Cell Niche Microenvironment

Telocytes (TCs) are newly identified interstitial cells characterized by thin and long cytoplasmic processes, called telopodes, which exhibit a distinctive moniliform shape and, often, a sinuous trajectory. Telopodes typically organize in intricate networks within the stromal space of most organs, where they communicate with neighboring cells by means of specialized cell-to-cell junctions or shedding extracellular vesicles. Hence, TCs are generally regarded as supporting cells that help in the maintenance of local tissue homeostasis, with an ever-increasing number of studies trying to explore their functions both in physiological and pathological conditions. Notably, TCs appear to be part of stem cell (SC) niches in different organs, including the intestine, skeletal muscle, heart, lung, and skin. Indeed, growing evidence points toward a possible implication of TCs in the regulation of the activity of tissue-resident SCs and in shaping the SC niche microenvironment, thus contributing to tissue renewal and repair. Here, we review how the introduction of TCs into the scientific literature has deepened our knowledge of the stromal architecture focusing on the intestine and skeletal muscle, two organs in which the recently unveiled unique relationship between TCs and SCs is currently in the spotlight as potential target for tissue regenerative purposes.
Learning an Efficient Hippocampal Place Map from Entorhinal Inputs Using Non-Negative Sparse Coding

Abstract Cells in the entorhinal cortex (EC) contain rich spatial information and project strongly to the hippocampus where a cognitive map is supposedly created. These cells range from cells with structured spatial selectivity, such as grid cells in the medial EC (MEC) that are selective to an array of spatial locations that form a hexagonal grid, to weakly spatial cells, such as non-grid cells in the MEC and lateral EC (LEC) that contain spatial information but have no structured spatial selectivity. However, in a small environment, place cells in the hippocampus are generally selective to a single location of the environment, while granule cells in the dentate gyrus of the hippocampus have multiple discrete firing locations but lack spatial periodicity. Given the anatomic connection from the EC to the hippocampus, how the hippocampus retrieves information from upstream EC remains unclear. Here, we propose a unified learning model that can describe the spatial tuning properties of both hippocampal place cells and dentate gyrus granule cells based on non-negative sparse coding from EC inputs. Sparse coding plays an important role in many cortical areas and is proposed here to have a key role in the hippocampus. Our results show that the hexagonal patterns of MEC grid cells with various orientations, grid spacings and phases are necessary for the model to learn different place cells that efficiently tile the entire spatial environment. However, if there is a lack of diversity in any grid parameters or a lack of hippocampal cells in the network, this will lead to the emergence of hippocampal cells that have multiple firing locations. More surprisingly, the model can also learn hippocampal place cells even when weakly spatial cells, instead of grid cells, are used as the input to the hippocampus. This work suggests that sparse coding may be one of the underlying organizing principles for the navigational system of the brain.