Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital whole-community phenotyping: tracking morphological and physiological responses of plant communities to environmental changes in the field

Plant traits are informative for ecosystem functions and processes and help to derive general rules and predictions about responses to environmental gradients, global change and perturbations. Ecological field studies often use ‘low-throughput’ methods to assess plant phenotypes and integrate species-specific traits to community-wide indices. In contrast, agricultural greenhouse or lab-based studies often employ ‘high-throughput phenotyping’ to assess plant individuals tracking their growth or fertilizer and water demand. In ecological field studies, remote sensing makes use of freely movable devices like satellites or unmanned aerial vehicles (UAVs) which provide large-scale spatial and temporal data. Adopting such methods for community ecology on a smaller scale may provide novel insights on the phenotypic properties of plant communities and fill the gap between traditional field measurements and airborne remote sensing. However, the trade-off between spatial resolution, temporal resolution and scope of the respective study requires highly specific setups so that the measurements fit the scientific question. We introduce small-scale, high-resolution digital automated phenotyping as a novel source of quantitative trait data in ecological field studies that provides complementary multi-faceted data of plant communities. We customized an automated plant phenotyping system for its mobile application in the field for ‘digital whole-community phenotyping’ (DWCP), capturing the 3-dimensional structure and multispectral information of plant communities. We demonstrated the potential of DWCP by recording plant community responses to experimental land-use treatments over two years. DWCP captured changes in morphological and physiological community properties in response to mowing and fertilizer treatments and thus reliably informed about changes in land-use. In contrast, manually measured community-weighted mean traits and species composition remained largely unaffected and were not informative about these treatments. DWCP proved to be an efficient method for characterizing plant communities, complements other methods in trait-based ecology, provides indicators of ecosystem states, and may help to forecast tipping points in plant communities often associated with irreversible changes in ecosystems.
Plasma virome dynamics in chronic hepatitis B virus infected patients

The virome remains an understudied domain of the human microbiome. The role of commensal viruses on the outcome of infections with known pathogens is not well characterized. In this study we aimed to characterize the longitudinal plasma virome dynamics in chronic hepatitis B virus (HBV) infected patients. Eighty-five longitudinal plasma samples were collected from 12 chronic HBV infected individuals that were classified in the four stages of HBV infection. The virome was characterized with an optimized viral extraction protocol and deep-sequenced on a NextSeq 2500 platform. The plasma virome was primarily composed of members of the Anello- Flavi-, and Hepadnaviridae (HBV) families. The virome structure and dynamics did not correlate with the different stages of chronic HBV infection nor with the administration of antiviral therapy. We observed a higher intrapersonal similarity of viral contigs. Genomic analysis of viruses observed in multiple timepoint demonstrated the presence of a dynamic community. This study comprehensively assessed the blood virome structure in chronic HBV infected individuals and provided insights in the longitudinal development of this viral community.
A novel approach for assessing bias during team-based clinical decision-making

Many clinical processes include multidisciplinary group decision-making, yet few methods exist to evaluate the presence of implicit bias during this collective process. Implicit bias negatively impacts the equitable delivery of evidence-based interventions and ultimately patient outcomes. Since implicit bias can be difficult to assess, novel approaches are required to detect and analyze this elusive phenomenon. In this paper, we describe how the de Groot Critically Reflective Diagnoses Protocol (DCRDP) can be used as a data analysis tool to evaluate group dynamics as an essential foundation for exploring how interactions can bias collective clinical decision-making. The DCRDP includes 6 distinct criteria: challenging groupthink, critical opinion sharing, research utilization, openness to mistakes, asking and giving feedback, and experimentation. Based on the strength and frequency of codes in the form of exemplar quotes, each criterion was given a numerical score of 1–4 with 1 representing teams that are interactive, reflective, higher functioning, and more equitable. When applied as a coding scheme to transcripts of recorded decision-making meetings, the DCRDP was revealed as a practical tool for examining group decision-making bias. It can be adapted to a variety of clinical, educational, and other professional settings as an impetus for recognizing the presence of team-based bias, engaging in reflexivity, informing the design and testing of implementation strategies, and monitoring long-term outcomes to promote more equitable decision-making processes in healthcare.
Alkaline ceramidase (ClAC) inhibition enhances heat stress response in Cyrtorhinus lividipennis (Reuter)

Ceramidases (CDases) are vital sphingolipid enzymes involved in organismal growth and development. They have been reported as key mediators of thermal stress response. However, whether and how CDase responds to heat stress in insects remain unclear. Herein, we identified two CDase genes, C. lividipennis alkaline ceramidase (ClAC) and neutral ceramidase (ClNC), by searching the transcriptome and genome databases of the mirid bug, Cyrtorhinus lividipennis, an important natural predator of planthoppers. Quantitative PCR (qPCR) analysis showed that both ClNC and ClAC were highly expressed in nymphs than in adults. ClAC was especially highly expressed in the head, thorax, and legs, while ClNC was widely expressed in the tested organs. Only the ClAC transcription was significantly affected by heat stress. Knocking down ClAC increased the C. lividipennis nymph survival rate under heat stress. The transcriptome and lipidomics data showed that the RNA interference-mediated suppression of ClAC significantly upregulated the transcription level of catalase (CAT) and the content of long-chain base ceramides, including C16-, C18-, C24-, and C31- ceramides. In C. lividipennis nymphs, ClAC played an important role in heat stress response, and the upregulation of nymph survival rate might be caused by variation in the ceramide levels and transcriptional changes in CDase downstream genes. This study improves our understanding of the physiological functions of insect CDase under heat stress and provides valuable insights into the nature enemy application.
Chronic epididymitis due to Chlamydia trachomatis LGV-L2 in an HIV-negative heterosexual patient: a case report

Chlamydia trachomatis is an obligate intracellular pathogen and the leading bacterial cause of sexually transmitted infections worldwide. Chlamydia trachomatis genovars L1–L3 are responsible for lymphogranuloma venereum (LGV), an invasive sexually transmitted disease endemic in tropical and subtropical regions of Africa, South America, the Caribbean, India and South East Asia. The typical signs and symptoms of C. trachomatis LGV urogenital infections in men include herpetiform ulcers, inguinal buboes, and/or lymphadenopathies. Since 2003, endemic cases of proctitis and proctocolitis caused by C. trachomatis LGV emerged in Europe, mainly in HIV-positive men who have sex with men (MSM). Scarce data have been reported about unusual clinical presentations of C. trachomatis LGV urogenital infections. Herein, we report a case of a 36-year-old heterosexual, HIV-negative male declaring he did not have sex with men or trans women, who presented to the Urology and Andrology outpatient clinic of a healthcare center from Cordoba, Argentina, with intermittent testicular pain over the preceding 6 months. Doppler ultrasound indicated right epididymitis and funiculitis. Out of 17 sexually transmitted infections (STIs) investigated, a positive result was obtained only for C. trachomatis. Also, semen analysis revealed oligoasthenozoospermia, reduced sperm viability as well as increased sperm DNA fragmentation and necrosis, together with augmented reactive oxygen species (ROS) levels and the presence of anti-sperm IgG autoantibodies. In this context, doxycycline 100 mg/12 h for 45 days was prescribed. A post-treatment control documented microbiological cure along with resolution of clinical signs and symptoms and improved semen quality. Strikingly, sequencing of the ompA gene revealed C. trachomatis LGV L2 as the causative uropathogen. Remarkably, the patient did not present the typical signs and symptoms of LGV. Instead, the infection associated with chronic testicular pain, semen inflammation and markedly reduced sperm quality. To our knowledge, this is the first reported evidence of chronic epididymitis due to C. trachomatis LGV L2 infection in an HIV-negative heterosexual man. These findings constitute important and valuable information for researchers and practitioners and highlight that C. trachomatis LGV-L2 should be considered as putative etiologic agent of chronic epididymitis, even in the absence of the typical LGV signs and symptoms.
CNVs in 8q24.3 do not influence gene co-expression in breast cancer subtypes

Gene co-expression networks are a useful tool in the study of interactions that have allowed the visualization and quantification of diverse phenomena, including the loss of co-expression over long distances in cancerous samples. This characteristic, which could be considered fundamental to cancer, has been widely reported in various types of tumors. Since copy number variations (CNVs) have previously been identified as causing multiple genetic diseases, and gene expression is linked to them, they have often been mentioned as a probable cause of loss of co-expression in cancerous networks. In order to carry out a comparative study of the validity of this statement, we took 477 protein-coding genes from chromosome 8, and the CNVs of 101 genes, also protein-coding, belonging to the 8q24.3 region, a cytoband that is particularly active in the appearance of breast cancer. We created CNVS-conditioned co-expression networks of each of the 101 genes in the 8q24.3 region using conditional mutual information. The study was carried out using the four molecular subtypes of breast cancer (Luminal A, Luminal B, Her2, and Basal), as well as a case corresponding to healthy samples. We observed that in all cancer cases, the measurement of the Kolmogorov-Smirnov statistic shows that there are no significant differences between one and other values of the CNVs for any case. Furthermore, the co-expression interactions are stronger in all cancer subtypes than in the control networks. However, the control network presents a homogeneously distributed set of co-expression interactions, while for cancer networks, the highest interactions are more confined to specific cytobands, in particular 8q24.3 and 8p21.3. With this approach, we demonstrate that despite copy number alterations in the 8q24 region being a common trait in breast cancer, the loss of long-distance co-expression in breast cancer is not determined by CNVs.
Machine learning clinical decision support for interdisciplinary multimodal chronic musculoskeletal pain treatment

Introduction Chronic musculoskeletal pain is a prevalent condition impacting around 20% of people globally; resulting in patients living with pain, fatigue, restricted social and employment capacity, and reduced quality of life. Interdisciplinary multimodal pain treatment programs have been shown to provide positive outcomes by supporting patients modify their behavior and improve pain management through focusing attention on specific patient valued goals rather than fighting pain. Methods Given the complex nature of chronic pain there is no single clinical measure to assess outcomes from multimodal pain programs. Using Centre for Integral Rehabilitation data from 2019–2021 (n = 2,364), we developed a multidimensional machine learning framework of 13 outcome measures across 5 clinically relevant domains including activity/disability, pain, fatigue, coping and quality of life. Machine learning models for each endpoint were separately trained using the most important 30 of 55 demographic and baseline variables based on minimum redundancy maximum relevance feature selection. Five-fold cross validation identified best performing algorithms which were rerun on deidentified source data to verify prognostic accuracy. Results Individual algorithm performance ranged from 0.49 to 0.65 AUC reflecting characteristic outcome variation across patients, and unbalanced training data with high positive proportions of up to 86% for some measures. As expected, no single outcome provided a reliable indicator, however the complete set of algorithms established a stratified prognostic patient profile. Patient level validation achieved consistent prognostic assessment of outcomes for 75.3% of the study group (n = 1,953). Clinician review of a sample of predicted negative patients (n = 81) independently confirmed algorithm accuracy and suggests the prognostic profile is potentially valuable for patient selection and goal setting. Discussion These results indicate that although no single algorithm was individually conclusive, the complete stratified profile consistently identified patient outcomes. Our predictive profile provides promising positive contribution for clinicians and patients to assist with personalized assessment and goal setting, program engagement and improved patient outcomes.
Incidence and risk factors of postoperative acute pancreatitis after pancreaticoduodenectomy: a systematic review and meta-analysis

Background Postoperative acute pancreatitis (POAP) is a specific complication after pancreatectomy. The acute inflammatory response of the residual pancreas may affect the healing of pancreatoenteric anastomoses, leading to postoperative pancreatic fistulas (POPFs), abdominal infections, and even progressive systemic reactions, conditions that negatively affect patients' prognoses and can cause death. However, to the best of our knowledge, no systematic reviews or meta-analytic studies have assessed the incidence and risk factors of POAP after pancreaticoduodenectomy (PD). Method We searched PubMed, Web of Science, Embase, and Cochrane Library databases for relevant literature describing the outcomes of POAP after PD until November 25, 2022, and we used the Newcastle–Ottawa Scale to assess the quality of the studies. Next, we pooled the incidence of POAP and the odds ratios (ORs) and 95% confidence intervals (CIs) of the risk factors using a random-effect meta-analysis. I2 tests were used to assess heterogeneity between the studies. Results We analyzed data from 7,164 patients after PD from 23 articles that met the inclusion criteria for this study. The subgroup results of the meta-analysis by different POAP diagnostic criteria showed that the incidences of POAP were 15% (95% CI, 5–38) in the International Study Group for Pancreatic Surgery group, 51% (95% CI, 42–60) in the Connor group, 7% (95% CI, 2–24) in the Atlanta group, and 5% (95% CI, 2–14) in the unclear group. Being a woman [OR (1.37, 95% CI, 1.06–1.77)] or having a soft pancreatic texture [OR (2.56, 95% CI, 1.70–3.86)] were risk factors of POAP after PD. Conclusion The results showed that POAP was common after PD, and its incidence varied widely according to different definitions. Large-scale reports are still needed, and surgeons should remain aware of this complication. Systematic Review Registration identifier: CRD42022375124.
Bi-musicality at the age of artificial intelligence

The notion of bi-musicality was first introduced by Mantle Hood in his influential paper published in 1960 and this notion is still used and discussed today (Hood 1960). The term itself, bi-musicality, was coined on the model of bilingual, a word which applied to somebody who is fluent in two different languages belonging to different communities, underlining the fact that both music and language are attached to human groups or communities. Today the term bi-musicality is now a taken-for-granted part of the ethnomusicologist’s methodology (Rice 2014, 21). But in the era of globalization and post-colonial issues, some new perspectives have arised. When the term was introduced more than sixty years ago, what is today called World music was not yet established. Nowaday cultural boundaries tend to become blurred, and the idea of learning the music of non-Western cultures is no longer the work of ethnomusicologists only. Furthermore, technology can also bring new questions on this subject through the use of artificial intelligence and machine learning. In fact, the discussions in computer science about the musicality of machines are at the heart of recent development in artificial creativity and it is a natural issue to ask whether a machine can also become bi-musical. This concert-conference will explore such ideas in the case of a zither repertoire from Madagascar and will be illustrated by live interaction of the computer with a Malagasy musician, the great Justin Vali.
Recognizing Multiple Persons' Facial Expressions from Image Sequences Using HMM Based on Automatic Extraction of Significant

A method that can be used for for recognizing facial expressions of multiple persons is proposed. In this method, the condition of facial muscles is assigned to a hidden state of a HMM for each expression. Then, the probability of the state is updated according to a feature vector obtained from image processing. Image processing is performed in two steps. First, a velocity vector is estimated from every two successive frames by using an optical flow algorithm. Then, a two-dimensional Fourier transform is applied to a velocity vector field at the regions around an eye and the mouth. The coefficients for lower frequencies are selected to form a feature vector. A mixture density is used for approximating the output probability of the HMM so as to represent a variation in facial expressions among persons. To cope with the case when two expressions are displayed contiguously, the HMM computation is modified such that when the peak of a facial motion is detected, a new sequence of facial expressions is assumed to start from the previous frame with minimal facial motion. Experiments show that a mixture density is effective because recognition accuracy improves as the number of mixtures increases. In addition, the method correctly recognizes a facial expression that contiguously follows another one.
Quantization error in precision time counters

The quantization error in interpolating time counters is analyzed for three models of interpolator and for correlated and uncorrelated input events representing the start and end of the measured time interval. The analysis is related to the currently most common two-stage time interpolation method and based on data from several up-to-date integrated time counters. The main aim of this discussion is to find a general and accurate method for presentation and calculation of the quantization error in real, non-ideal time counters. We propose a novel graphical representation of the error, which may be useful for analysis of time counters with any interpolation method used.
Spline smoothing over difficult regions

Summary. It is occasionally necessary to smooth data over domains in ℝ2 with complex irregular boundaries or interior holes. Traditional methods of smoothing which rely on the Euclidean metric or which measure smoothness over the entire real plane may then be inappropriate. This paper introduces a bivariate spline smoothing function defined as the minimizer of a penalized sum‐of‐squares functional. The roughness penalty is based on a partial differential operator and is integrated only over the problem domain by using finite element analysis. The method is motivated by and applied to two sample smoothing problems and is compared with the thin plate spline.
Homologie de Leibniz et homologie de Hochschild

On definit une generalisation des algebres de Lie, les algebres de Leibniz, et construit une theorie (co)homologique associee, l'homologie de Leibniz. Celle-ci est definie au moyen d'une algebre tensorielle; pour les algebres de Lie, la projection canonique induit un morphisme de complexes vers le complexe standard pour l'homologie de Lie. On etudie l'homologie de Leibniz de gl(A), et montre principalement qu'il s'agit d'une algebre de Hopf, isomorphe a l'algebre exterieure sur l'homologie de Hochschild de A
Beamforming Optimality Range in TIMO Channels

In this paper, the effect of the input power constraint on the beamforming optimality range in Gaussian two-input multiple-output (TIMO) channels is explored. The obtained results, using standard Lagrangian formulation, determine explicitly the range of the input SNR for which rank-1 signaling (beamforming) is optimal in TIMO channels for both the common power constraint and the individual power constraint cases. Moreover, the obtained results are extended to random TIMO channels, with channel state information at the receiver only, using the Jensen's upper bound on the mutual information.
Influence of Simulated Wound Exudate on the Antimicrobial Efficacy of Various Intracanal Medicaments Against Enterococcus faecalis: An In Vitro Study

Aim The aim of this study is to compare and evaluate the antimicrobial efficacy of chlorhexidine, calcium hydroxide, and cetylpyridinium chloride against Enterococcus faecalis in the presence and absence of contamination with simulated periapical exudate at different time intervals. Methods Simulated wound exudate and cetylpyridinium chloride gel were prepared prior to testing. The test groups were divided into groups A and B based on the presence and absence of simulated wound exudate. They were further divided into four subgroups as follows: subgroup 1: calcium hydroxide; subgroup 2: 2% chlorhexidine gel; subgroup 3: 0.5% cetylpyridinium chloride gel; subgroup 4: 0.9% saline as control. E. faecalis was inoculated, and the test groups were evaluated at different time periods of six, 12, and 24 hours. Aliquots were then obtained and subjected to 10-fold serial dilutions. A total of 10 µl of individual samples was spread onto the nutrient agar medium using L-rod. The plates were then assessed for colony-forming units (CFU), and the values obtained were subjected to statistical analysis. Kolmogorov-Smirnov and Shapiro-Wilk normality tests were used to check whether the variables follow a normal distribution. For within-group comparison, the Friedman test and the Kruskal-Wallis test were used. For between-group comparison, the Mann-Whitney U test was used. Results Saline had the highest CFU values, while cetylpyridinium chloride had the lowest CFU values in both contaminated and non-contaminated groups. In all the conditions, the CFU values of cetylpyridinium chloride were significantly lowest compared to the other three groups. CFU values of the calcium hydroxide group were significantly high, followed by the chlorhexidine group when compared to cetylpyridinium chloride in both contaminated and non-contaminated groups. Conclusion Within the limitations of the current study, it can be concluded that cetylpyridinium chloride was the most effective intracanal medicament against E. faecalis than calcium hydroxide and chlorhexidine at varying time intervals, even in the presence of a periapical exudate. Thus, cetylpyridinium chloride can be considered an effective intracanal medicament for root canal disinfection.