Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Acetonitrile real gas phase behavior from quasi-ideal gas to nanodroplets: A microscopical view.

We have applied a recently developed general purpose acetonitrile force field based on first-principles calculations to simulate acetonitrile in the gas phase at different temperatures and densities. These conditions range from nearly ideal to real gas phase behavior and condensation. The molecular dynamics simulation results agree fairly well with the experimental studies available in the literature on the gas samples. The structural analysis of aggregates and their associated interaction energies is examined and related to the early model proposed on molecular association and equilibrium determining the non-ideal behavior. The formation of dimers is mainly responsible for the non-ideal behavior of the gas at very low density, confirming suggested models based on previous experimental studies. However, when the density of the sample rises, the level of aggregation increases and the simple concept of dimerization does not hold anymore. The real behavior adopted by the gas is related to the distribution of molecular structures observed. The macroscopical view of a real gas as a generic interparticle interaction system without a defined form may then be rationalized on the basis of a defined molecular association originated by a distribution of aggregates at the low density regime. The sample with the highest density (∼1.4 × 103 mol m-3) at the lowest temperature exhibits a massive aggregation where most of the acetonitrile (ACN) molecules in the simulation box form a big cluster. Its radial distribution function is similar to that of the liquid ACN. This strongly inhomogeneous distribution in the box can be considered a condensation in the gas phase under specific density-T conditions. This formation opens the door to the potential tuning of its solvent properties as a function of its size in these nanodroplets that in turn are controlled by the density-T conditions.

Osteopontin as a Biomarker in Interstitial Lung Diseases.

Osteopontin (OPN) is a glycoprotein involved in Th1 and Th17 differentiation, and inflammation and tissue remodeling. OPN is a biomarker of disease activity in patients with autoimmune inflammatory conditions. This study aimed to assess the diagnostic and prognostic value of OPN in interstitial lung diseases (ILDs). Between May 2016 and October 2019, 344 patients with ILD were recruited at the Hospital Universitario Marqués de Valdecilla (Spain) and were prospectively followed-up. This study involved the determination of OPN serum levels by ELISA and OPN RNA expression quantified using qPCR. Six genetic polymorphisms in OPN (rs28357094, rs2853749, rs2853750, rs11728697, rs7695531, and rs1126616) were genotyped using TaqMan assays. OPN serum levels were also assessed in 140 healthy controls. OPN serum levels (median [interquartile range]) were significantly higher in ILD patients than in controls (1.05 [0.75-1.51] ng/mL versus 0.81 [0.65-0.98] ng/mL in healthy controls; p < 0.01). OPN serum levels were inversely correlated with the forced vital capacity. OPN serum levels were also higher in ILD patients who died or underwent lung transplantation when compared with the remaining ILD patients (1.15 [0.80-1.72] ng/mL versus 0.99 [0.66-1.32] ng/mL; p = 0.05). Survival worsened in ILD patients with OPN > 1.03 ng/mL at 1, 3, and 5 years. No statistically significant differences in the genetic frequencies of OPN polymorphisms or the RNA expression were found among the different ILD groups. Elevated levels of OPN in the serum may be a useful indicator in identifying patients with ILD who are more likely to experience poor outcomes.

The impact of time from ILD diagnosis to referral to the transplant center on the probability of inclusion in the transplant waiting list.

BACKGROUND: Lung transplant is a therapeutic option for patients with progressive interstitial lung disease (ILD). OBJECTIVES: The objective of this study was to determine whether time from ILD diagnosis to referral to a transplant center influences the probability of being included in the transplant waiting list. METHODS: We performed a retrospective cohort study including all ILD patients evaluated as lung transplantation (LT) candidates at a lung transplant center between 01/01/2017 and 31/12/2022. The primary endpoint was the probability of being included in the lung transplant waiting list according to the time elapsed from diagnosis to referral to the transplant center. RESULTS: A total of 843 lung transplant requests were received, of which 367 (43.5%) were associated with ILD. Thirteen patients were excluded because they did not attend the first visit, whereas another 11 were excluded because some information was missing. As a result, our final sample was composed of 343 patients. The median time from diagnosis to referral was 29.4 (10.9 - 61.1) months. The overall probability of inclusion in the waiting list was 29.7%. By time from diagnosis to referral, the probability of inclusion in the waiting list was 48.1% for the patients referred 〈 6 months from diagnosis; 27.5% for patients referred 6 to 24 months from diagnosis; and 25.8% for patients referred 〉 24 months from diagnosis (p = 0.007). CONCLUSIONS: Early referral to a lung transplant center seemed to increase the probability of being included in the lung transplant waiting list. Further research is needed in this topic.

Magnetically modified-mitoxantrone mesoporous organosilica drugs: an emergent multimodal nanochemotherapy for breast cancer.

BACKGROUND: Chemotherapy, the mainstay treatment for metastatic cancer, presents serious side effects due to off-target exposure. In addition to the negative impact on patients' quality of life, side effects limit the dose that can be administered and thus the efficacy of the drug. Encapsulation of chemotherapeutic drugs in nanocarriers is a promising strategy to mitigate these issues. However, avoiding premature drug release from the nanocarriers and selectively targeting the tumour remains a challenge. RESULTS: In this study, we present a pioneering method for drug integration into nanoparticles known as mesoporous organosilica drugs (MODs), a distinctive variant of periodic mesoporous organosilica nanoparticles (PMOs) in which the drug is an inherent component of the silica nanoparticle structure. This groundbreaking approach involves the chemical modification of drugs to produce bis-organosilane prodrugs, which act as silica precursors for MOD synthesis. Mitoxantrone (MTO), a drug used to treat metastatic breast cancer, was selected for the development of MTO@MOD nanomedicines, which demonstrated a significant reduction in breast cancer cell viability. Several MODs with different amounts of MTO were synthesised and found to be efficient nanoplatforms for the sustained delivery of MTO after biodegradation. In addition, Fe3O4 NPs were incorporated into the MODs to generate magnetic MODs to actively target the tumour and further enhance drug efficacy. Importantly, magnetic MTO@MODs underwent a Fenton reaction, which increased cancer cell death twofold compared to non-magnetic MODs. CONCLUSIONS: A new PMO-based material, MOD nanomedicines, was synthesised using the chemotherapeutic drug MTO as a silica precursor. MTO@MOD nanomedicines demonstrated their efficacy in significantly reducing the viability of breast cancer cells. In addition, we incorporated Fe3O4 into MODs to generate magnetic MODs for active tumour targeting and enhanced drug efficacy by ROS generation. These findings pave the way for the designing of silica-based multitherapeutic nanomedicines for cancer treatment with improved drug delivery, reduced side effects and enhanced efficacy.

Association of Acidotolerant Cyanobacteria to Microbial Mats below pH 1 in Acidic Mineral Precipitates in Río Tinto River in Spain.

This report describes acidic microbial mats containing cyanobacteria that are strongly associated to precipitated minerals in the source area of Río Tinto. Río Tinto (Huelva, Southwestern Spain) is an extreme acidic environment where iron and sulfur cycles play a fundamental role in sustaining the extremely low pH and the high concentration of heavy metals, while maintaining a high level of microbial diversity. These multi-layered mineral deposits are stable all year round and are characterized by a succession of thick greenish-blue and brownish layers mainly composed of natrojarosite. The temperature and absorbance above and below the mineral precipitates were followed and stable conditions were detected inside the mineral precipitates. Different methodologies, scanning and transmission electron microscopy, immunological detection, fluorescence in situ hybridization, and metagenomic analysis were used to describe the biodiversity existing in these microbial mats, demonstrating, for the first time, the existence of acid-tolerant cyanobacteria in a hyperacidic environment of below pH 1. Up to 0.46% of the classified sequences belong to cyanobacterial microorganisms, and 1.47% of the aligned DNA reads belong to the Cyanobacteria clade.

Evaluating Sensitization-associated, Neuropathic-like Symptoms and Psychological Factors in Patients With Interstitial Lung Disease.

The aims of this study were to phenotype pain in patients with interstitial lung disease (ILD) by investigating the association between sensitization-associated symptoms with quality of life, anxiety/depression, pain catastrophizing, and kinesiophobia levels and identifying those risk factors explaining the variance of quality of life in individuals with ILD and pain. One hundred and thirty-two (38.6% women, mean age: 70, standard deviation: 10.5 years) patients with ILD completed clinical (age, sex, height, weight), psychological (Hospital Anxiety and Depression Scale [HADS] and the Pittsburgh Sleep Quality Index), and health-related quality of life (EQ-5D-5L) variables, as well as the Central Sensitization Inventory (CSI), the Self-Report Leeds Assessment of Neuropathic Symptoms (S-LANSS), Pain Catastrophizing Scale, and Tampa Scale for Kinesiophobia (TSK-11) questionnaires. The prevalence of sensitization-associated symptomatology (CSI), neuropathic-like features (S-LANSS), anxiety symptoms, depressive symptoms, or poor sleep was 20.5%, 23.5%, 23.6%, 22.9%, or 51.6%. Significant associations between CSI, S-LANSS, HADS-A, HADS-D, Pain Catastrophizing Scale, TSK-11, and EQ-5D-5L (.220 < r < .716) were found. The regression analysis revealed that CSI, TSK-11, and HADS-D explained 44.8% of the variance of EQ-5D-5L (r2 adjusted: .448). This study found the presence of sensitization-associated and neuropathic-like symptoms as well as other central nervous system-derived symptoms, such as anxiety, depression, poor sleep, pain catastrophizing, and kinesiophobia in 25% of ILD patients with pain. Sensitization-associated symptoms, depression, and kinesiophobia were associated with a worse quality of life. These findings would support that individuals with ILD can exhibit different pain phenotypes, including nociplastic-like pain phenotype based on self-reported measurements. PERSPECTIVE: Pain in patients with ILD can fulfill features of different phenotypes, including nociplastic pain, when sensory, emotional, and cognitive mechanisms are involved at the same time.

Draft genome sequence of the deep-subsurface Ciceribacter sp. strain T2.26MG-112.2, a second Rhizobiaceae isolated from the Iberian Pyrite Belt at 492.6 mbs.

T2.26MG-112.2 is a Ciceribacter strain that has been isolated from the deep subsurface of the Iberian Pyrite Belt. We report its draft genome consisting of a chromosome of ≈4.9 Mb and a plasmid of 357 kb. The annotation reveals 4,824 coding sequences, 48 tRNA genes, and 1 rRNA operon.

Impact of the New Definition of Pulmonary Hypertension on the Prevalence of Primary Graft Dysfunction in Lung Transplant Recipients.

BACKGROUND & AIM: Pulmonary hypertension (PH) secondary to lung disease (Group-3 PH) is the second leading cause of PH. The role of PH as a risk factor for primary graft dysfunction (PGD) following lung transplant (LT) is controversial. OBJECTIVE: To assess the impact that the new definition of PH had on the prevalence of PH in patients with advanced lung disease-candidate for LT, and its association with the occurrence of PGD. METHOD: A retrospective study was performed in all patients undergoing cardiac catheterisation referred for consideration as candidates to LT in a centre between 1 January 2017 and 31 December 2022. The baseline and haemodynamic characteristics of patients were analysed, along with the occurrence of PGD and post-transplant course in those who ultimately underwent transplantation. RESULTS: A total of 396 patients were included. Based on the new 2022 European Society of Cardiology/European Respiratory Society definitions, as many as 70.7% of patients met PH criteria. Since the introduction of the 2022 definition, a significant reduction was observed in the frequency of severe Group-3 PH (41.1% vs 10.3%; p<0.001), with respect to the 2015 definition. As many as 236 patients underwent transplantation. None of the variables associated with PH was identified as a risk factor for PGD. CONCLUSION: The new classification did not have any impact on the prevalence of PGD after transplantation. These results exclude that any significant differences exist in the baseline characteristics or post-transplant course of patients with Group-3 PH vs unclassified PH.

Association analysis of self-reported outcomes with a validated subset.

In health-science research, outcomes ascertained through surveys and interviews are subject to potential bias with respect to the true outcome status, which is only ascertainable with clinical and laboratory assessment. This measurement error may lead to biased inference when evaluating associations between exposures and outcomes of interest. Here, we consider a cohort study in which the outcome of interest is ascertained via questionnaire, subject to imperfect ascertainment, but where a subset of participants also have a clinically assessed, validated outcome available. This presents a methodological opportunity to address potential bias. Specifically, we constructed the likelihood in two parts, one using the validated subset and the other using a subset without validation. This work expands on that proposed by Pepe and enables inference with standard statistical software. Weighted generalized linear model estimates for our method and maximum likelihood estimates (MLE) for Pepe's method were computed, and the statistical inference was based on the standard large-sample likelihood theory. We compare the finite sample performance of two approaches through Monte Carlo simulations. This methodological work was motivated by a large cohort study of long-term childhood cancer survivors, allowing us to provide a relevant application example where we examined the association between clinical factors and chronic health conditions.

Development of a liver graft assessment expert machine-learning system: when the artificial intelligence helps liver transplant surgeons.

Background: The complex process of liver graft assessment is one point for improvement in liver transplantation. The main objective of this study is to develop a tool that supports the surgeon who is responsible for liver donation in the decision-making process whether to accept a graft or not using the initial variables available to it. Material and method: Liver graft samples candidate for liver transplantation after donor brain death were studied. All of them were evaluated "in situ" for transplantation, and those discarded after the "in situ" evaluation were considered as no transplantable liver grafts, while those grafts transplanted after "in situ" evaluation were considered as transplantable liver grafts. First, a single-center, retrospective and cohort study identifying the risk factors associated with the no transplantable group was performed. Then, a prediction model decision support system based on machine learning, and using a tree ensemble boosting classifier that is capable of helping to decide whether to accept or decline a donor liver graft, was developed. Results: A total of 350 liver grafts that were evaluated for liver transplantation were studied. Steatosis was the most frequent reason for classifying grafts as no transplantable, and the main risk factors identified in the univariant study were age, dyslipidemia, personal medical history, personal surgical history, bilirubinemia, and the result of previous liver ultrasound (p < 0.05). When studying the developed model, we observe that the best performance reordering in terms of accuracy corresponds to 76.29% with an area under the curve of 0.79. Furthermore, the model provides a classification together with a confidence index of reliability, for most cases in our data, with the probability of success in the prediction being above 0.85. Conclusion: The tool presented in this study obtains a high accuracy in predicting whether a liver graft will be transplanted or deemed non-transplantable based on the initial variables assigned to it. The inherent capacity for improvement in the system causes the rate of correct predictions to increase as new data are entered. Therefore, we believe it is a tool that can help optimize the graft pool for liver transplantation.

Enabling Remote Elderly Care: Design and Implementation of a Smart Energy Data System with Activity Recognition.

Seniors face many challenges as they age, such as dementia, cognitive and memory disorders, vision and hearing impairment, among others. Although most of them would like to stay in their own homes, as they feel comfortable and safe, in some cases, older people are taken to special institutions, such as nursing homes. In order to provide serious and quality care to elderly people at home, continuous remote monitoring is perceived as a solution to keep them connected to healthcare service providers. The new trend in medical health services, in general, is to move from 'hospital-centric' services to 'home-centric' services with the aim of reducing the costs of medical treatments and improving the recovery experience of patients, among other benefits for both patients and medical centers. Smart energy data captured from electrical home appliance sensors open a new opportunity for remote healthcare monitoring, linking the patient's health-state/health-condition with routine behaviors and activities over time. It is known that deviation from the normal routine can indicate abnormal conditions such as sleep disturbance, confusion, or memory problems. This work proposes the development and deployment of a smart energy data with activity recognition (SEDAR) system that uses machine learning (ML) techniques to identify appliance usage and behavior patterns oriented to older people living alone. The proposed system opens the door to a range of applications that go beyond healthcare, such as energy management strategies, load balancing techniques, and appliance-specific optimizations. This solution impacts on the massive adoption of telehealth in third-world economies where access to smart meters is still limited.

Vitamin B12 Auxotrophy in Isolates from the Deep Subsurface of the Iberian Pyrite Belt.

Vitamin B12 is an enzymatic cofactor that is essential for both eukaryotes and prokaryotes. The development of life in extreme environments depends on cofactors such as vitamin B12 as well. The genomes of twelve microorganisms isolated from the deep subsurface of the Iberian Pyrite Belt have been analyzed in search of enzymatic activities that require vitamin B12 or are involved in its synthesis and import. Results have revealed that vitamin B12 is needed by these microorganisms for several essential enzymes such as ribonucleotide reductase, methionine synthase and epoxyqueosine reductase. Isolate Desulfosporosinus sp. DEEP is the only analyzed genome that holds a set core of proteins that could lead to the production of vitamin B12. The rest are dependent on obtaining it from the subsurface oligotrophic environment in which they grow. Sought proteins involved in the import of vitamin B12 are not widespread in the sample. The dependence found in the genomes of these microorganisms is supported by the production of vitamin B12 by microorganisms such as Desulfosporosinus sp. DEEP, showing that the operation of deep subsurface biogeochemical cycles is dependent on cofactors such as vitamin B12.

Bronchial Stenosis After Lung Transplantation From cDCD Donors Using Simultaneous Abdominal Normothermic Regional Perfusion: A Single-center Experience.

BACKGROUND: Controlled donation after circulatory death (cDCD) has increased the number of lung donors significantly. The use of abdominal normothermic regional perfusion (A-NRP) during organ procurement is a common practice in some centers due to its benefits on abdominal grafts. This study aimed to assess whether the use of A-NRP in cDCD increases the frequency of bronchial stenosis in lung transplant (LT) recipients. METHODS: A single-center, retrospective study including all LTs was performed between January 1, 2015, and August 30, 2022. Airway stenosis was defined as a stricture that leads to clinical/functional worsening requiring the use of invasive monitoring and therapeutic procedures. RESULTS: A total of 308 LT recipients were included in the study. Seventy-six LT recipients (24.7%) received lungs from cDCD donors using A-NRP during organ procurement. Forty-seven LT recipients (15.3%) developed airway stenosis, with no differences between lung recipients with grafts from cDCD (17.2%) and donation after brain death donors (13.3%; P = 0.278). A total of 48.9% of recipients showed signs of acute airway ischemia on control bronchoscopy at 2 to 3 wk posttransplant. Acute ischemia was an independent risk factor for airway stenosis development (odds ratio = 2.523 [1.311-4.855], P = 0.006). The median number of bronchoscopies per patient was 5 (2-9), and 25% of patients needed >8 dilatations. Twenty-three patients underwent endobronchial stenting (50.0%) and each patient needed a median of 1 (1-2) stent. CONCLUSIONS: Incidence of airway stenosis is not increased in LT recipients with grafts obtained from cDCD donors using A-NRP.

Display site selection in a ground dwelling bird: the importance of viewshed.

We studied the effects of visibility, female and male distribution, microhabitat and distance to human infrastructure on display site selection in a ground-dwelling bird, the Canarian houbara bustard. Using a very high-resolution digital elevation model based on LIDAR technology, and a complete census of the breeding population, we compared 98 display sites with randomly generated sites through generalized linear models. Univariate analyses showed that males displayed at locations that increased their visibility, both at short and long distances. Interestingly, although numbers of females and males around sites did not differ between display and random locations, from display locations males could see more females and males at both distance ranges. The absence of vegetation and stones was also critical as it allowed males to perform display runs on a ground free of obstacles. The amount of trophic resources did not correlate with the selection of the display site itself, though an appropriate vegetation cover seemed to be important at a wider habitat scale. Finally, display sites were farther away than random sites from sources of human disturbance, such as urban nuclei, buildings and tracks. Logistic regression analyses confirmed the importance of viewshed, low stone and vegetation cover, and distance to urban centres and tracks, and model averaging identified short-range visibility and females visible in the long range as the most important visibility variables. These results are compatible with the sexual advertisement and predator avoidance hypotheses. We provide recommendations to ensure an appropriate management of the breeding habitat of this endangered subspecies.

Shedding light on the metal-phthalocyanine EXAFS spectra through classical and ab initio molecular dynamics.

Extended X-Ray Absorption Fine Structure (EXAFS) theoretical spectra for some 3d transition metal-phthalocyanines-FePc, NiPc, CuPc, and ZnPc-are presented. Their complexity and rigidity make them a good testbed for the development of theoretical strategies that can complement the difficulties present in the experimental spectrum fitting. Classical and ab initio molecular dynamics trajectories are generated and employed as a source of structural information to compute average spectra for each MPc species. The original ZnPc force field employed in the classical molecular dynamics simulations has been modified in order to improve the agreement with the experimental EXAFS spectrum, and the modification strategy-based on MP2 optimized structures-being extended to the rest of MPcs. Both types of trajectories, classical and ab initio, provide very similar results, showing in all cases the main features present in the experimental spectra despite the different simulation timescales employed. Spectroscopical information has been analyzed on the basis of shells and legs contributions, making possible the comparison with the experimental fitting approaches. According to the simulations results, the simple relationships employed in the fitting process to define the dependence of the Debye Waller factors associated with multiple scattering paths with those of single scattering paths are reasonable. However, a lack of multiple backscattering paths contributions is found due to the intrinsic rigidity of the chemical motif (macrocycle). Its consequences in the Debye Waller factors of the fitted contributions are discussed.

Combining participatory action research and emerging ways of collective action to promote institutional change toward social commitment: Groundings, strategies, and implications of an experience.

AIMS: This study reports the foundations, strategies, and results of an institutional change experience based on the combination of participatory-action-research and new currents of collective mobilization and political participation. It aimed to achieve the institution's greater social commitment and a more participatory and transparent management. METHODS: The process took place in a Spanish public university and was promoted and coordinated by a Work Group that emerged from grassroots university community. Collective diagnosis was performed through face-to-face strategies (global, sectorial, and faculty meetings) and virtual tools (web-blog, on-line surveys, shared documents). Collective action combined nonformal with formal institutional participation and applied hybrid activism, self-organization in horizontal structures and integrative conflict management. RESULTS: A sequential process of diagnosis, collective action, and negotiation was implemented. As a result, the university Governing Team, representatives from different sectors and members of the Work Group worked jointly to define several institutional actions that were thereafter launched. Those actions aimed to improve institutional participation and transparency, and greater institutional social commitment. CONCLUSION: The combination of participatory-action-research and new ways of collective action can be an excellent tool to draw institutions towards greater social engagement, thus contributing to sustainable social change. A model to guide institutional change is drafted.

Type IV Mirizzi Syndrome: Brief Report and Review of Management Options.

Mirizzi syndrome is a rare complication of chronic calculous cholecystitis. Preoperative diagnosis is challenging due to the absence of pathognomonic signs and symptoms and low sensitivity rates of imaging tests. Historically, laparotomy has been the preferred choice of surgical management. Endoscopic and laparoscopic approaches have been increasingly described as diagnostic and therapeutic options for Mirizzi type I and II, but data is limited regarding the management of more complex cases. We describe a staged endoscopic and laparoscopic approach for the management of type IV Mirizzi syndrome and review the management options.

Towards automatic waste containers management in cities via computer vision: containers localization and geo-positioning in city maps.

This paper describes the scientific achievements of a collaboration between a research group and the waste management division of a company. While these results might be the basis for several practical or commercial developments, we here focus on a novel scientific contribution: a methodology to automatically generate geo-located waste container maps. It is based on the use of Computer Vision algorithms to detect waste containers and identify their geographic location and dimensions. Algorithms analyze a video sequence and provide an automatic discrimination between images with and without containers. More precisely, two state-of-the-art object detectors based on deep learning techniques have been selected for testing, according to their performance and to their adaptability to an on-board real-time environment: EfficientDet and YOLOv5. Experimental results indicate that the proposed visual model for waste container detection is able to effectively operate with consistent performance disregarding the container type (organic waste, plastic, glass and paper recycling,…) and the city layout, which has been assessed by evaluating it on eleven different Spanish cities that vary in terms of size, climate, urban layout and containers' appearance.