Miracle-dz/UniFAR-FTUs huggingface dataset:
A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma

Due to biological heterogeneity, lung adenocarcinoma (LUAD) patients with the same stage may exhibit variable responses to immunotherapy and a wide range of outcomes. It is urgent to seek a biomarker that can predict the prognosis and response to immunotherapy in these patients. In this study, we identified two genes (ANLN and ARNTL2) from multiple gene expression data sets, and developed a two-mRNA-based signature that can effectively distinguish high- and low-risk patients and predict patients’ response to immunotherapy. Furthermore, taking full advantage of the complementary value of clinical and molecular features, we combined the immune prognostic signature with clinical features to construct and validate a nomogram that can predict the probability of high tumor mutational burden (>10 mutations per megabyte). This may improve the estimation of immunotherapy response in LUAD patients, and provide a new perspective for clinical screening of immunotherapy beneficiaries.
Case Report: Surgical Closure of Chronic Soft Tissue Defects Using Extracellular Matrix Graft Augmented Tissue Flaps

Chronic soft tissue defects are notoriously difficult to heal. Surgical reconstruction of chronic defects using tissue flaps is a routine approach for closure of challenging chronic defects. Due to the poor tissue quality of chronic defects and associated inflammation, infection and impaired blood supply the success of flap closure is marred by reported complication rates of 25–58%. Extracellular matrix (ECM)-based graft materials are commonly used for resolving chronic wounds and in plastic and reconstructive procedures to create a scaffold for tissue regeneration. We hypothesized combination use of ECM grafts with tissue flaps in a single-stage surgical procedure would reduce complications and improve outcomes in the closure of chronic soft tissue defects. We report a case series (n = 9) of chronic soft tissue defect reconstruction using this modified procedure of ECM graft augmented flap closure. Defects included pressure injuries and surgical dehiscence and ranged in wound age from 5 months to 7 years. Successful uncomplicated healing was achieved in six defects. Post-operative complications (dehiscence) occurred in two defects, however, these healed via secondary intention without additional surgical intervention. All healed defects exhibited acceptable cosmesis and “normal” function, with 100% patient satisfaction. Augmentation of tissue flaps with ECM graft materials in this modified single-stage procedure may improve outcomes and minimize typical complications encountered in flap closure of chronic defects attributed to inflammation, infection, hypoperfusion, and dead space.
Vegetation Monitoring Optimization With Normalized Difference Vegetation Index and Evapotranspiration Using Remote Sensing Measurements and Land Surface Models Over East Africa

The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration (ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.
Effects of Ramadan and Non-ramadan Intermittent Fasting on Body Composition: A Systematic Review and Meta-Analysis

Intermittent fasting (IF) has gained popularity for body-composition improvement purposes. The aim of this systematic review and meta-analysis was to summarize the effects of Ramadan vs. non-Ramadan IF on parameters of body composition. We conducted a comprehensive search of peer-reviewed articles in three electronic databases: PubMed, Scopus, and Web of Science (published until May 2020). Studies were selected if they included samples of adults (≥18 years), had an experimental or observational design, investigated any type of IF and included body composition outcomes. Meta-analytical procedures were conducted when feasible. Sixty-six articles met the eligibility criteria. We found that non-Ramadan IF is effective for decreasing body weight (−0.341 (95% CI [−0.584, −0.098], p = 0.006), body mass index (−0.699, 95% CI [−1.05, −0.347], p < 0.001), and absolute fat mass (−0.447, 95% CI [−0.673, −0.221], p < 0.001). When contrasting pre- post-intervention data on fat-free mass between treatments and controls, group-differences were non-significant (p > 0.05). Conversely, we observed a significant increase in fat-free mass when comparing pre- to post-intervention in a within design fashion (0.306, 95% CI [0.133, 0.48], p = 0.001). Finally, despite being accompanied by dehydration, Ramadan IF is effective in decreasing body weight (−0.353; 95% CI [−0.651, −0.054], p = 0.02) and relative fat mass (−0.533; 95% CI [−1.025, −0.04], p = 0.034). Ramadan IF seems to implicate some beneficial adaptations in weight management, although non-Ramadan IF appears to be more effective in improving overall body composition.
Global Transcriptome and Weighted Gene Co-expression Network Analyses of Growth-Stage-Specific Drought Stress Responses in Maize

Drought is the major abiotic stress threatening maize (Zea mays L.) production globally. Despite recent scientific headway in deciphering maize drought stress responses, the overall picture of key genes, pathways, and co-expression networks regulating maize drought tolerance is still fragmented. Therefore, deciphering the molecular basis of maize drought tolerance remains pertinent. Here, through a comprehensive comparative leaf transcriptome analysis of drought-tolerant hybrid ND476 plants subjected to water-sufficient and water-deficit treatment conditions at flared (V12), tasseling (VT), the prophase of grain filling (R2), and the anaphase of grain filling (R4) crop growth stages, we report growth-stage-specific molecular mechanisms regulating maize drought stress responses. Based on the transcriptome analysis, a total of 3,451 differentially expressed genes (DEGs) were identified from the four experimental comparisons, with 2,403, 650, 397, and 313 DEGs observed at the V12, VT, R1, and R4 stages, respectively. Subsequently, 3,451 DEGs were divided into 12 modules by weighted gene co-expression network analysis (WGCNA), comprising 277 hub genes. Interestingly, the co-expressed genes that clustered into similar modules exhibited diverse expression tendencies and got annotated to different GO terms at different stages. MapMan analysis revealed that DEGs related to stress signal transduction, detoxification, transcription factor regulation, hormone signaling, and secondary metabolites biosynthesis were universal across the four growth stages. However, DEGs associated with photosynthesis and amino acid metabolism; protein degradation; transport; and RNA transcriptional regulation were uniquely enriched at the V12, VT, R2, and R4 stages, respectively. Our results affirmed that maize drought stress adaptation is a growth-stage-specific response process, and aid in clarifying the fundamental growth-stage-specific mechanisms regulating drought stress responses in maize. Moreover, genes and metabolic pathways identified here can serve as valuable genetic resources or selection targets for further functional validation experiments.
TMPSS: A Deep Learning-Based Predictor for Secondary Structure and Topology Structure Prediction of Alpha-Helical Transmembrane Proteins

Alpha transmembrane proteins (αTMPs) profoundly affect many critical biological processes and are major drug targets due to their pivotal protein functions. At present, even though the non-transmembrane secondary structures are highly relevant to the biological functions of αTMPs along with their transmembrane structures, they have not been unified to be studied yet. In this study, we present a novel computational method, TMPSS, to predict the secondary structures in non-transmembrane parts and the topology structures in transmembrane parts of αTMPs. TMPSS applied a Convolutional Neural Network (CNN), combined with an attention-enhanced Bidirectional Long Short-Term Memory (BiLSTM) network, to extract the local contexts and long-distance interdependencies from primary sequences. In addition, a multi-task learning strategy was used to predict the secondary structures and the transmembrane helixes. TMPSS was thoroughly trained and tested against a non-redundant independent dataset, where the Q3 secondary structure prediction accuracy achieved 78% in the non-transmembrane region, and the accuracy of the transmembrane region prediction achieved 90%. In sum, our method showcased a unified model for predicting the secondary structure and topology structure of αTMPs by only utilizing features generated from primary sequences and provided a steady and fast prediction, which promisingly improves the structural studies on αTMPs.
Serum Prealbumin Concentrations, COVID-19 Severity, and Mortality: A Systematic Review and Meta-Analysis

Excessive inflammation and malnutrition are associated with coronavirus disease 2019 (COVID-19) severity and mortality. Combined biomarkers of malnutrition and inflammation, such as serum prealbumin, might be particularly attractive for early risk stratification. We conducted a systematic review and meta-analysis of studies reporting serum prealbumin in patients with COVID-19. We searched PubMed, Web of Science and Scopus, between January and November 2020, for studies reporting data on serum prealbumin, COVID-19 severity, defined as severe illness, prolonged viral load, receiving mechanical ventilation or admitted to intensive care unit (ICU), and mortality. Nineteen studies in 4,616 COVID-19 patients were included in the meta-analysis. Pooled results showed that serum prealbumin concentrations were significantly lower in patients with severe disease and non-survivors (standard mean difference, SMD, −0.92, 95% CI, −1.10 to −0.74, P < 0.001). Extreme heterogeneity was observed (I2 = 77.9%; P < 0.001). In sensitivity analysis, the effect size was not significantly affected when each study was in turn removed (range between −0.86 and −0.95). The Begg's (P = 0.06) and Egger's t-tests (P = 0.26) did not show publication bias. Pooled SMD values were significantly and negatively associated with age (t = −2.18, P = 0.045) and C-reactive protein (t = −3.85, P = 0.002). In our meta-analysis, lower serum prealbumin concentrations were significantly associated with COVID-19 severity and mortality. This combined marker of malnutrition and inflammation might assist with early risk stratification and management in this group.
MOLECULAR DYNAMICS STUDIES OF HYDRATED ZEOLITE 4A

Molecular dynamics (MD) simulations of hydrated zeolite 4A incorporating a mobile zeolite framework have been performed at 298 K for a range of hydration over a time scale of 0.5 ns. The hydration energy of the water is found to be 57 kJ/mol of water at full hydration, in excellent agreement with previous MD simulations. The water molecules are found to locate at preferred sites on the inside of the α-cages with additional water located within the volume of the α-cages. The latter are more mobile. The self-diffusion coefficient of the water molecules contained in the α-cages is found to increase from 2.7 × 10-10 m2/s with 56 water molecules per unit cell to 6.8 × 10-10 m2/s with 168 water molecules per unit cell. The diffusion coefficient is found to decrease close to full hydration, namely 224 water molecules per unit cell, due to the blocking effect of water molecules in the fully hydrated cages. The MD self-diffusion coefficient at full hydration is found to be approximately 3 times the experimental va.
A study about the structure of vulcanized natural rubber/styrene butadiene rubber blends and the glass transition behavior

A study of the thermal behavior of cured elastomeric blends of natural rubber (NR) and styrene butadiene rubber (SBR) prepared by solution blending in toluene is presented. Binary blends with different compositions of NR/SBR were produced using a conventional cure system based on sulfur and TBBS (n-t-butyl-2-benzothiazole sulfonamide as accelerator. The compounds were vulcanized at 433 K up to an optimum time of cure determined by rheometric tests. From swelling tests, the crosslink densities of the compounds were obtained and compared with those obtained in similar blends prepared by mechanical mixing. The results were analyzed in terms of the disentangling of the chain structures of the SBR and NR phases and the achieved cure state of the blend. Using differential scanning calorimetry, the glass transition temperature Tg of each blend was measured. In most compounds, the value of Tg corresponding to each phase of the blend was determined, but in some blends a single value of Tg was obtained. The variation of Tg with the composition and cure level in each phase was analyzed. On the other hand, a physical mixture of two equal parts of NR and SBR vulcanized was measured and the results were compared to those of the NR50/SBR50 cured blend. Besides, to analyze the influence of the network structure, pure NR and SBR unvulcanized samples were measured. On the basis of all the obtained results, the influence of the interphase formed in the blend between SBR and NR phases is discussed. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
A Chemomechanobiological Model of the Long-Term Healing Response of Arterial Tissue to a Clamping Injury

Vascular clamping often causes injury to arterial tissue, leading to a cascade of cellular and extracellular events. A reliable in silico prediction of these processes following vascular injury could help us to increase our understanding thereof, and eventually optimize surgical techniques or drug delivery to minimize the amount of long-term damage. However, the complexity and interdependency of these events make translation into constitutive laws and their numerical implementation particularly challenging. We introduce a finite element simulation of arterial clamping taking into account acute endothelial denudation, damage to extracellular matrix, and smooth muscle cell loss. The model captures how this causes tissue inflammation and deviation from mechanical homeostasis, both triggering vascular remodeling. A number of cellular processes are modeled, aiming at restoring this homeostasis, i.e., smooth muscle cell phenotype switching, proliferation, migration, and the production of extracellular matrix. We calibrated these damage and remodeling laws by comparing our numerical results to in vivo experimental data of clamping and healing experiments. In these same experiments, the functional integrity of the tissue was assessed through myograph tests, which were also reproduced in the present study through a novel model for vasodilator and -constrictor dependent smooth muscle contraction. The simulation results show a good agreement with the in vivo experiments. The computational model was then also used to simulate healing beyond the duration of the experiments in order to exploit the benefits of computational model predictions. These results showed a significant sensitivity to model parameters related to smooth muscle cell phenotypes, highlighting the pressing need to further elucidate the biological processes of smooth muscle cell phenotypic switching in the future.
Plant-Soil-Microbiota Combination for the Removal of Total Petroleum Hydrocarbons (TPH): An In-Field Experiment

The contamination of soil with total petroleum hydrocarbons (TPH) may result in dramatic consequences and needs great attention, as soil rehabilitation would need more effort from a sustainability perspective. However, there is still no known general method since the remediation technology is strictly site-specific. Adaptive biological system dynamics can play a key role in understanding and addressing the potential of situ-specific biological combinations for soil pollutants removal. The potential worst-case of TPH contamination reflects soil affected by heavy industrial activities, such as oil refineries. Therefore, the experimental trial was conducted on a 2,000 m2 area from a contaminated site located in northern Italy. We evaluated the remediation potential over time (270 days) assessing (i) the phytoremediation efficiency of two species of Poaceae (Festuca arundinacea Schreb. and Dactylis glomerata L.) and two species of Fabaceae (Medicago sativa L. and Lotus corniculatus L.) and (ii) the role of the indigenous bacteria flora and endo-mycorrhizae consortium addition in plant growth promotion. We also induced resistance to contamination stress in a field experiment. Thirty-three indigenous bacteria selected from the contaminated soils showed marked plant growth promotion. Moreover, functional metagenomics confirmed the metabolic capability of hydrocarbon-degrading microorganisms living in the polluted soil. Our data showed that soil enzymatic activities increased with hydrocarbon degradation rate after 60 days. Both Poaceae and Fabaceae resulted in remarkable remediation potential. Stress markers and antioxidant activity indicated that the selected plant species generally need some time to adapt to TPH stress. In conclusion, our evaluation implied both the rhizosphere effects and functional features of the plant and suggested that plants should (i) have marked tolerance to specific contaminants, (ii) be characterized by an extensive root system, and (iii) be susceptible to arbuscular mycorrhizal fungi (AMF) infection.
Early-Life Neglect Alters Emotional and Cognitive Behavior in a Sex-Dependent Manner and Reduces Glutamatergic Neuronal Excitability in the Prefrontal Cortex

Early-life neglect in critical developmental periods has been associated with emotional and cognitive consequences. Maternal separation (MS) has been commonly used as a rodent model to identify the developmental effects of child neglect. However, reports have shown considerable variability in behavioral results from MS studies in both mice and rats. Difficulties in developing reliable child neglect models have impeded advances in identifying the effects of early-life stress. Accumulating evidence shows that neuronal intrinsic excitability plays an important role in information processing and storage in the brain. The prefrontal cortex (PFC) integrates information from many cortical and subcortical structures. No studies to date have examined the impact of early-life stress on glutamatergic neuronal excitability in the PFC. This study aimed to develop a reliable child neglect rat model and observe glutamatergic neuronal excitability in the PFC. An MS with early weaning (MSEW) rat model was developed. Rats were separated from the dam for 4 h per day on postnatal days (PNDs) 2–5 and for 8 h per day on PNDs 6–16 and then weaned on PND 17. A battery of behavioral tests was used to assess anxiety-like behavior, coping behavior, working memory, spatial reference memory, and fear memory. The action potentials (APs) of glutamatergic neuronal membranes were recorded. MSEW resulted in anxiety-like behavior, a passive coping strategy and increased fear memory in male rats and decreased locomotor activity in both sexes. MSEW slightly impaired working memory during non-stressful situations in female rats but did not change spatial reference memory or associative learning under stressful circumstances in either sex. MSEW reduced the number of glutamatergic neuron APs in male rats. Our findings showed that MS with early weaning induced anxiety-like behavior in male rats. The reduced glutamatergic neuronal excitability may be associated with the emotional alteration induced by MSEW in male rats. In addition, MSEW induced adaptive modification, which depended on a non-stressful context.
Improved Hydration Resistance of Synthesized Magnesia–Calcia Clinker by Surface Modification

Hydration resistance of synthesized MgO–CaO clinker was improved by surface modification using oleic acid, stearic acid, or complex acids as modifiers, with phosphoric acid as a reference. Unmodified and modified samples were evaluated using a powdering resistance test, weight change test, and flowability test. The remarkable effects of the modifiers on the hydration resistance and flowability of the clinker were manifested, and the complex modifier caused the most significant effect. The mechanism involved the formation of calcium-containing films on the surfaces of the clinker particles, which protected them from hydration. The flowability of the clinker also increased with improved hydration resistance because of the decreased bonded-moisture content. Comparison of infrared spectra between unmodified and modified samples confirmed the formation of surface films.