This work reports the polar lipid profiles of two freshwater algae: the diatom Nitzschia palea, widespread alga that typically inhabits freshwater ponds and rivers, and the Scenedesmus costatus, a common green alga. HILIC-ESI-MS/MS analysis was used to determine and quantify the major phospholipids and glycolipids, and their relative molecular species, extracted from the two microalgal cultures. Glycolipids were eluted first, followed by phospholipids partially co-eluting with the sulfoglycolipids. We also studied the fragmentation pattern in the negative ionization mode for galactolipids. The most intense daughter ion corresponded to the fatty acyl chain located at the sn-2 position, which allowed us to determine the stereospecific distribution of the following fatty acids on the glycerol backbone. For green algae, 18:3 fatty acid was frequently occurring in both phospholipids and galactolipids. We also found 16:4 in some molecular species of mono- and digalactosyldiacylglycerol (MGDG and DGDG). The most abundant and characteristic molecular species of MGDG in green algae exhibited the combination (18:3/16:4), whereas DGDG was more saturated than MGDG and contained mainly 18:1, 18:2, or 18:3 at sn-1 and shorter fragments 16:0, 16:1, 16:2, and 16:3 at sn-2. It is also remarkable that in the diatom, the phospholipids contained mainly molecular species with saturated or monounsaturated fatty acids such as 16:0, 16:1 and 18:1. In contrast, MGDG and DGDG contained a higher proportion of polyunsaturated fatty acids, such as the unique and abundant MGDG (20:5/20:2).

Background: Variation of inferior vena cava (IVC) is used to predict fluid-responsiveness, but the IVC visualization with standard sagittal approach (SC, subcostal) cannot be always achieved. In such cases, coronal trans-hepatic (TH) window may offer an alternative, but the interchangeability of IVC measurements in SC and TH is not fully established. Further, artificial intelligence (AI) with automated border detection may be of clinical value but it needs validation. Methods: Prospective observational validation study in mechanically ventilated patients with pressure-controlled mode. Primary outcome was the IVC distensibility (IVC-DI) in SC and TH imaging, with measurements taken both in M-Mode or with AI software. We calculated mean bias, limits of agreement (LoA), and intra-class correlation (ICC) coefficient. Results: Thirty-three patients were included. Feasibility rate was 87.9% and 81.8% for SC and TH visualization, respectively. Comparing imaging from the same anatomical site acquired with different modalities (M-Mode vs AI), we found the following IVC-DI differences: 1)SC: mean bias -3.1%, LoA [-20.1;13.9], ICC=0.65; 2)TH: mean bias -2.0%, LoA [-19.3;15.4], ICC=0.65. When comparing the results obtained from the same modality but from different sites (SC vs TH), IVC-DI differences were: 3)M-Mode: mean bias 1.1%, LoA [-6.9;9.1], ICC=0.54; 4)AI: mean bias 2.0%, LoA [-25.7;29.7], ICC=0.32. Conclusions: In patients mechanically ventilated, AI software shows good accuracy (modest overestimation) and moderate correlation as compared to M-mode assessment of IVC-DI, both for SC and TH windows. However, precision seems suboptimal with wide LoA. The comparison of M-Mode or AI between different sites yields similar results but with weaker correlation.

Nature has provided unique molecular scaffolds for applications including therapeutics, agriculture, and food. Due to differences in ecological environments and laboratory conditions, engineering is often necessary to uncover and utilize the chemical diversity. Although we can efficiently activate and mine these often complex 3D molecules, sufficient production of target molecules for further engineering and application remain a considerable bottleneck. An example of these bioactive scaffolds are armeniaspirols, which are potent polyketide antibiotics against gram-positive pathogens and multi-resistance gram-negative Helicobacter pylori. Here, we examine upregulation of armeniaspirols through engineering of biosynthetic pathways and primary metabolism; including perturbation of genes in biosynthetic gene clusters and regulation for triacylglycerols pool towards armeniaspirol upregulation. With either overexpression of extender unit pathway or late-stage N-methylation, or the deletion of a competing polyketide cluster, we can achieve 7-49-fold upregulation of armeniaspirols production. The most significant upregulation was achieved by expression of heterologous fatty acyl-CoA synthase, where we observed not only a 97-fold increase in production yields compared to wild type, but also an increase in the diversity of observed armeniaspirol analogs.

The IOT management platform is used to handle and transmit data from many types of power system terminal devices. The current IOT management platform has a low data processing efficiency and a high mistake rate when it comes to finding anomalous data. Furthermore, the effective selection and optimum decision of the convolutional neural network’s structural parameters has a significant impact on prediction performance. Based on this, the paper proposes a decision algorithm for locating anomalous data in an IOT integrated management platform using a convolutional neural network (CNN) and a global optimization decision of key structural parameters of a convolutional neural network using an improved particle swarm optimization (APSO) algorithm. First, an index model is created to determine if the data retrieved from the IOT management platform is anomalous or not. Second, the structure of the convolutional neural network-based decision method for finding anomalous data is examined. Following that, an enhanced particle swarm optimization technique is developed to optimize the structural parameters of the convolutional neural network, and an APSO-CNN with improved performance for anomalous data localization is generated. Finally, the established algorithm’s correctness, feasibility, and efficacy were evaluated using the Adam optimizer. The results reveal that the established APSO-CNN-based decision algorithm for anomaly data localization offers considerable benefits in terms of accuracy and running time, with extremely interesting application potential.

Schizophrenia remains a sizable socioeconomic burden that continues to be treated with therapeutics based on 70-year old science. All currently approved therapeutics primarily target the dopamine D2 receptor to achieve their efficacy. Whilst dopaminergic dysregulation is a key feature in this disorder, the targeting of dopaminergic machinery has yielded limited efficacy and an appreciable side effect burden. Over the recent decades, numerous drugs that engage non-dopaminergic GPCRs have yielded a promise of efficacy without the deleterious side effect profile, yet none have successfully completed clinical studies and progressed to the market. More recently, there has been increased attention around non-dopaminergic GPCR-targeting drugs, notably KarXT, which demonstrated efficacy in some schizophrenia symptom domains. This provides renewed hope that effective schizophrenia may lay outside of the dopaminergic space. Despite the potential for muscarinic receptor- (and other well-characterised GPCR families) targeting drugs to treat schizophrenia, they are often plagued with complications such as lack of receptor subtype selectivity and peripheral on-target side-effects. Orphan GPCR studies have opened a new avenue of exploration with many demonstrating schizophrenia-relevant mechanisms and a favourable expression profile, thus offering potential for novel drug development. This review discusses centrally-expressed orphan G protein-coupled receptors: GPR3, GPR6, GPR12, GPR52, GPR85, GPR88 and GPR139 and their relationship to schizophrenia. We review their expression, signalling mechanisms and cellular function, in conjunction with small molecule development and structural insights. We seek to provide a snapshot of the growing evidence and development potential of new classes of schizophrenia therapeutics.

Biaxial tension/compression-torsion fatigue tests with varying levels of non-proportionality were performed employing a structural adhesive designed for wind turbine rotor blades. The cycles to failure were found to be independent of the level of non-proportionality. It is demonstrated that numerical fatigue life predictions via rainflow-counted equivalent stress histories are not able to replicate these experimental observations and overestimate the fatigue life up to a hundredfold. The tension-compression asymmetry of the adhesive resulted in significant damage prediction differences depending on the stress space representation of the Haigh diagram. If not properly taken care of, the asymmetry will also lead to non-conservative results. While demonstrated with a short fiber reinforced adhesive, the results can be transferred to other materials.

Although parasites reduce host health, parasite infections also occur as a consequence of compromised host health. Both causalities could induce positive feedback, in which infected hosts with poor body conditions may suffer further infection, but it has rarely been demonstrated in the wild, possibly due to methodological difficulties. We used a mark-recapture survey combined with structural equation modelling (SEM) to examine whether both causalities and positive feedback occurred in stream salmonid and parasitic copepod systems. We found that parasitic copepods reduced host conditions and hosts with poor conditions were likely to be infected, suggesting that positive feedback can occur in the wild. Importantly, heavily infected hosts with poor body conditions showed lower apparent survival rates. Our findings provide robust evidence showing host condition–parasite infection dynamics, offering novel insights into how positive feedback could strongly undermine the wild host population via reduction of host survival.

AbstractMining areas characterized by high underground water levels are one of the most important types of coal mining areas in China. In regions with high groundwater levels, the soil ecological environment is destroyed due to surface subsidence induced by coal mining and soil disturbances. There are a variety of soil factors each with different degrees of spatial variation, and the impact on soil microbial communities is particularly severe. In order to explore the change and driving mechanism of soil microbial community structure in coal mining subsidence areas with high underground water levels, we sought to elucidate these mechanisms by studying soil samples collected at different depths (SL: 0-20 cm, ML: 20-40 cm, DL: 40-60 cm) of a deep coal seam subsidence area (T1) and shallow coal seam subsidence area (T2) and their control non-subsidence areas (W1 and W2) within a typical coal mine area with high underground water levels in southwest Shandong Province. These soil samples were used for determination and analysis of their physicochemical properties and microbial diversity. The results show that coal mining subsidence has significant effects on the soil physicochemical properties and soil microbial community. With the increase in sampling depth, the soil water content (SWC), bulk density (BD), and soil pH increased, whereas the contents of soil alkali-hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM) decreased. Compared with the non-subsidence area, the soil alkalinity in the subsidence area was lower and the soil moisture content, affected by the underground water level, was higher; the richness and diversity of the microbial community was lower in the subsidence area despite its higher relative abundance of Actinobacteria, Chloroflexi, and Myxomycota species. In addition, species of Thelebolales and Pleosporales were dominant in T1 and T2, respectively. Soil pH was observed to be the most important physicochemical factor affecting microbial communities, followed by AN and AP. The results of our study provide a theoretical basis for soil ecological restoration and land reclamation in mining areas with high underground water levels.

Background Several good results of clinical trial of nivolumab or involving nivolumab in advanced esophageal squamous cell carcinoma were reported. However, the response rate was still poor. A rare phenomenon called the “abscopal effect” refers to the regression of not only the irradiated tumor but also non-irradiated distant tumors after local radiotherapy. The mechanism is not completely clear, but it is thought that the activation of anti-tumor immunity induced by radiotherapy is the main factor. Case A 66-year-old man with recurred and nivolumab resistant esophageal squamous cell carcinoma in left-side cervical and abdominal para-aortal lymph node metastasis was treated with a total of 40 Gy (10 fractions) of radiotherapy to the left-side cervical lymph node metastasis which caused neck pain as a palliative treatment. Nivolumab was resumed the day after completion of radiotherapy. At 3 months after radiotherapy showed that the irradiated lesion in the left neck had regressed to a scar-like appearance. Notably, the abdominal para-aortal lymph nodes outside the irradiation area, which had previously tended to progress, had also shrunk (abscopal effect). The T cell receptor and B cell receptor (TCR/BCR) repertoire analysis before and after radiotherapy revealed that radiotherapy caused the changes in the TCR/BCR repertoire. Conclusion Changes in the TCR/BCR receptor repertoire repertoires were assumed to be a part of the mechanism of the abscopal effect. The findings in this patient suggest that combination of immune checkpoint inhibitors and radiotherapy can be a promising treatment approach, even for patients with immune checkpoint inhibitors resistant cancer.

Soil erosion is a serious environmental degradation controlled by several natural and anthropogenic factors. The Yellow River Basin (YRB) has been considered one of the most serious soil erosion regions in the world. In the past decades, revegetation projects accompanying apparent climate changes in the YRB region have aroused great uncertainty regarding soil erosion. Therefore, identifying and mapping the spatial controlling factors would be of great help in adopting targeting strategies for soil erosion prevention. The spatial-temporal changes of soil erosion from 1985 to 2018 in the YRB region were estimated by using the RUSLE model and its spatial controlling factors were identified and mapped by using the Mann-Kendall test and Sen’s test. The results indicated that the slight erosion intensity accounted for 68.25% to 70.17% of the entire basin from 1985 to 2018, and the average erosion modulus of the entire YRB region was 2009.81 t∙km -2∙yr -1. The erosion modulus in the middle reach (3245. 56 t∙km -2∙yr -1) was significantly greater than in the lower (1084. 56 t∙km -2∙yr -1) and upper (1135. 90 t∙km -2∙yr -1) reaches. Vegetation coverage, rainfall, and land-use changes accounted for 42.07%, 52.23%, and 1.77%, respectively, of the soil erosion change areas. Specifically, 40.19% of the vegetation coverage increase area was responsible for the decrease in soil erosion that was located mainly in the middle and upper reaches, while 42.30% of the rainfall increase area contributed to the increase in soil erosion that was located mainly in the upper and lower reaches.

In recent years, developing dopant-free carrier-selective contacts, instead of heavily doped Si layer (either externally or internally), for crystalline silicon (c-Si) solar cells have attracted considerable interests with the aims to reduce parasitic light absorption and fabrication cost. However, the stability still remains a big challenge for dopant-free contacts, especially when thermal treatment is involved, which limits their industrial adoption. In this study, a perovskite material ZnTiO 3 combining with an ultrathin (~1 nm) SiO 2 film and Al layer is used as an electron-selective contact, forming an isotype heterojunction with n-type c-Si. The perovskite/c-Si heterojunction solar cells exhibit a performance-enhanced effect by post-metallization annealing when the annealing temperature is 200-350 °C. Thanks to the post-annealing treatment, an impressive efficiency of 22.0% has been demonstrated, which is 3.5% in absolute value higher than that of the as-fabricated solar cell. A detailed material and device characterization reveal that post annealing leads to the diffusion of Al into ZnTiO 3 film, thus doping the film and reducing its work function. Besides, the coverage of SiO 2 is also improved. Both these two factors contribute to the enhanced passivation effect and electron selectivity of the ZnTiO 3-based contact, and hence improve the cell performance.

The distinction of loci under local adaptive evolution from background selection has been one of the main challenges to evolutionary genomicists. Matthey-Doret and Whitlock (2019) concluded from their simulation that background selection does not affect FST severely for the inference of local adaptation. Even though this conclusion is logically correct, the field of evolutionary genomics will be benefited much more if the conclusion were ‘dΧΥ should be used to infer local adaptation’.

By protein structure prediction (PSP) we refer to the prediction of the 3-dimensional (3D) folding of a protein, known as tertiary structure, starting from its amino acid sequence, known as primary structure. The state-of-the-art in PSP is currently achieved by complex deep learning pipelines that require several input features extracted from amino acid sequences. It has been demonstrated that features that grasp the relative orientation of amino acids in space positively impacts the prediction accuracy of the 3D coordinates of atoms in the protein backbone. In this paper, we demonstrate the relevance of Geometric Algebra (GA) in instantiating orientational features for PSP problems. We do so by proposing two novel GA-based metrics which contain information on relative orientations of amino acid residues. We then employ these metrics as an additional input features to a Graph Transformer (GT) architecture to aid the prediction of the 3D coordinates of a protein, and compare them to classical angle-based metrics. We show how our GA features yield comparable results to angle maps in terms of accuracy of the predicted coordinates. This is despite being constructed from less initial information about the protein backbone. The features are also fewer and more informative, and can be (i) closely associated to protein secondary structures and (ii) more readily predicted compared to angle maps. We hence deduce that GA can be employed as a tool to simplify the modeling of protein structures and pack orientational information in a more natural and meaningful way.

Background Artificial intelligence (AI) is a promising field in the neonatal field.  We focused on lung ultrasound (LUS), a useful tool for the neonatologist. Our aim was to train a neural network to create a model able to interpret LUS. Methods Our multicentric, prospective study included newborns with gestational age (GA) ≥ 33+0 weeks with early tachypnea/dyspnea/oxygen requirements. For each baby, three LUS were performed: within 3 hours of life (T0), at 4–6 hours of life (T1) and in the absence of respiratory support (T2). Each scan was processed to extract ROI used to train a neural network to classify it according to the LUS score. We assessed sensitivity, specificity, positive and negative predictive value of the AI model’s scores in predicting the need for respiratory assistance with nasal Continuous Positive Airway Pressure (nCPAP) and for surfactant, compared to the “classical” scores. Results We enrolled 62 newborns (GA=36±2 weeks). In the prediction of the need for CPAP, we found a cut-off of 6 (at T0) and 5 (at T1) for both the classical nLUS and AI score. In the prediction of surfactant therapy we found a cut-off of 9 for both scores at T0, at T1 the nLUS cut-off was 6, while the AI’s one was 5. Classification accuracy was good both at the image and classes level. Conclusions This is, to our knowledge, the first attempt to use an AI model to interpret early neonatal LUS and can be extremely useful for neonatologist in the clinical setting.

Adhesion G protein-coupled receptors (aGPCRs) possess a unique topology including the presence of a GPCR proteolysis site (GPS) which upon autoproteolysis generates two functionally distinct fragments that remain non-covalently associated at the plasma membrane. A proposed activation mechanism for aGPCRs involves the release of a tethered agonist which depends on cleavage at the GPS. However, this hypothesis has been challenged by the observation that non-cleavable aGPCRs exhibit constitutive activity, thus making the function of GPS cleavage widely enigmatic. In this study, we sought to elucidate the function of GPS-mediated cleavage through the study of G protein coupling with Latrophilin-3/ADGRL3, a prototypical aGPCR involved in synapse formation and function. Using BRET-based G protein biosensors, we reveal that an autoproteolysis-deficient mutant of ADGRL3 retains constitutive activity. Surprisingly, we uncover that cleavage deficiency leads to a signaling bias directed at potentiating the activity of select G proteins such as Gi2 and G12/13. These data unveil the underpinnings of biased signaling for aGPCRs defined by GPS autoproteolysis.

ABSTRACT Intestinal cestode(tapeworm ) is characterized by multisegmented, scolex, and absence of digestive tracts as appears in our segments, we reported nine segments of tape worm with,scolex,neck,13-17 uterus branch, and scorpion like tail.

We describe a 63-year-old male with systemic AL amyloidosis with cardiac, renal, and liver involvement. After 4 courses of CyBorD, mobilization with G-CSF was initiated and CART was simultaneously performed for fluid retention. Anasarca gradually disappeared and he underwent autologous hematopoietic stem cell transplantation.

Urothelial cell carcinoma (UCC) is the ninth most common cancer that accounts for 4.7% of all the new cancer cases globally. UCC development and progression are due to complex and stochastic genetic programmes. To study the cascades molecular events underlying the poor prognosis that are due to limited treatment options for advance disease and resistance to conventional therapies in UCC, transcriptomics technology (RNA-Seq), a method of analysing the RNA content of a sample using the modern high-throughput sequencing platforms has been employed to address these limitations. Here we review the principles of RNA-Seq technology and summarize the recent studies on human bladder cancer that employed this technique to unravel the pathogenesis of the disease, identify biomarkers, discover pathways and classify the disease state. We list the commonly used computational platforms and software that are publicly available for RNA-Seq analysis. Moreover, we discussed the future perspective for RNA-Seq studies on bladder cancer and recommend the application of new technology called single cell sequencing (scRNA-Seq) to further understand bladder cancer.

The pernicious nature of low quality sequencing data warrants improvement in the bioinformatics workflow for profiling microbial diversity. The conventional merging approach, which drops a copious amount of sequencing reads when processing low quality amplicon data, requires alternative methods. In this study, a computational workflow, a combination of merging and direct-joining where the paired-end reads lacking overlaps are concatenated and pooled with the merged sequences, is proposed to handle the low quality amplicon data in microbial ecology research. The proposed computational strategy was compared with two workflows; the merging approach where the paired-end reads were merged, and the direct-joining approach where the reads were concatenated. The results showed that the merging approach generates a significantly low number of amplicon sequences, limits the microbiome inference and obscures some microbial associations. In comparison to other workflows, the combination of merging and direct-joining strategy reduces the loss of amplicon data, improves the taxonomy classification and importantly, abates the misleading results associated with the merging approach when analysing the low quality amplicon data. The mock community analysis also supports the findings. Thus, the researchers are suggested to analyse merged sequences along with directly-joined unmerged reads to avoid problems associated with low quality data while profiling the microbial community structure.

A study was under taken to isolate and screen selected beneficial microbes, which can restore soil fertility in the chosen flood-affected areas of Attapady and Nelliyampathy in Palakkad district of Kerala, India. A total of 76 isolates (40 N-fixers, 26 P-solubilizers and 10 K-solubilizers) were obtained from the flood affected areas. Triple enzyme activities of cellulase, laccase and dehydrogenase were recorded in 47.36% of N-fixers from Attapadi, 36.36% P-solubilizers and 60% K-solubilizers from Nelliyampathy. Six diverse maximal enzyme producers were selected based on study of microbial dry weight and plant growth-promoting characteristics, including nitrogen(N) fixation, phoshphate(P), potassium(K), and indole acetic acid(IAA) synthesis. These 6 isolates were ranked according to all the evaluated characteristics using statistical analysis, and the top 3 isolates were found. The most efficient multi-functional N-fixer was identified as Priestia megaterium from Attapadi which ranked first, Aspergillus terreus as the most capable P-solubilizer from Nelliyampathy and Talaromyces pinophilus as the most proficient K-solubilizer from Nelliyampathy. The competence of these three isolates from flood affected regions could help in the rejuvenation of the soil organic matter (SOM) in degraded soils. However further evaluation under field conditions are required to confirm these results.

Estimating of soil sorptivity ( S ) and saturated hydraulic conductivity ( K s ) parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by Haverkamp et al. (1994) allows the modeling of the cumulative infiltration process, from which the hydraulic parameters can be estimated. This model depends on both initial and final values of the soil hydraulic conductivity, initial soil sorptivity, the volumetric water content increase ( ∆ θ ), and two infiltration constants, the so-called β and γ parameters. However, to reduce the number of unknown variables when inverting experimental data, constant parameters such as β and γ are usually prefixed to 0.6 and 0.75, respectively. In this study, the values of these constants are investigated using numerical infiltration curves for different soil types and initial soil water contents for the van Genuchten-Mualem (vGM) soil hydraulic model. Our approach considers the long-time expansions of the Haverkamp model, the exact soil properties such as S , K s , and initial soil moisture to derive the value of the β and γ parameters for each specific case. We then generated numerically cumulative infiltration curves using Hydrus 3-D software and fitted the long-time expansions to derive the value of the β and γ parameters. The results show that these parameters are influenced by the initial soil water content and the soil type. However, for initially dry soil conditions, some prefixed values can be proposed instead of the currently used values. If an accurate estimate of S and K s is the case, then for coarse-textured soils such as sand and loamy sand, we propose the use of 0.9 for both constants. For the remaining soils, the value of 0.75 can be retained for γ . For β constant, 0.75 and 1.5 values can be considered for, intermediate permeable soils (sandy loam and loam) and low permeable soils (silty loam and silt), respectively. We clarify that the results are based on using the vGM model to describe the hydraulic functions of the soil and that the results may differ, and the assumptions may change for other models.

We present a case report of an immunocompetent African young man who presented with persistent chest pain and fever, and was diagnosed with EPTB following chest CT scan, pleural biopsy histopathology examination and Ziehl-Neelsen (ZN) staining, and pleural fluid gene Expert studies.

Necrotizing pneumonia (NP) is a severe form of lung disease with a high mortality rate. Although NP generally occurs as a complication in community-acquired pneumonia, our case illustrates that NP can occur as a secondary infection even if the clinical course of COVID-19 pneumonia is favorable, particularly in intubated patients.

The use of pulsed dc-sputtering sources for reactive magnetron sputtering with oxygen offers a possibility to suppress the negative effects of target poisoning (such as arcing). This results in a wide process range for the selection of a desired operating point. The control of target poisoning plays a major role in maintaining constant coating properties and affects the stoichiometry of the reactive coating, as well as the coating rate and the economic impact of the coating process. In a hysteresis, the target poisoning during the reactive sputtering of titanium under oxygen addition proceeds nonlinearly. Without the use of a suitable target poisoning control technique, the sputtering process can abruptly change to an unstable state. As a result, variations of stoichiometry can occur during the deposition process. A proven method for maintaining a stable reactive sputtering process is the control of oxygen flow with the input variable target voltage. By determining the typical oxygen hysteresis at constant target power and constant argon flow, an operating point for the control loop is derived. The desired target voltage then serves as the input variable for the control loop of the target poisoning. The controlling technique for target poisoning is a basic requirement for the production of the photolytic active anatase phase of titanium dioxide (TiO2) using reactive magnetron sputtering. The photocatalytic equipment of surfaces with a titanium dioxide coating in the anatase phase can be realized with the reactive pulsed dc magnetron sputter ion plating process (DC-MSIP). The pulsed DC-MSIP process facilitates coating a variety of surfaces at temperatures below 200 °C in an environmentally friendly manner.