Alternative Sequences Research Articles

Social context affects sequence modification learning in birdsong

Social interactions are crucial for imitative vocal learning such as human speech learning or song learning in songbirds. Recently, introducing specific learned modifications into adult song by experimenter-controlled reinforcement learning has emerged as a key protocol to study aspects of vocal learning in songbirds. This form of adult plasticity does not require conspecifics as a model for imitation or to provide social feedback on song performance. We therefore hypothesized that social interactions are irrelevant to, or even inhibit, song modification learning. We tested whether social context affects song sequence learning in adult male Bengalese finches (Lonchura striata domestica). We targeted specific syllable sequences in adult birds’ songs with negative auditory feedback, which led the birds to reduce the targeted syllable sequence in favor of alternate sequences. Changes were apparent in catch trials without feedback, indicating a learning process. Each experiment was repeated within subjects with three different social contexts (male–male, MM; male–female, MF; and male alone, MA) in randomized order. We found robust learning in all three social contexts, with a nonsignificant trend toward facilitated learning with social company (MF, MM) compared to the single-housed (MA) condition. This effect could not be explained by the order of social contexts, nor by different singing rates across contexts. Our results demonstrate that social context can influence degree of learning in adult birds even in experimenter-controlled reinforcement learning tasks, and therefore suggest that social interactions might facilitate song plasticity beyond their known role for imitation and social feedback.

A Unique Intramolecular Redox Reaction by Unidirectional Migration of Three Hydrogen Atoms: Theoretical Elucidation of the 3H-Transfer Sequence.

The intramolecular migration of three hydrogen atoms from one moiety of a gaseous radical cation to the other prior to fragmentation is an extremely rare type of redox reaction. Within the scope of this investigation, this scenario requires an ionized but electron-rich arene acceptor bearing a para-(3-hydroxyalkyl) residue. The precise mechanism of such unidirectional 3H transfer processes, including the order of the individual H transfer steps, has remained unclear in spite of previous isotope labelling and recent infrared ion spectroscopy (IRIS) studies. Herein, the details of this peculiar process have been investigated for ionized 4-(N,N-dimethylaminophenyl)-2-butanol, 2, by state-of-the-art density functional theory (DFT) calculations. The energetically most favorable pathway consists of a sequence of successive 1,4-, 1,6- and 1,5-H steps. During these steps the secondary alcohol functionality is oxidized to a carbonyl group and the radical-cationic aniline ring is reduced to an ionized 2,3-dihydroaniline unit. Several alternative sequences, such as three successive 1,5-H shifts, could be excluded. A concomitant unidirectional 2H migration reaction of the ion 2 was also investigated and the intermediacy of ion-neutral complexes (INCs) enabling sequential hydride and proton transfer was confirmed by the calculations.

Comparison of two alternative sequences with cabazitaxel and 177Lu-PSMA-617 in metastatic castration-resistant prostate cancer: A retrospective multicenter study (LuCaS).

Cabazitaxel and 177Lu-PSMA-617 have been shown to improve survival in patients with metastatic castration-resistant prostate cancer (mCRPC) previously treated with docetaxel and androgen receptor pathway inhibitors (ARPI). we aimed to evaluate the impact of sequencing cabazitaxel and 177Lu-PSMA-617 on survival outcomes in patients with mCRPC. This is a retrospective, multicenter, cohort study which included patients with mCRPC who received sequential treatment with 177Lu-PSMA-617 and cabazitaxel between January 2015 and December 2023. Primary outcome was progression-free survival-2 (PFS-2) RESULTS: A total of 68 patients with mCRPC who received sequential 177Lu-PSMA-617 and cabazitaxel were included in the study. The primary outcome, progression-free survival-2 (PFS-2), was similar in patients treated with 177Lu-PSMA-617 first (LU-CA) and those receiving cabazitaxel (CA-LU) first (10.8 and 11.7 months, respectively; p = 0.422). The median overall survival (OS) was also similar in the LU-CA and CA-LU groups (16.6 and 19.9 months, respectively; p = 0.917). The objective response rate (ORR) for 177Lu-PSMA-617 was 23.1 % when used first and 16.1 % after cabazitaxel. ORR for cabazitaxel was 25.6 % and 31.3 % when used as the first agent and when used after 177Lu-PSMA-617, respectively. In conclusion, treatment sequencing between cabazitaxel and 177Lu-PSMA-617 did not significantly affect survival outcomes in patients with mCRPC. These findings suggest that both drugs can be effectively integrated into the mCRPC treatment paradigm without concerns about the effect of sequencing. However, prospective data are needed to optimize sequencing strategies and explore their impact on specific patient subgroups for more personalized care.

Flexibility in PAM Recognition Expands DNA Targeting in xCas9.

xCas9 is an evolved variant of the CRISPR-Cas9 genome editing system, engineered to improve specificity and reduce undesired off-target effects. How xCas9 expands the DNA targeting capability of Cas9 by recognizing a series of alternative Protospacer Adjacent Motif (PAM) sequences while ignoring others is unknown. Here, we elucidate the molecular mechanism underlying xCas9's expanded PAM recognition and provide critical insights for expanding DNA targeting. We demonstrate that while wild-type Cas9 enforces stringent guanine selection through the rigidity of its interacting arginine dyad, xCas9 introduces flexibility in R1335, enabling selective recognition of specific PAM sequences. This increased flexibility confers a pronounced entropic preference, which also improves recognition of the canonical TGG PAM. Furthermore, xCas9 enhances DNA binding to alternative PAM sequences during the early evolution cycles, while favouring binding to the canonical PAM in the final evolution cycle. This dual functionality highlights how xCas9 broadens PAM recognition and underscores the importance of fine-tuning the flexibility of the PAM-interacting cleft as a key strategy for expanding the DNA targeting potential of CRISPR-Cas systems. These findings deepen our understanding of DNA recognition in xCas9 and may apply to other CRISPR-Cas systems with similar PAM recognition requirements.

Mathematically inspired structure design in nanoscale thermal transport.

Mathematically inspired structure design has emerged as a powerful approach for tailoring material properties, especially in nanoscale thermal transport, with promising applications both within this field and beyond. By employing mathematical principles, based on number theory, such as periodicity and quasi-periodic organizations, researchers have developed advanced structures with unique thermal behaviours. Although periodic phononic crystals have been extensively explored, various structural design methods based on alternative mathematical sequences have gained attention in recent years. This review provides an in-depth overview of these mathematical frameworks, focusing on nanoscale thermal transport. We examine key mathematical sequences, their foundational principles, and analyze the influence of thermal behavior, highlighting recent advancements in this field. Looking ahead, further exploration of mathematical sequences offers significant potential for the development of next-generation materials with tailored, multi-functional properties suited to diverse technological applications.

Comprehensive multi-metric analysis of user experience and performance in adaptive and non-adaptive lower-limb exoskeletons.

Among control methods for robotic exoskeletons, biologically inspired control based on central pattern generators (CPGs) offer a promising approach to generate natural and robust walking patterns. Compared to other approaches, like model-based and machine learning-based control, the biologically inspired control provides robustness to perturbations, requires less computational power, and does not need system models or large learning datasets. While it has shown effectiveness, a comprehensive evaluation of its user experience is lacking. Thus, this study addressed this gap by investigating the performance of a state-of-the-art adaptive CPG-based exoskeleton control system (intelligent mode) under a multi-metric analysis (involving three-dimensional gait analysis, muscle activity, oxygen consumption, user comfort, and exoskeleton performance scores) and comparing it to a standard commercial exoskeleton control system (default mode). A cross-over design with randomized allocation in Thai healthy and independently walking adults ensured participants experienced both modes. All participants were assigned into two groups to receive an alternate sequence of walking with the intelligent mode or the default mode of the lower-limb exoskeleton Exo-H3 at high and normal speed. From eight participants, the intelligent mode-driven exoskeleton (adaptive exoskeleton) showed a significantly lower velocity, stride, and step lengths than the default mode-driven exoskeleton (non-adaptive exoskeleton). This setup significantly increased anterior pelvic tilt during mid-swing at normal speed (3.69 ± 1.77 degrees, p = 0.001) and high speed (2.52 ± 1.69 degrees, p = 0.004), hip flexion during stance phase with ankle dorsiflexion, and used less oxygen consumption at high speed (-2.03 ± 2.07 ml/kg/min) when compared to the default one. No significant differences of muscle activity, user comfort and exoskeleton performance scores between the two modes. Further exoskeletal modification in terms of hardware and control is still needed to improve the temporal spatial, kinematics, user comfort, and exoskeleton performance.

RANK REVERSAL IN ECONOMIC DECISION MAKING

Economic decision making is often based on a sequence of ranking alternatives to ensure reasonable decisions. Cases of rank reversals, in which the order of preference of choices is altered by the introduction or removal of options, present important issues. This study examines the occurrence of degree of change characterized by uncertainty in economic parameters in environment Z. The study examines the causes of rate fluctuations and their implications for economic theory and practice using advanced decision-making models and simulations The findings show that rank change in environment Z is not only a theoretical irregularity, but also a real concern that can lead to bad economic outcomes. This study presents a relatively low-complexity, theoretically driven, and comprehensive method to decision-making under bimodal uncertainty, as represented by Z-numbers. The suggested technique for making decisions is based on the consistency-driven preferences creation method, and the eigenvector determination method of Z-number valued matrixes. The study concludes with recommendations to avoid rate-shifting in economic decision-making, emphasizing the need for vigorous modeling approaches and sensitivity analysis. The recommended method's correctness and viability are demonstrated with an numerical example using Z-lab tool created for calculation of Z-numbers and sets. Keywords: Z-number, economic decision making, consistent preferences.

Optimizing treatment sequencing in multiple myeloma: a novel model to predict survival outcomes

ABSTRACT Objective Patients with multiple myeloma (MM) typically require multiple regimens and become harder to treat with each line of treatment. Furthermore, there is a lack of direct comparative clinical trial data to guide effective treatment sequencing. A novel model is described comparing alternative MM treatment sequences to optimize patient outcomes. Methods The model compares treatment sequences and outcomes for adults with newly diagnosed transplant-eligible (TE) or transplant-ineligible (TIE) MM across four treatment lines (first-line [FL] to fourth-line [4L]). Inputs are derived from patient-level data from clinical trials and indirect treatment comparisons. We report a base case prediction using data representing clinical practice in Italy. Results For FL TE, overall survival (OS) and progression-free survival (PFS) were greatest for FL regimens containing daratumumab; OS ranged from 11.80–18.10 years. PFS ranged from 4.82–13.42 years (FL) to 0.66–6.03 years (second-line [2L]), 0.81–1.76 years (third-line [3L]), and 0.69–0.72 years (4L). For FL TIE, OS rates were greater for treatment sequences with FL daratumumab vs. sequences with either 2L or no daratumumab (OS ranging from 5.95–10.61 years). PFS was greatest for FL daratumumab regimens in the TIE group, with PFS ranging from 2.12–7.48 years (FL), 0.53–4.73 years (2L), 0.63–1.17 years (3L), and 0.42 years (4L). Discussion This novel model demonstrates that using the most effective treatment in FL optimizes treatment sequencing and clinical outcomes for patients. Conclusion The optimal MM treatment sequences begin with daratumumab-containing regimens in FL and improve outcomes compared with alternative sequences.

Energy Budgeting of Different Cropping Sequences in the Indian Upper Gangetic Plains

Background: This study is meant to examine the energy requirement and energy input- output of different cropping sequences .The crucial objective to conduct experiment to understand energy efficiency using inputs and outputs which were disbursed in cropping sequences. Hence, it is need of the hour to identify the most remunerative and cost effective cropping sequence with high energy efficient for UGP of India. Methods: This study was carried out at the research farm of ICAR-Indian Institute of Farming Systems Research, Modipuram, during 2017-2021.The divergent cropping sequences viz. sugarcane-ratoon-wheat (CS1); rice-wheat-dhaincha (CS2); pigeonpea +maize-chickpea-okra (CS3); maize-berseem-black gram (CS4); sorghum-mustard-green gram (CS5) and Napier+cowpea/berseem (CS6) were compared in reference to curtail higher energy inputs through selected alternate cropping sequences. The obtained energy values were calculated by multiplying the amount of inputs and outputs by using energy conversion factors. Result: Maximum inputs energy consumed by sugarcane crop alone (33.14x103 MJ ha-1). Results shown that irrigation, seed, fertilizers and diesel required higher energy for the completion of cultural operations. However, higher inputs energy was used in irrigation followed by seed and fertilizers, respectively. In regard to per cent energy intake through inputs, the highest energy spent was for irrigation (35.30 MJ ha-1) and fertilizer (23.80 MJ ha-1).The wheat equivalent yield was higher in sugarcane-ratoon-wheat (125.58 t ha-1). Maximum output energy was with above system (596.70×103 MJ ha-1). Highest net energy returns was counted with sugarcane-ratoon-wheat (549.37x103 MJ ha-1), energy ratio (12.60) and energy profitability (11.60). Indeed, energy efficiency was highest in same system (1657.50) followed by maize-berseem-black gram (1421.96).

Genes to therapy: a comprehensive literature review of whole-exome sequencing in neurology and neurosurgery

Whole-exome sequencing (WES), a ground-breaking technology, has emerged as a linchpin in neurology and neurosurgery, offering a comprehensive elucidation of the genetic landscape of various neurological disorders. This transformative methodology concentrates on the exonic portions of DNA, which constitute approximately 1% of the human genome, thus facilitating an expedited and efficient sequencing process. WES has been instrumental in advancing our understanding of neurodegenerative diseases, neuro-oncology, cerebrovascular disorders, and epilepsy by revealing rare variants and novel mutations and providing intricate insights into their genetic complexities. This has been achieved while maintaining a substantial diagnostic yield, thereby offering novel perspectives on the pathophysiology and personalized management of these conditions. The utilization of WES boasts several advantages over alternative genetic sequencing methodologies, including cost-effectiveness, reduced incidental findings, simplified analysis and interpretation process, and reduced computational demands. However, despite its benefits, there are challenges, such as the interpretation of variants of unknown significance, cost considerations, and limited accessibility in resource-constrained settings. Additionally, ethical, legal, and social concerns are raised, particularly in the context of incidental findings and patient consent. As we look to the future, the integration of WES with other omics-based approaches could help revolutionize the field of personalized medicine through its implications in predictive models and the development of targeted therapeutic strategies, marking a significant stride toward more effective and clinically oriented solutions.Graphical

Unified specification tests in partially linear time series models

Based on a residual marked empirical process, Cramér–von Mises and Kolmogorov–Smirnov tests are proposed for the correct specification of the nonparametric components in partially linear time series models. The tests are unified in the sense that the asymptotic distribution of residual marked empirical process is invariant across different nν-consistent estimators in calculating residuals (where ν>1/4) under the null. In addition, the residual marked empirical process has the same power property under the sequence of local alternatives regardless of the estimators used. Achieved through a projection method, these features also enable using a computationally convenient multiplier bootstrap to approximate the unified null distributions of the test statistics. Simulations show satisfactory finite-sample performance of the proposed method. The application to validate the parametric form of conditional variance in the ARCH-X model is also highlighted, along with an empirical analysis of the conditional variance of the FTSE 100 index return series.

Synthesis and immunological study of tetrasaccharide repeating units of capsular polysaccharide of Group B Streptococcus serotype VIII and their protein conjugates

This study reports the efficient synthesis of three tetrasaccharide derivatives of Group B Streptococcus (GBS) serotype VIII capsular polysaccharide with alternative glycan sequences and spacer chains through a convergent chemical glycosylation manner or a one-pot three-enzyme assembly protocol. Using bifunctional glutarate ester as the linker, these synthesized oligosaccharides were efficiently conjugated with recombinant ScpA193 protein, generating the resultant oligosaccharide-ScpA193 conjugates with desirable carbohydrate loading. ELISA analysis of the antisera obtained from mice inoculated with the synthetic glycoconjugates showed the elicitation of strong oligosaccharide-specific immunoglobulin G (IgG) antibodies, suggesting the potential of the synthesized oligosaccharides for use in the development of GBS vaccines.

Phase diagram of the three-dimensional subsystem toric code

Subsystem quantum error-correcting codes typically involve measuring a sequence of noncommuting parity check operators. They can sometimes exhibit greater fault tolerance than conventional codes, which use commuting checks. However, unlike subspace codes, it is unclear if subsystem codes—in particular their advantages—can be understood in terms of ground-state properties of a physical Hamiltonian. In this paper, we address this question for the three-dimensional subsystem toric code (3D STC), as recently constructed by Kubica and Vasmer [], which exhibits single-shot error correction. Motivated by a conjectured relation between single-shot properties and thermal stability, we study the zero- and finite-temperature phases of an associated noncommuting Hamiltonian. By mapping the Hamiltonian model to a pair of 3D Z2 gauge theories coupled by a kinetic constraint, we find various phases at zero temperature, all separated by first-order transitions: There are 3D toric code-like phases with deconfined point-like excitations in the bulk, and there are phases with a confined bulk supporting a 2D toric code on the surface when appropriate boundary conditions are chosen. The latter is similar to the surface topological order present in 3D STC. However, the similarities between the single-shot correction in 3D STC and the confined phases are only partial: they share the same sets of degrees of freedom, but they are governed by different dynamical rules. Instead, we argue that the process of single-shot error correction can more suitably be associated with a path (rather than a point) in the zero-temperature phase diagram, a perspective, which inspires alternative measurement sequences enabling single-shot error correction. Moreover, since none of the above-mentioned phases survives at nonzero temperature, the single-shot error-correction property of the code does not imply thermal stability of the associated Hamiltonian phase. Published by the American Physical Society 2024

16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in Streptomyces.

Streptomyces is among the most extensively studied genera of bacteria but its complex taxonomy remains contested and is suspected to contain significant species-level misclassification. Resolving the classification of Streptomyces would benefit many areas of applied microbiology that rely on an accurate ground truth for grouping of related organisms, including comparative genomics-based searches for novel antimicrobials. We survey taxonomic conflicts between 16S rRNA and whole genome-based Streptomyces classifications using 2276 publicly available Streptomyces genome assemblies and 48 981 publicly available full-length 16S rRNA Streptomyces sequences from silva, Greengenes, Ribosomal Database Project (RDP), and NCBI (National Centre for Biotechnology Information) databases. We construct a full-length 16S gene tree for 14 239 distinct Streptomyces sequences that resolves three major lineages of Streptomyces, but whose topology is not consistent with existing taxonomic assignments. We use these sequence data to delineate 16S and whole genome landscapes for Streptomyces, demonstrating that 16S and whole-genome classifications are frequently in disagreement, and that 16S zero-radius Operational Taxonomic Units (zOTUs) are often inconsistent with Average Nucleotide Identity (ANI)-based taxonomy. Our results strongly imply that 16S rRNA sequence data does not map to taxonomy sufficiently well to delineate Streptomyces species routinely. We propose that alternative marker sequences should be adopted by the community for classification and metabarcoding. Insofar as Streptomyces taxonomy has been determined or supported by 16S sequence data and may in parts be in error, we also propose that reclassification of the genus by alternative approaches may benefit the Streptomyces community.

Updating and calibrating the Real-World Progression In Diabetes (RAPIDS) model in a non-Veterans Affairs population.

To present the Real-World Progression In Diabetes (RAPIDS) 2.0 Risk Engine, the only simulation model to study the long-term trajectories of outcomes arising from dynamic sequences of glucose-lowering treatments in type 2 diabetes (T2DM). The RAPIDS model's risk equations were re-estimated using a Least Absolute Shrinkage and Selection Operator (LASSO)-based regularization of features that spanned baseline data from the last two quarters of current time and interactions with age. These equations were supplemented with estimates for the impact of dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, and sodium-glucose cotransporter-2 inhibitor classes of drugs as monotherapies and their combinations with metformin based on newer trial data and comprehensive meta-analyses. The probabilistic RAPIDS 2.0 model was calibrated (N = 25 000) and validated (N = 263 816) using electronic medical records (EMR) data between 2008 and 2021 from a national network of US healthcare organizations. The EMR-based cohort had a mean age of 61 years at baseline, with 50% women, 70% non-Hispanic White individuals and 20% non-Hispanic Black individuals, and was followed for 17.5 quarters (range: 3-50). The final RAPIDS 2.0 risk engine accurately predicted the long-term trajectories of all nine biomarkers and nine outcomes in the hold-out validation sample. Similar accuracies in predictions were observed in each of the 14 subgroups studied. The RAPIDS 2.0 model demonstrated valid long-term predictions of outcomes in individuals with T2DM in the United States as a function of dynamic sequences of treatment use patterns. This highlights its potential to project long-term comparative effectiveness between alternative sequences of glucose-lowering treatment uses in the United States.

Unified specification tests in partially linear quantile regression models

We propose specification tests for parametric quantile regression models versus semiparametric alternatives over a continuum of quantile levels. The test statistics are constructed as continuous functionals of a quantile-marked residual process. We show that using an orthogonal projection on the tangent space of nuisance parameters at each quantile index delivers unified asymptotic properties for tests based on different estimators. Consistency of the tests and asymptotic power under a sequence of local alternatives converging to the null at a parametric rate are also discussed. We propose a simple multiplier bootstrap procedure to carry out the tests, whose nominal levels are well approximated in our simulation study for modest sample sizes.

Mitigation of Performance Degradation of PEM Water Electrolyzers by Power Distribution Control of Fluctuating Renewable Energy

Introduction Hydrogen production by water electrolysis using renewable energy such as wind and solar power generation (i.e., green hydrogen production) has attracted considerable attention as a key technology towards decarbonization. Proton exchange membrane (PEM) water electrolyzers are often used in combination with renewable energy source since they show fast response to input power fluctuation. However, lifetime of PEM electrolyzer needs to be improved for reducing hydrogen production cost. Recently we reported a durability analysis of PEM electrolyzers under wind power voltage fluctuations, where the reversible and irreversible voltage losses were analyzed in terms of gas bubble transport and catalyst degradation [1]. We also developed a novel control strategy called the power distribution control (PDC) that controls the power converters so that the input fluctuating power is decomposed to several fluctuating patterns that less degrade the electrolyzers than the input pattern [2]. The purpose of this study is to validate the effect of the PDC on mitigation of performance degradation of PEM electrolyzers under wind power fluctuations. Experimental method A membrane electrode assembly (MEA) with an active area of 1 cm2 was prepared using Nafion 117 membrane, IrO2 anode catalyst and Pt/KB cathode catalyst. The catalyst loading for anode and cathode was 0.5 mg IrO2/cm2 and 0.3 mg Pt/cm2, respectively. A PEM water electrolysis cell was prepared by assembling the MEA into a cell holder. The cell temperature was kept at 80°C during the durability test.Figure 1a) and 1b) show a schematic system diagram for performing the PDC and the two voltage fluctuation patterns (A and B) used for the durability test, respectively. As in our previous study [1], actual 24-h voltage fluctuation of wind power turbine was used as the primary data. The pattern A was prepared from the primary data by (i) scaling down the maximum voltage by 1/100 and setting the minimum voltage higher than the standard potential of water electrolysis and (ii) accelerating the time scale by 5 times. The pattern B was prepared by applying the PDC, that is, converting the pattern A into an alternative sequence of a high-operating rate pattern and a low-operating rate pattern as described in Ref. [2]. Here we set the average voltage of the high-operating rate pattern (~2.4 V) and the low-operating rate pattern (~1.7 V) as the same value with the voltage of the pattern A (~2.05 V) for each time, ensuring that we model the situation in which the input fluctuating power is distributed between two series of electrolyzers as shown in Fig. 1a). We performed 240-h durability tests and analyzed performance degradation of the PEM cell for the pattern A and B, respectively. Results and Discussion Figure 2 summarizes the performance degradation of the PEM cell during the 240-h durability test. The cell current density at the cell voltage of 2.1 V showed a steep decrease during the initial ~30 h for both pattern A and B. For 30 – 240 h, the current density continuously decreased for the pattern A (−0.68 mAcm-2/h), while no distinguishable decrease was observed for the pattern B (+0.06 mAcm-2/h). Therefore we successfully demonstrated that performance degradation of the PEM electrolyzers can be effectively suppressed by the PDC when using actual wind power voltage fluctuation as the input power.To further investigate the performance degradation behavior, the increase in overpotential components of the PEM cell was analyzed. Figure 2b) shows the comparison of overpotential components before and after the 240-h test. For the pattern A, the diffusion overpotential (E diff) showed a significant increase after the test for the current density higher than 1.0 mAcm-2. In contrast, for the pattern B, increase in E diff was suppressed and confirmed only for > 1.4 Acm-2. Increase in the activation overpotential (E act) was small compared to increase in E diff for both pattern A and B. Furthermore, we confirmed that the performance degradation confirmed in this study was reversible, that is, the current density was almost recovered within 24-h rest time after the test. These results are consistent with our previous study [1] in that the reversible degradation is related to gas bubble transport, that is, the increase in E diff. Therefore it was shown that the PDC suppresses reversible degradation, which is important for mitigating irreversible degradation during long-term operation. Our results demonstrate that PDC is a promising technique for improving lifetime of PEM electrolyzers operating under fluctuating renewable energy.

μ-Opioid receptor transcriptional variants in the murine forebrain and spinal cord

Oprm1, the gene encoding the μ-opioid receptor, has multiple reported transcripts, with a variable 3′ region and many alternative sequences encoding the C-terminus of the protein. The functional implications of this variability remain mostly unexplored, though a recurring notion is that it could be exploited by developing selective ligands with improved clinical profiles. Here, we comprehensively examined Oprm1 transcriptional variants in the murine central nervous system, using long-read RNAseq as well as spatial and single-cell transcriptomics. The results were validated with RNAscope in situ hybridization. We found a mismatch between transcripts annotated in the mouse genome (GRCm38/mm10) and the RNA-seq results. Sequencing data indicated that the primary Oprm1 transcript has a 3′ terminus located on chr10:6,860,027, which is ∼ 9.5 kilobases downstream of the longest annotated exon 4 end. Long-read sequencing confirmed that the final Oprm1 exon included a 10.2 kilobase long 3′ untranslated region, and the presence of the long variant was unambiguously confirmed using RNAscope in situ hybridization in the thalamus, striatum, cortex and spinal cord. Conversely, expression of the Oprm1 reference transcript or alternative transcripts of the Oprm1 gene was absent or close to the detection limit. Thus, the primary transcript of the Oprm1 mouse gene is a variant with a long 3′ untranslated region, which is homologous to the human OPRM1 primary transcript and encodes the same conserved C-terminal amino acid sequence.

Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays.

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r 2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.

Investigating cold tolerance mechanisms in rice seedlings: Alternative splicing, promoter analysis, and their applications for marker development

Cold stress harms rice seedlings, causing yield reduction. Enhancing cold tolerance at the seedling stage is crucial for rice breeding. OsFH10, OsFER1, ONAC045, and OsProT were selected to study gene expression including alternative splicing and promoter sequence analysis in rice seedlings. Under cold stress, the four genes exhibited alternative splicing showing intron retention isoforms, and displayed a consistent pattern of upregulation in a group of cold-tolerant varieties, while no isoforms were presented in a group of sensitive varieties. These intron retention isoforms might play a role in facilitating improved cold adaptation in rice seedlings. Promoter sequence analysis revealed polymorphisms of Single nucleotide polymorphisms (SNPs) or Insertions and Deletions (InDels) in ONAC045 and OsProT that distinguished cold-tolerant from cold-sensitive varieties. ONAC045 SNP and OsProT InDel markers were developed and validated using 159 rice lines. These markers were associated with cold tolerance (P < 0.05) and practical to use with general agarose gel. The ONAC045 marker showed high efficacy in predicting tolerance in rice germplasm seedlings, achieving an accuracy of 43.8%. Furthermore, the OsProT marker exhibited greater sensitivity towards cold-tolerant indica seedlings. Both markers have a wide distribution in all rice subspecies. Our findings elucidate the cold response mechanisms and provide insights into potential application in developing cold-tolerant indica rice varieties.