Multiple diffusion models-enhanced extremely limited-view reconstruction strategy for photoacoustic tomography boosted by multi-scale priors.

Photoacoustic tomography (PAT) is an innovative biomedical imaging technology, which has the capacity to obtain high-resolution images of biological tissue. In the extremely limited-view cases, traditional reconstruction methods for photoacoustic tomography frequently result in severe artifacts and distortion. Therefore, multiple diffusion models-enhanced reconstruction strategy for PAT is proposed in this study. Boosted by the multi-scale priors of the sinograms obtained in the full view and the limited-view case of 240°, the alternating iteration method is adopted to generate data for missing views in the sinogram domain. The strategy refines the image information from global to local, which improves the stability of the reconstruction process and promotes high-quality PAT reconstruction. The blood vessel simulation dataset and the in vivo experimental dataset were utilized to assess the performance of the proposed method. When applied to the in vivo experimental dataset in the limited-view case of 60°, the proposed method demonstrates a significant enhancement in peak signal-to-noise ratio and structural similarity by 23.08 % and 7.14 %, respectively, concurrently reducing mean squared error by 108.91 % compared to the traditional method. The results indicate that the proposed approach achieves superior reconstruction quality in extremely limited-view cases, when compared to other methods. This innovative approach offers a promising pathway for extremely limited-view PAT reconstruction, with potential implications for expanding its utility in clinical diagnostics.

Genome-wide association study of maternal plasma metabolites during pregnancy.

Metabolites are key indicators of health and therapeutic targets, but their genetic underpinnings during pregnancy-a critical period for human reproduction-are largely unexplored. Using genetic data from non-invasive prenatal testing, we performed a genome-wide association study on 84 metabolites, including 37 amino acids, 24 elements, 13 hormones, and 10 vitamins, involving 34,394 pregnant Chinese women, with sample sizes ranging from 6,394 to 13,392 for specific metabolites. We identified 53 metabolite-gene associations, 23 of which are novel. Significant differences in genetic effects between pregnant and non-pregnant women were observed for 16.7%-100% of these associations, indicating gene-environment interactions. Additionally, 50.94% of genetic associations exhibited pleiotropy among metabolites and between six metabolites and eight pregnancy phenotypes. Mendelian randomization revealed potential causal relationships between seven maternal metabolites and 15 human traits and diseases. These findings provide new insights into the genetic basis of maternal plasma metabolites during pregnancy.

Concurrent removal of Fe(II), Cu(II), and Zn(II) cations from acid mine drainage by an industrial solid waste - steel slag: Behaviors and mechanisms.

Acid mine drainage (AMD) contamination poses a severe environmental threat and is a significant risk to human health. There is an urgent need to develop environmentally sustainable and technically viable solutions for water contamination caused by heavy metals. In this study, steel slag (SS) was used as a secondary resource to concurrently remove Fe(II), Cu(II), and Zn(II) from AMD. Because of the loose and porous structure, abundant functional groups, fast sedimentation velocity, and excellent solid-liquid separation, SS showed exceptional removal performance for heavy metal ions. The adsorption kinetic data of Fe(II), Cu(II), and Zn(II) showed good regression with the pseudo-second-order model. Besides, the adsorption of Fe(II) by SS conformed to the Freundlich model, whereas the adsorption of Cu(II) and Zn(II) followed the Langmuir model, with the maximum adsorption amounts of Cu(II) and Zn(II) being 170.69 and 155.98 mg/g. Furthermore, competitive adsorption was observed among Fe (II), Cu (II), and Zn (II) in a multi-component system, with the adsorption priority being Fe (II) > Cu (II) > Zn (II). The removal mechanism of Fe(II), Cu(II), and Zn(II) in AMD by SS mainly includes electrostatic attraction, chemical precipitation, and surface complexation. Interestingly, the leached concentrations of Fe(II), Cu(II), and Zn(II) from the spent slag after calcination were all within the detection limit of the Chinese emission standard, demonstrating excellent environmental stability. Theoretically, this renders it a viable candidate for use as an additive in construction materials. Meaningfully, the work offers a practical approach for energy-efficient and eco-friendly heavy metal ions adsorption, and the secondary utilization of SS also contributes to the sustainable development of the steel industry. It is beneficial to implement the development concepts of clean production and efficient utilization of industrial solid waste.

Long-term effects of COVID-19 infection on bone mineral density.

Background: In this study, we aimed to identify bone mineral density (BMD) trajectories of hospitalised patients with coronavirus disease 2019 (COVID-19) and to determine the prognostic role of the trajectory groups. Methods: This is a retrospective study of hospitalised patients with COVID-19 treated in our hospital from November 2022 to February 2023. BMD was manually measured from the thoracic 12 (T12) and lumbar one (L1) vertebra using chest computed tomography images. We constructed group trajectory models using group-based trajectory modelling. We performed the logistic regression analysis to associate the BMD trajectory pattern with clinical outcomes. Results: This study included 1767 patients. The mean follow-up time after discharge was 181.5 days (standard deviation (SD) = 9.7). There were 1137 (64.3%) male patients, and more than 80% of patients were aged >60 years. We successfully identified three latent BMD trajectories to reveal the dynamic effects of COVID-19 infection on bone health in patients, namely, the early low-normal decline group, the average, and the early high-rapid decline group. All groups demonstrated consistent overall declining trends. A significant association was observed between BMD trajectory pattern (T12 or L1) and baseline characteristics of sex, age, and penetrating keratoplasty (P < 0.05). Our study showed that the BMD trajectories were significantly associated with mortality. Furthermore, we found that these trajectories were also associated with the length of hospital stay. Conclusions: This study provided evidence for the COVID-19 process to bone health, as well as evidence on strengthening bone health management before and after COVID-19 infection. BMD trajectories may help manage bone health and guide treatment in patients with COVID-19.

Engineered model of heart tissue repair for exploring fibrotic processes and therapeutic interventions.

Advancements in human-engineered heart tissue have enhanced the understanding of cardiac cellular alteration. Nevertheless, a human model simulating pathological remodeling following myocardial infarction for therapeutic development remains essential. Here we develop an engineered model of myocardial repair that replicates the phased remodeling process, including hypoxic stress, fibrosis, and electrophysiological dysfunction. Transcriptomic analysis identifies nine critical signaling pathways related to cellular fate transitions, leading to the evaluation of seventeen modulators for their therapeutic potential in a mini-repair model. A scoring system quantitatively evaluates the restoration of abnormal electrophysiology, demonstrating that the phased combination of TGFß inhibitor SB431542, Rho kinase inhibitor Y27632, and WNT activator CHIR99021 yields enhanced functional restoration compared to single factor treatments in both engineered and mouse myocardial infarction model. This engineered heart tissue repair model effectively captures the phased remodeling following myocardial infarction, providing a crucial platform for discovering therapeutic targets for ischemic heart disease.

Establishment of a non-integrated iPS cell line (SDQLCHi072-A) from a patient suffered from AUTS2 syndrome.

In this study, PBMCs used in reprogramming were from a boy suffered from AUTS2 syndrome confirmed by clinical and genetic diagnosis. iPSCs were established by non-integrated method, which carried AUTS2 heterozygous mutation. The established iPSCs presented similar appearance and expressed pluripotent markers in mRNA and protein level. Additionally, the iPSCs possessed favorable differentiative capacity in vivo and normal karyotype. This is an effective potential model for the study about AUTS2 syndrome and the screen about drug therapy.

Response characteristics of soil microorganisms under strong disturbance conditions in the riparian zone of the three Gorges reservoir Area.

The normal operation of the Three Gorges Reservoir, which involves periodic water storage and discharge, has led to strong disturbances in environmental conditions that alter soil microbial habitats in the riparian zones. Riparian zones are an important part of controlling pollution in the Three Gorges Reservoir area, since they act as a final ecological barrier that intercepts pollutants. Meanwhile, monitoring the health of microbial communities in the riparian zone is crucial for maintaining the ecological security of the reservoir area. We specifically investigate the Daning River, which are tributaries of the Three Gorges Reservoir and have typical riparian zones. Soil samples from these areas were subjected to high-throughput sequencing of 16S rRNA genes and 18S rRNA genes, in order to obtain the characteristics of the present microbial communities under strong disturbances in the riparian zones. We studied the characteristics and distribution patterns of microbial communities and their relationship with soil physicochemical properties. The study results indicate that microbial communities exhibit high diversity and evenness, and spatial heterogeneity is present. The ASV dataset contains many sequences not assigned to known genera, suggesting the presence of new fungal genera in the riparian zone. Redundancy analysis (RDA) revealed that pH and NH 4 + -N were the primary environmental factors driving bacterial community variation in the riparian zone, while pH, total carbon (TC) content, and NO 3 - -N were identified as the main drivers of soil archaeal community variation.

Systematic development of a highly efficient cell factory for 5-aminolevulinic acid production.

The versatile applications of 5-aminolevulinic acid (5-ALA) across the fields of agriculture, livestock, and medicine necessitate a cost-efficient biomanufacturing process. In this study, we achieved the economic viability of biomanufacturing this compound through a systematic engineering framework. First, we obtained a 5-ALA synthase (ALAS) with superior performance by exploring its natural diversity with divergent evolution. Subsequently, using a genome-scale model, we identified and modified four key targets from distinct pathways in Escherichia coli, resulting in a final enhancement of 5-ALA titers up to 21.82 g/l in a 5-l bioreactor. Furthermore, recognizing that an imbalance of redox equivalents hindered further titer improvement, we developed a dynamic control system that effectively balances redox status and carbon flux. Ultimately, we collaboratively optimized the artificial redox homeostasis system at the transcription level with other cofactors at the feeding level, demonstrating the highest recorded performance to date with a titer of 63.39 g/l for the biomanufacturing of 5-ALA.

Persistent Gene Flow Suggests an Absence of Reproductive Isolation in an African Antelope Speciation Model.

African antelope diversity is a globally unique vestige of a much richer world-wide Pleistocene megafauna. Despite this, the evolutionary processes leading to the prolific radiation of African antelopes are not well understood. Here, we sequenced 145 whole genomes from both subspecies of the waterbuck (Kobus ellipsiprymnus), an African antelope believed to be in the process of speciation. We investigated genetic structure and population divergence and found evidence of a mid-Pleistocene separation on either side of the eastern Great Rift Valley, consistent with vicariance caused by a rain shadow along the so-called 'Kingdon's Line'. However, we also found pervasive evidence of both recent and widespread historical gene flow across the Rift Valley barrier. By inferring the genome-wide landscape of variation among subspecies, we found 14 genomic regions of elevated differentiation, including a locus that may be related to each subspecies' distinctive coat pigmentation pattern. We investigated these regions as candidate speciation islands. However, we observed no significant reduction in gene flow in these regions, nor any indications of selection against hybrids. Altogether, these results suggest a pattern whereby climatically driven vicariance is the most important process driving the African antelope radiation, and suggest that reproductive isolation may not set in until very late in the divergence process. This has a significant impact on taxonomic inference, as many taxa will be in a gray area of ambiguous systematic status, possibly explaining why it has been hard to achieve consensus regarding the species status of many African antelopes. Our analyses demonstrate how population genetics based on low-depth whole genome sequencing can provide new insights that can help resolve how far lineages have gone along the path to speciation.

The C-terminal self-binding helical peptide of human estrogen-related receptor γ can be druggably targeted by a novel class of rationally designed peptidic antagonists.

Orphan nuclear estrogen-related receptor γ (ERRγ) has been recognized as a potential therapeutic target for cancer, inflammation and metabolic disorder. The ERRγ contains a regulatory AF2 helical tail linked C-terminally to its ligand-binding domain (LBD), which is a self-binding peptide (SBP) and serves as molecular switch to dynamically regulate the receptor alternation between active and inactive states by binding to and unbinding from the AF2-binding site on ERRγ LBD surface, respectively. Traditional ERRγ modulators are all small-molecule chemical ligands that can be classified into agonists and inverse agonists in terms of their action mechanism; the agonists stabilize the AF2 in ABS site with an agonist conformation, while the inverse agonists lock the AF2 out of the site to largely abolish ERRγ transcriptional activity. Here, a class of ERRγ peptidic antagonists was described to compete with native AF2 for the ABS site, thus blocking the active state of AF2 binding to ERRγ LBD domain. Self-inhibitory peptide was derived from the SBP-covering AF2 region and we expected it can rebind potently to the ABS site by reducing its intrinsic disorder and entropy cost upon the rebinding. Hydrocarbon stapling was employed to do so, which employed an all-hydrocarbon bridge across the [i, i + 4]-anchor residue pair in the N-terminal, middle or C-terminal region of the self-inhibitory peptide. As might be expected, it is revealed that the stapled peptides are good binders of ERRγ LBD domain and can effectively compete with the native AF2 helical tail for ERRγ ABS site, which exhibit a basically similar binding mode with AF2 to the site and form diverse noncovalent interactions with the site, thus conferring stability and specificity to the domain-peptide complexes.

Epigenetic regulation in liver regeneration.

The liver is considered unique in its enormous capacity for regeneration and self-repair. In contrast to other regenerative organs (i.e., skin, skeletal muscle, and intestine), whether the adult liver contains a defined department of stem cells is still controversial. In order to compensate for the massive loss of hepatocytes following liver injury, the liver processes a precisely controlled transcriptional reprogram that can trigger cell proliferation and cell-fate switch. Epigenetic events are thought to regulate the organization of chromatin architecture and gene transcription during the liver regenerative process. In this review, we will summarize how changes to the chromatin by epigenetic modifiers are translated into cell fate transitions to restore liver homeostasis during liver regeneration.

High-yield porphyrin production through metabolic engineering and biocatalysis.

Porphyrins and their derivatives find extensive applications in medicine, food, energy and materials. In this study, we produced porphyrin compounds by combining Rhodobacter sphaeroides as an efficient cell factory with enzymatic catalysis. Genome-wide CRISPRi-based screening in R. sphaeroides identifies hemN as a target for improved coproporphyrin III (CPIII) production, and exploiting phosphorylation of PrrA further improves the production of bioactive CPIII to 16.5 g L-1 by fed-batch fermentation. Subsequent screening and engineering high-activity metal chelatases and coproheme decarboxylase results in the synthesis of various metalloporphyrins, including heme and the anti-tumor agent zincphyrin. After pilot-scale fermentation (200 L) and setting up the purification process for CPIII (purity >95%), we scaled up the production of heme and zincphyrin through enzymatic catalysis in a 5-L bioreactor, with CPIII achieving respective enzyme conversion rates of 63% and 98% and yielding 10.8 g L-1 and 21.3 g L-1, respectively. Our strategy offers a solution for high-yield bioproduction of heme and other valuable porphyrins with substantial industrial and medical applications.

Synthetic genomes unveil the effects of synonymous recoding.

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

LexA, an SOS response repressor, activates TGase synthesis in Streptomyces mobaraensis.

Transglutaminase (EC 2.3.2.13, TGase), an enzyme that catalyzes the formation of covalent cross-links between protein or peptide molecules, plays a critical role in commercial food processing, medicine, and textiles. TGase from Streptomyces is the sole commercial enzyme preparation for cross-linking proteins. In this study, we revealed that the SOS response repressor protein LexA in Streptomyces mobaraensis not only triggers morphological development but also enhances TGase synthesis. The absence of lexA significantly diminished TGase production and sporulation. Although LexA does not bind directly to the promoter region of the TGase gene, it indirectly stimulates transcription of the tga gene, which encodes TGase. Furthermore, LexA directly enhances the expression of genes associated with protein synthesis and transcription factors, thus favorably influencing TGase synthesis at both the transcriptional and posttranscriptional levels. Moreover, LexA activates four crucial genes involved in morphological differentiation, promoting spore maturation. Overall, our findings suggest that LexA plays a dual role as a master regulator of the SOS response and a significant contributor to TGase regulation and certain aspects of secondary metabolism, offering insights into the cellular functions of LexA and facilitating the strategic engineering of TGase overproducers.

Score-based generative model-assisted information compensation for high-quality limited-view reconstruction in photoacoustic tomography.

Photoacoustic tomography (PAT) regularly operates in limited-view cases owing to data acquisition limitations. The results using traditional methods in limited-view PAT exhibit distortions and numerous artifacts. Here, a novel limited-view PAT reconstruction strategy that combines model-based iteration with score-based generative model was proposed. By incrementally adding noise to the training samples, prior knowledge can be learned from the complex probability distribution. The acquired prior is then utilized as constraint in model-based iteration. The information of missing views can be gradually compensated by cyclic iteration to achieve high-quality reconstruction. The performance of the proposed method was evaluated with the circular phantom and in vivo experimental data. Experimental results demonstrate the outstanding effectiveness of the proposed method in limited-view cases. Notably, the proposed method exhibits excellent performance in limited-view case of 70° compared with traditional method. It achieves a remarkable improvement of 203% in PSNR and 48% in SSIM for the circular phantom experimental data, and an enhancement of 81% in PSNR and 65% in SSIM for in vivo experimental data, respectively. The proposed method has capability of reconstructing PAT images in extremely limited-view cases, which will further expand the application in clinical scenarios.

Perceptions of social class through Chinese speech cues.

Speech is a complex auditory signal that contains multiple layers of linguistic and non-linguistic structure, it contains both linguistic and social class information. Perceivers are exquisitely sensitive to this layered structure and extract not only linguistic properties, but also indexical characteristics that provide information about individual talkers and groups of talkers. Social class information involves inferring the speaker's social class or forming an impression of their social status based on their speech. Previous research on social class perception in speech has primarily focused on English, with relatively little research on Chinese. This study examines social class perception in Chinese speech. Study 1 employed class judgment and evaluation tasks with a subjective social class scale as the main measure to examine whether listeners could infer class information from Chinese speech and how their own class background influenced their perception. The results of Study 1 showed that subjects could accurately discriminate between speakers' social classes, but there may be a response bias that overestimates lower-class speakers as upper-class speakers. Study 2 focused on whether the speech of different classes of speakers actually differed on a number of indicators. It was found that the speech of higher class speakers was perceived to be more standardised, more pleasant to listen to and less accent-intensive. Overall, listeners can perceive class information from Chinese speech; different classes of Chinese speech do contain different levels of indexical information. In Chinese language societies, individuals can also judge their class information through the speech, which is consistent with the relevant research results in English.

Analysis of admixed Greenlandic siblings shows that the mean genotypic values for metabolic phenotypes differ between Inuit and Europeans.

BACKGROUND: Disease prevalence and mean phenotype values differ between many populations, including Inuit and Europeans. Whether these differences are partly explained by genetic differences or solely due to differences in environmental exposures is still unknown, because estimates of the genetic contribution to these means, which we will here refer to as mean genotypic values, are easily confounded, and because studies across genetically diverse populations are lacking. METHODS: Leveraging the unique genetic properties of the small, admixed and historically isolated Greenlandic population, we estimated the differences in mean genotypic value between Inuit and European genetic ancestry using an admixed sibling design. Analyses were performed across 26 metabolic phenotypes, in 1474 admixed sibling pairs present in a cohort of 5996 Greenlanders. RESULTS: After FDR correction for multiple testing, we found significantly lower mean genotypic values in Inuit genetic ancestry compared to European genetic ancestry for body weight (effect size per percentage of Inuit genetic ancestry (se), -0.51 (0.16) kg/%), body mass index (-0.20 (0.06) kg/m2/%), fat percentage (-0.38 (0.13) %/%), waist circumference (-0.42 (0.16) cm/%), hip circumference (-0.38 (0.11) cm/%) and fasting serum insulin levels (-1.07 (0.51) pmol/l/%). The direction of the effects was consistent with the observed mean phenotype differences between Inuit and European genetic ancestry. No difference in mean genotypic value was observed for height, markers of glucose homeostasis, or circulating lipid levels. CONCLUSIONS: We show that mean genotypic values for some metabolic phenotypes differ between two human populations using a method not easily confounded by possible differences in environmental exposures. Our study illustrates the importance of performing genetic studies in diverse populations.

Efficient biosynthesis of transglutaminase in Streptomyces mobaraensis via systematic engineering strategies.

Transglutaminases (TGases) have been widely used in food, pharmaceutical, biotechnology, and other industries because of their ability to catalyze deamidation, acyl transfer, and crosslinking reactions between Ƴ-carboxamide groups of peptides or protein-bound glutamine and the Ɛ-amino group of lysine. In this study, we demonstrated an efficient systematic engineering strategy to enhance the synthesis of TGase in a recombinant Streptomyces mobaraensis smL2020 strain in a 1000-L fermentor. Briefly, the enzymatic properties of the TGase TGL2020 from S. mobaraensis smL2020 and TGase TGLD from S. mobaraensis smLD were compared to obtain the TGase TGLD with perfected characteristics for heterologous expression in a recombinant S. mobaraensis smL2020ΔTG without the gene tgL 2020. Through multiple engineering strategies, including promoter engineering, optimizing the signal peptides and recombination sites, and increasing copies of the expression cassettes, the final TGLD activity in the recombinant S. mobaraensis smL2020ΔTG: (PL2020-spL2020-protgLD-tgLD)2 (tgL2020and BT1) reached 56.43 U/mL and 63.18 U/mL in shake flask and 1000-L fermentor, respectively, which was the highest reported to date. With the improvement of expression level, the application scope of TGLD in the food industry will continue to expand. Moreover, the genetic stability of the recombinant strain maintained at more than 20 generations. These findings proved the feasibility of multiple systematic engineering strategies in synthetic biology and provided an emerging solution to improve biosynthesis of industrial enzymes.

Unsupervised disentanglement strategy for mitigating artifact in photoacoustic tomography under extremely sparse view.

Traditional methods under sparse view for reconstruction of photoacoustic tomography (PAT) often result in significant artifacts. Here, a novel image to image transformation method based on unsupervised learning artifact disentanglement network (ADN), named PAT-ADN, was proposed to address the issue. This network is equipped with specialized encoders and decoders that are responsible for encoding and decoding the artifacts and content components of unpaired images, respectively. The performance of the proposed PAT-ADN was evaluated using circular phantom data and the animal in vivo experimental data. The results demonstrate that PAT-ADN exhibits excellent performance in effectively removing artifacts. In particular, under extremely sparse view (e.g., 16 projections), structural similarity index and peak signal-to-noise ratio are improved by ∼188 % and ∼85 % in in vivo experimental data using the proposed method compared to traditional reconstruction methods. PAT-ADN improves the imaging performance of PAT, opening up possibilities for its application in multiple domains.