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The turnover number k cat , a measure of enzyme efficiency, is central to understanding cellular physiology and resource allocation. As experimental k cat estimates are unavailable for the vast majority of enzymatic reactions, the development of accurate computational prediction methods is highly desirable. However, existing machine learning models are limited to a single, well-studied organism, or they provide inaccurate predictions except for enzymes that are highly similar to proteins in the training set. Here, we present TurNuP, a general and organism-independent model that successfully predicts turnover numbers for natural reactions of wild-type enzymes. We constructed model inputs by representing complete chemical reactions through differential reaction fingerprints and by representing enzymes through a modified and re-trained Transformer Network model for protein sequences. TurNuP outperforms previous models and generalizes well even to enzymes that are not similar to proteins in the training set. Parameterizing metabolic models with TurNuP-predicted k cat values leads to improved proteome allocation predictions. To provide a powerful and convenient tool for the study of molecular biochemistry and physiology, we implemented a TurNuP web server. The turnover numbers of most enzyme-catalyzed reactions are unknown. Kroll et al. developed a general model that can predict turnover numbers even for enzymes dissimilar to those used for training, outperforming existing models.

The improvement of GTFP has become an important guarantee to change China’s development mode and achieve long-term stable economic growth, while the development of AI is of great significance to the development of GTFP. This paper adopts the SBM-GML method to calculate the GTFP of 30 regions in China from 2011 to 2020, and manually collects AI data to study the impact of AI on GTFP, and systematically analyze the relationship between AI and GTFP using a panel double-fixed model with a faceted threshold model. The experimental results show that: (1) There is a positive and significant effect of AI on GTFP, which increases GTFP productivity by 0.3654% for every 1% increase in AI, which still holds after a robust type test. (2) The development of AI in China’s eastern region has a greater promoting effect on GTFP. (3) Further mechanism analysis reveals that RIS and ER are two important channels through which AI influences the improvement of GTFP. (4) Threshold regression shows that AI has a single threshold effect on GTFP based on TI and LNPGDP. The promotion of GTFP by AI is higher when technological innovation is less than the threshold value of 29.95, and the promotion of GTFP by AI is insignificant when the level of economic development is less than the threshold value of 85.45. This paper deepens the knowledge and understanding of the role played in the development of AI at the macro level and provides suggestions for improving GTFP at the provincial level in China.

Protein synthesis is the most expensive process in fast-growing bacteria. Experimentally observed growth rate dependencies of the translation machinery form the basis of powerful phenomenological growth laws; however, a quantitative theory on the basis of biochemical and biophysical constraints is lacking. Here, we show that the growth rate-dependence of the concentrations of ribosomes, tRNAs, mRNA, and elongation factors observed in Escherichia coli can be predicted accurately from a minimization of cellular costs in a mechanistic model of protein translation. The model is constrained only by the physicochemical properties of the molecules and has no adjustable parameters. The costs of individual components (made of protein and RNA parts) can be approximated through molecular masses, which correlate strongly with alternative cost measures such as the molecules’ carbon content or the requirement of energy or enzymes for their biosynthesis. Analogous cost minimization approaches may facilitate similar quantitative insights also for other cellular subsystems. The protein translation machinery is the most expensive cellular subsystem in fast growing bacteria. Providing a detailed mechanistic model for this complex system, the authors show that the translation machinery components are expressed such that their combined cost to the cell is minimal.

Two series of binary graft cationic starch-based flocculants (CS-DMCs and CS-DMLs) with different hydrophilicity and charge density (CD) were prepared by graft copolymerization of acrylamide with 2-(Methacryloyloxy)- N , N , N -trimethylethanaminium chloride and methacrylic acid 2-(benzyldimethylaminio) ethyl chloride, respectively, on the starch (St) backbone. The sludge dewatering performance of CS-DMCs and CS-DMLs were evaluated and compared based on the changes in filter cake moisture content (FCMC), specific resistance of filtration (SRF), fractions and components of extracellular polymeric substances, and various physiochemical characteristics of sludge flocs and cakes. Increase in CD of the St-based flocculants caused improved sludge dewaterability. Under the similar CD, CS-DML with relatively high hydrophobicity exhibited lower FCMC and SRF, larger and denser sludge flocs, and better permeability of sludge cakes than CS-DMCs due to the synergistic effects of charge neutralization, bridging flocculation and hydrophobic association. Furthermore, a second-order polynomial model on the basis of phenomenological theory was successfully applied to quantitatively evaluate the influences of the two important structural factors of these St-based flocculants, i.e., hydrophobicity and CD, on the sludge dewaterability. The structure–activity relationship of the St-based flocculants in sludge dewatering was obtained according to the theoretic simulation. The dewatering mechanisms was discussed in depth on the basis of the experimental and simulated results; besides, the FCMC and optimal dose can be predicted by the established structure–activity relationship. This current work offered a novel and valuable way to exploit and design of low-cost and high-performance graft natural polymeric flocculants applied in efficient conditioning of sludge.

Purpose To review and summarize the clinical features, diagnosis, treatment strategies, and prognosis of spinal Rosai-Dorfman disease (RDD). Methods RDD is also termed as sinus histiocytosis with massive lymphadenopathy. We searched the databases of PubMed, Elsevier ScienceDirect, SpringerLink, and OVID. The keywords were Rosai-Dorfman disease and spine/central nervous system . Research articles and case reports with accessibility to full texts regarding spinal RDD were eligible for the inclusion. A total of 62 articles were included, and they contained 69 cases. We extracted the information of interest and analyzed them using SPSS statistics package. Results The average age was 33.1 ± 18.3 years. The ratio of males to females was 1.9/1. Overall, 63 cases presented with spine-related symptoms. A total of 27 cases (39.1%) had multi-organ lesions, and 12 cases had records of massive lymphadenopathy. Among 47 cases who first manifested spine-related symptoms, 93.6% were preoperatively misdiagnosed. The disease had a predilection for cervical spine (38.8%) and thoracic spine (40.3%). 62.9% of lesions were dura-based. Surgery remained the mainstream treatment option (78.8%), with or without adjuvant therapies. Total lesion resection was achieved in 34.8% of cases. The rate of lesion recurrence/progression was 19.5%, which was marginally lower for total resection than for non-total resection. Conclusion Spinal RDD has no pathognomonic clinical and imaging features. Most cases first present with spine-relevant symptoms. Massive lymphadenopathy is not common, but a tendency for multi-organ involvement should be considered. Spinal RDD has a high recurrence rate; thus, total resection is the treatment of choice. Adjuvant therapies are indicated for multi-organ lesions and residual lesions. A wait and watch strategy is recommended for asymptomatic patients. Herein, a workflow of diagnosis and treatment of the spinal RDD is established.

Low NOx staged combustion technology generates large amounts of CO gas in the primary combustion zone of the boiler, thereby exacerbating high-temperature corrosion in the boiler waterwall. Applying near-wall air (NWA) technology has proven to be an effective strategy for mitigating the reducing atmosphere near the waterwall. This study presents experimental configurations of NWA co-combustion adjustments conducted on a 650 MWe swirl-opposed boiler. The research investigates the impact of the flow rate of the outer secondary air of the burner and the flow rate of overfire air (OFA) on CO concentration near the sidewall. Results indicate that increasing the opening of the outer secondary air near the sidewall and reducing the opening of the OFA effectively reduced CO concentration.

The distribution of cellular resources across bacterial proteins has been quantified through phenomenological growth laws. Here, we describe a complementary bacterial growth law for RNA composition, emerging from optimal cellular resource allocation into ribosomes and ternary complexes. The predicted decline of the tRNA/rRNA ratio with growth rate agrees quantitatively with experimental data. Its regulation appears to be implemented in part through chromosomal localization, as rRNA genes are typically closer to the origin of replication than tRNA genes and thus have increasingly higher gene dosage at faster growth. At the highest growth rates in E . coli , the tRNA/rRNA gene dosage ratio based on chromosomal positions is almost identical to the observed and theoretically optimal tRNA/rRNA expression ratio, indicating that the chromosomal arrangement has evolved to favor maximal transcription of both types of genes at this condition.

Endometriosis is a common chronic inflammatory and estrogen-dependent disease that mostly affects people of childbearing age. The dietary inflammatory index (DII) is a novel instrument for assessing the overall inflammatory potential of diet. However, no studies have shown the relationship between DII and endometriosis to date. This study aimed to elucidate the relationship between DII and endometriosis. Data were acquired from the National Health and Nutrition Examination Survey (NHANES) 2001–2006. DII was calculated using an inbuilt function in the R package. Relevant patient information was obtained through a questionnaire containing their gynecological history. Based on an endometriosis questionnaire survey, those participants who answered yes were considered cases (with endometriosis), and participants who answered no were considered as controls (without endometriosis) group. Multivariate weighted logistic regression was applied to examine the correlation between DII and endometriosis. Subgroup analysis and smoothing curve between DII and endometriosis were conducted in a further investigation. Compared to the control group, patients were prone to having a higher DII (P = 0.014). Adjusted multivariate regression models showed that DII was positively correlated with the incidence of endometriosis (P < 0.05). Analysis of subgroups revealed no significant heterogeneity. In middle-aged and older women (age ≥ 35 years), the smoothing curve fitting analysis results demonstrated a non-linear relationship between DII and the prevalence of endometriosis. Therefore, using DII as an indicator of dietary-related inflammation may help to provide new insight into the role of diet in the prevention and management of endometriosis.

Coagulation/flocculation is one of the most widely used and cost-effective pretreatment methods for improving the dewaterability of sludge. In this study, a cationic modified starch-based flocculant (St-CTA) in conjunction with a popular clay, attapulgite (ATP), was used for the conditioning of waste-activated sludge. The dewatering properties, including the filter cake moisture content, filtration specific resistance, capillary suction time, filtration rate and compressibility coefficient, were measured and compared by varying the doses of St-CTA and ATP. By combination of the apparent dewatering performance and the changes in the contents and distributions of the extracellular polymeric substance (EPS) fractions and components, sludge flocs, and microstructures of sludge cakes, the dewatering mechanisms were discussed in detail. St-CTA in conjunction with ATP can exhibit an enhanced dewaterability of sludge and the water content in final sludge cake can be stably reduced below 80% owing to the synergistic effects of St-CTA and ATP. In addition to the efficient charge neutralization of St-CTA, ATP not only acts as a skeleton builder in the sludge dewatering process which makes the sludge flocs more compact and improves the filterability and permeability, but also tightly interacts with the proteins in EPS of the sludge which reduces the protein content and further enhances the dewatering effect. This study provides an economical, green, and effective way to further improve the dewaterability of sludge.