Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning.

Accurately modeling the protein fitness landscapes holds great importance for protein engineering. Pre-trained protein language models have achieved state-of-the-art performance in predicting protein fitness without wet-lab experimental data, but their accuracy and interpretability remain limited. On the other hand, traditional supervised deep learning models require abundant labeled training examples for performance improvements, posing a practical barrier. In this work, we introduce FSFP, a training strategy that can effectively optimize protein language models under extreme data scarcity for fitness prediction. By combining meta-transfer learning, learning to rank, and parameter-efficient fine-tuning, FSFP can significantly boost the performance of various protein language models using merely tens of labeled single-site mutants from the target protein. In silico benchmarks across 87 deep mutational scanning datasets demonstrate FSFP's superiority over both unsupervised and supervised baselines. Furthermore, we successfully apply FSFP to engineer the Phi29 DNA polymerase through wet-lab experiments, achieving a 25% increase in the positive rate. These results underscore the potential of our approach in aiding AI-guided protein engineering.

RiboDiffusion: tertiary structure-based RNA inverse folding with generative diffusion models.

MOTIVATION: RNA design shows growing applications in synthetic biology and therapeutics, driven by the crucial role of RNA in various biological processes. A fundamental challenge is to find functional RNA sequences that satisfy given structural constraints, known as the inverse folding problem. Computational approaches have emerged to address this problem based on secondary structures. However, designing RNA sequences directly from 3D structures is still challenging, due to the scarcity of data, the nonunique structure-sequence mapping, and the flexibility of RNA conformation. RESULTS: In this study, we propose RiboDiffusion, a generative diffusion model for RNA inverse folding that can learn the conditional distribution of RNA sequences given 3D backbone structures. Our model consists of a graph neural network-based structure module and a Transformer-based sequence module, which iteratively transforms random sequences into desired sequences. By tuning the sampling weight, our model allows for a trade-off between sequence recovery and diversity to explore more candidates. We split test sets based on RNA clustering with different cut-offs for sequence or structure similarity. Our model outperforms baselines in sequence recovery, with an average relative improvement of 11% for sequence similarity splits and 16% for structure similarity splits. Moreover, RiboDiffusion performs consistently well across various RNA length categories and RNA types. We also apply in silico folding to validate whether the generated sequences can fold into the given 3D RNA backbones. Our method could be a powerful tool for RNA design that explores the vast sequence space and finds novel solutions to 3D structural constraints. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/ml4bio/RiboDiffusion.

Supplier selection in green supply chain management using correlation-based TOPSIS in a q-rung orthopair fuzzy soft environment.

Fuzzy hybrid models are efficient mathematical tools for managing unclear and vague data in real-world scenarios. This research explores the q-rung orthopair fuzzy soft set (q-ROFSS), which presents incomplete and ambiguous details in decision-making problems. The main intention of this study is to describe and evaluate the characteristics of the correlation coefficient (CC) and weighted correlation coefficient (WCC) for q-ROFSS. Also, the technique for order preference should be enhanced by similarity to the ideal solution (TOPSIS) with extended measures in q-ROFSS settings. Furthermore, we integrated mathematical formulations of correlation obstructions to confirm the consistency of the planned technique. It helps handle difficulties involving multi-attribute group decision-making (MAGDM). Moreover, a numerical illustration is presented to clarify how the advocated decision-making methodology can be implemented in evaluating suppliers in green supply chain management (GSCM). As a result, each alternative is assessed using multiple criteria, such as quality and reliability, capacity and scalability, compliance and certifications, and sustainability practices. The technique proposed in this study retains the selected research's specific structure more effectively than current techniques. A comparative analysis further substantiates the feasibility and effectiveness of the proposed approach over other decision-making techniques.

The MdNAC72-MdABI5 module acts as an interface integrating jasmonic acid and gibberellin signals and undergoes ubiquitination-dependent degradation regulated by MdSINA2 in apple.

Jasmonic acid (JA) and gibberellin (GA) coordinately regulate plant developmental programs and environmental cue responses. However, the fine regulatory network of the cross-interaction between JA and GA remains largely elusive. In this study, we demonstrate that MdNAC72 together with MdABI5 positively regulates anthocyanin biosynthesis through an exquisite MdNAC72-MdABI5-MdbHLH3 transcriptional cascade in apple. MdNAC72 interacts with MdABI5 to promote the transcriptional activation of MdABI5 on its target gene MdbHLH3 and directly activates the transcription of MdABI5. The MdNAC72-MdABI5 module regulates the integration of JA and GA signals in anthocyanin biosynthesis by combining with JA repressor MdJAZ2 and GA repressor MdRGL2a. MdJAZ2 disrupts the MdNAC72-MdABI5 interaction and attenuates the transcriptional activation of MdABI5 by MdNAC72. MdRGL2a sequesters MdJAZ2 from the MdJAZ2-MdNAC72 protein complex, leading to the release of MdNAC72. The E3 ubiquitin ligase MdSINA2 is responsive to JA and GA signals and promotes ubiquitination-dependent degradation of MdNAC72. The MdNAC72-MdABI5 interface fine-regulates the integration of JA and GA signals at the transcriptional and posttranslational levels by combining MdJAZ2, MdRGL2a, and MdSINA2. In summary, our findings elucidate the fine regulatory network connecting JA and GA signals with MdNAC72-MdABI5 as the core in apple.

Six new quassinoids from Picrasma chinese P·Y. Chen and their cytotoxicity activity.

In the present study, six new compounds namely, picralactones CH (1-6) along with nine known compounds (7-15) were isolated from the branches and leaves of Picrasma chinese P.Y. Chen. Their structures were determined with the help of spectroscopic techniques such as NMR, HR-ESI-MS, UV, IR and CD. Cytotoxicity of all compounds was evaluated against MDA-MB-231, SW-620 and HepG2 human cancer cell lines. Compound 4 showed cytotoxic activities.

Left atrial volume index and interleukin-6 as predictors for postoperative atrial fibrillation.

BACKGROUND: Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery. However, the predictive value of single indictor still remains controversial. This study aimed to assess the predictive value of combining preoperative left atrial volume index (LAVI) and postoperative interleukin-6 (IL-6) for POAF in the patients receiving cardiac surgery. METHODS: Patients who admitted to Nanjing First Hospital during the study period between December 2022 and June 2023, and underwent open-heart surgery without a history of atrial fibrillation (AF) were enrolled. The relationships between predictors and POAF were investigated using logistic regression analysis. We determined the combined predictive value of LAVI and IL-6 for POAF by measuring the changes in the area under the receiver operating characteristic curve (AUC) and calculating the net reclassification improvements (NRIs) and integrated discrimination improvement (IDIs). RESULTS: 102 patients were enrolled in this study, and 50 participants developed POAF (49.0%). Patients who experienced POAF had higher levels of preoperative LAVI and postoperative IL-6 than those who did not. Regression analysis revealed that larger LAVI and higher level of IL-6 were independently associated with increased risk of POAF. The combined addition of LAVI and IL-6 to the predictive model resulted in an evident increase in the AUC. Incorporating both LAVI and IL-6 increased IDIs in all models. CONCLUSION: Our results demonstrated that combined LAVI and IL-6 achieved a higher prediction performance for POAF.

[Effects of reductive soil disinfestation and organic fertilizer application on microbial community stability in a facility vegetable soil]. / 强还原处理和施用有机肥对设施蔬菜地土壤微生物群落稳定性的影响.

Reductive soil disinfestation (RSD) is an effective method for remediating degraded facility vegetable soils. However, the effectiveness of RSD using green manure as a carbon source in the field has not yet been clarified. We investigated the effects of RSD and organic fertilizer application on soil microbial community composition, diversity, and stability in a degraded facility vegetable soil. There were six treatments, including no fertilization (CK), no fertilization and soil flooded and mulched with plastic film (FF), soil amended with chicken manure (OM), soil amended with chicken manure and flooded and mulched with plastic film (OMR), soil amended with Sesbania cannabina (TF), and soil amended with S. cannabina and flooded and mulched with plastic film (TR). The results showed that the OMR and TR treatments significantly decreased bacterial Chao1 index, altered bacterial and fungal community structure, and increased the relative abundances of Bacillus, Rhodococcus, Clostridium, and Penicillium. The TR treatment significantly reduced the relative abundance of Fusarium. Results of redundancy analysis and Mantel test analysis suggested that soil ammonium nitrogen and dissolved organic carbon contents were the key factors influencing bacterial community composition, and soil pH was the key factor affecting fungal community composition. Results of cohesion analysis showed that the OMR and TR treatments significantly improved bacterial community stability, and that there was no difference between OMR and TR treatments. The TR treatment enhanced fungal community stability, which was significantly higher than the OMR treatment. Therefore, the RSD with green manure as carbon source could be effective remediation practice to improve soil health.

Temperature dependence of the rain-gas and snow-gas partition coefficients for nearly a thousand chemicals.

Compared to the particle-gas partition coefficients (KPG), the rain-gas (KRG) and snow-gas (KSG) partition coefficients are also essential in studying the environmental behavior and fate of chemicals in the atmosphere. While the temperature dependence for the KPG have been extensively studied, the study for KRG and KSG are still lacking. Adsorption coefficients between water surface-air (KIA) and snow surface-air (KJA), as well as partition coefficients between water-air (KWA) and octanol-air (KOA) are vital in calculating KRG and KSG. These four basic adsorption and partition coefficients are also temperature-dependent, given by the well-known two-parameters Antoine equation logKXY = AXY + BXY/T, where KXY is the adsorption or partition coefficients, AXY and BXY are Antoine parameters (XY stand for IA, JA, WA, and OA), and T is the temperature in Kelvin. In this study, the parameters AXY and BXY are calculated for 943 chemicals, and logKXY can be estimated at any ambient temperature for these chemicals using these Antoine parameters. The results are evaluated by comparing these data with published experimental and modeled data, and the results show reasonable accuracy. Based on these coefficients, temperature-dependence of logKRG and logKSG is studied. It is found that both logKRG and logKSG are linearly related to 1/T, and Antoine parameters for logKRG and logKSG are also estimated. Distributions of the 943 chemicals in the atmospheric phases (gas, particle, and rain/snow), are illustrated in a Chemical Space Map. The findings reveal that, at environmental temperatures and precipitation days, the dominant state for the majority of chemicals is the gaseous phase. All the AXY and BXY values for logKSG, logKRG, and basic adsorption and partition coefficients, both modeled by this study and collected from published work, are systematically organized into an accessible dataset for public utilization.

Visualising cancer in 3D: 3-Dimensional Tissue Imaging for management of cutaneous basal cell carcinoma.

Surgical management of basal cell carcinoma (BCC) typically involves surgical excision with post-operative margin assessment using the bread-loafing technique; or gold-standard Mohs micrographic surgery (MMS), where margins are iteratively examined for residual cancer after tumour removal, with additional excisions performed upon detecting residual tumour at margins. There is limited sampling of resection margins with bread loafing, with detection of positive margins 44% of the time using 2 mm intervals. To resolve this, we have developed three-dimensional (3D) Tissue Imaging for: (1) complete examination of cancer margins and (2) detection of tumour proximity to nerves and blood vessels. 3D Tissue optical clearing with a light sheet imaging protocol was developed for margin assessment in two datasets assessed by two independent evaluators: (1) 48 samples from 29 patients with varied BCC subtypes, sizes and pigmentation levels; (2) 32 samples with matching Mohs' surgeon reading of tumour margins using two-dimensional haematoxylin & eosin-stained sections. The 3D Tissue Imaging protocol permits a complete examination of deeper and peripheral margins. Two independent evaluators achieved negative predictive values of 92.3% and 88.24% with 3D Tissue Imaging. Images obtained from 3D Tissue Imaging recapitulates histological features of BCC, such as nuclear crowding, palisading and retraction clefting and provides a 3D context for recognising normal skin adnexal structures. Concurrent immunofluorescence labelling of nerves and blood vessels allows visualisation of structures closer to tumour-positive regions, which may have a higher risk for neural and vascular infiltration. Together, this method provides more information in a 3D spatial context, enabling better cancer management by clinicians.

Unraveling the Mechanisms of Cannabidiol's Pharmacological Actions: A Comprehensive Research Overview.

Cannabis sativa has long been used for neurological and psychological healing. Recently, cannabidiol (CBD) extracted from cannabis sativa has gained prominence in the medical field due to its non-psychotropic therapeutic effects on the central and peripheral nervous systems. CBD, also acting as a potent antioxidant, displays diverse clinical properties such as anticancer, antiinflammatory, antidepressant, antioxidant, antiemetic, anxiolytic, antiepileptic, and antipsychotic effects. In this review, we summarized the structural activity relationship of CBD with different receptors by both experimental and computational techniques and investigated the mechanism of interaction between related receptors and CBD. The discovery of structural activity relationship between CBD and target receptors would provide a direction to optimize the scaffold of CBD and its derivatives, which would give potential medical applications on CBD-based therapies in various illnesses.

White Matter Microstructure Changes Revealed by Diffusion Kurtosis and Diffusion Tensor Imaging in Mutant Huntingtin Gene Carriers.

Background: Diffusion magnetic resonance imaging (dMRI) has revealed microstructural changes in white matter (WM) in Huntington's disease (HD). Objective: To compare the validities of different dMRI, i.e., diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in HD. Methods: 22 mutant huntingtin (mHTT) carriers and 14 controls were enrolled. Clinical assessments and dMRI were conducted. Based on CAG-Age Product (CAP) score, mHTT carriers were categorized into high CAP (hCAP) and medium and low CAP (m& lCAP) groups. Spearman analyses were used to explore correlations between imaging parameters in brain regions and clinical assessments. Receiver operating characteristic (ROC) was used to distinguish mHTT carriers from control, and define the HD patients at advanced stage. Results: Compared to controls, mHTT carriers exhibited WM changes in DKI and DTI. There were 22 more regions showing significant differences in HD detected by MK than FA. Only MK in five brain regions showed significantly difference between any two group, and negatively correlated with the disease burden (r = -0.80 to -0.71). ROC analysis revealed that MK was more sensitive and FA was more specific, while Youden index showed that the integration of FA and MK gave rise to higher authenticities, in distinguishing m& lCAP from controls (Youden Index = 0.786), and discerning different phase of HD (Youden Index = 0.804). Conclusions: Microstructural changes in WM occur at early stage of HD and deteriorate over the disease progression. Integrating DKI and DTI would provide the best accuracies for differentiating early HD from control and identifying advanced HD.

Insight into saffron associated microbiota from different origins and explore the endophytes for enhancement of bioactive compounds.

Crocus sativus L. is a perennial crop for its valuable active compounds. Plant-associated microbes impact on the quality and efficacy of medicinal herbs by promoting bioactive components accumulation. However, how microbes influence the accumulation of bioactive components in saffron have not been well studied. Here, the microbiome in C. sativus derived from 3 core production areas were deciphered by 16S rDNA sequencing and the relationship between endophytes and bioactive ingredients were further investigated. The main results are as follows: (1) Both Comamonadaceae and Burkholderiaceae were positively correlated with the content of bioactive components in the stigmas. (2) The synthesis of crocin was positively correlated with Xanthomonadaceae, negatively correlated with Lachnospiraceae and Prevotellaceae. Therefore, further investigation is required to determine whether Xanthomonadaceae plays an unknown function in the synthesis of crocin. These findings provide guidelines for disentangling the function of endophytes in the production of bioactive ingredients and thus for microbe-mediated breeding.

The potential of RNA therapeutics in dermatology.

Ribonucleic acid (RNA) therapeutics hold great potential for the advancement of dermatological treatments due to, among other reasons, the possibility of treating previously undruggable targets, high specificity with minimal side effects, and ability to include multiple RNA targets in a single product. Although there have been research relating to RNA therapeutics for decades, there have not been many products translated for clinical use until recently. This may be because of challenges to the application of RNA therapeutics, including the dearth of effective modes of delivery to the target, and rapid degradation of RNA in the human body and environment. This article aims to provide insight on (1) the wide-ranging possibilities of RNA therapeutics in the field of dermatology as well as (2) how key challenges can be addressed, so as to encourage the development of novel dermatological treatments. We also share our experience on how RNA therapeutics have been applied in the management of hypertrophic and keloid scars.

PCSK9 Inhibitor Added to High-Intensity Statin Therapy to Prevent Cardiovascular Events in Patients with Acute Coronary Syndrome after Percutaneous Coronary Intervention: A Randomized, Double- Blind, Placebo-Controlled, Multicenter SHAWN Study.

BACKGROUND: It is currently uncertain whether the combination of a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor and high-intensity statin treatment can effectively reduce cardiovascular events in patients with acute coronary syndrome (ACS) who have undergone percutaneous coronary intervention (PCI) for culprit lesions. METHODS: This study protocol describes a double-blind, randomized, placebo-controlled, multicenter study aiming to investigate the efficacy and safety of combining a PCSK9 inhibitor with high-intensity statin therapy in patients with ACS following PCI. A total of 1212 patients with ACS and multiple lesions will be enrolled and randomly assigned to receive either PCSK9 inhibitor plus high-intensity statin therapy or high-intensity statin monotherapy. The randomization process will be stratified by sites, diabetes, initial presentation and use of stable (≥4 weeks) statin treatment at presentation. PCSK 9 inhibitor or its placebo is injected within 4 hours after PCI for the culprit lesion. The primary endpoint is the composite of cardiovascular death, myocardial infarction, stroke, re-hospitalization due to ACS or heart failure, or any ischemia-driven coronary revascularization at one-year follow-up between two groups. Safety endpoints mean PCSK 9 inhibitor and statin intolerance. CONCLUSION: The SHAWN study has been specifically designed to evaluate the effectiveness and safety of adding a PCSK9 inhibitor to high-intensity statin therapy in patients who have experienced ACS following PCI. The primary objective of this study is to generate new evidence regarding the potential benefits of combining a PCSK9 inhibitor with high-intensity statin treatment in reducing cardiovascular events among these patients.

Smurf1-targeting microRNA-136-5p-modified bone marrow mesenchymal stem cells combined with 3D-printed ß-tricalcium phosphate scaffolds strengthen osteogenic activity and alleviate bone defects.

Suitable biomaterials with seed cells have promising potential to repair bone defects. However, bone marrow mesenchymal stem cells (BMSCs), one of the most common seed cells used in tissue engineering, cannot differentiate efficiently and accurately into functional osteoblasts. In view of this, a new tissue engineering technique combined with BMSCs and scaffolds is a major task for bone defect repair. Lentiviruses interfering with miR-136-5p or Smurf1 expression were transfected into BMSCs. The effects of miR-136-5p or Smurf1 on the osteogenic differentiation (OD) of BMSCs were evaluated by measuring alkaline phosphatase activity and calcium deposition. Then, the targeting relationship between miR-136-5p and Smurf1 was verified by bioinformatics website analysis and dual luciferase reporter assay. Then, a rabbit femoral condyle bone defect model was established. miR-136-5p/BMSCs/ß-TCP scaffold was implanted into the defect, and the repair of the bone defect was detected by Micro-CT and HE staining. Elevating miR-136-5p-3p or suppressing Smurf1 could stimulate OD of BMSCs. miR-136-5p negatively regulated Smurf1 expression. Overexpressing Smurf1 reduced the promoting effect of miR-136-5p on the OD of BMSCs. miR-136-5p/BMSCs/ß-TCP could strengthen bone density in the defected area and accelerate bone repair. SmurF1-targeting miR-136-5p-modified BMSCs combined with 3D-printed ß-TCP scaffolds can strengthen osteogenic activity and alleviate bone defects.

Mechanism Analysis of Antimicrobial Peptide NoPv1 Related to Potato Late Blight through a Computer-Aided Study.

Phytophthora infestans (Mont.) de Bary, the oomycotic pathogen responsible for potato late blight, is the most devastating disease of potato production. The primary pesticides used to control oomycosis are phenyl amide fungicides, which cause environmental pollution and toxic residues harmful to both human and animal health. To address this, an antimicrobial peptide, NoPv1, has been screened to target Plasmopara viticola cellulose synthase 2 (PvCesA2) to inhibit the growth of Phytophthora infestans (P. infestans). In this study, we employed AlphaFold2 to predict the three-dimensional structure of PvCesA2 along with NoPv peptides. Subsequently, utilizing computational methods, we dissected the interaction mechanism between PvCesA2 and these peptides. Based on this analysis, we performed a saturation mutation of NoPv1 and successfully obtained the double mutants DP1 and DP2 with a higher affinity for PvCesA2. Meanwhile, dynamics simulations revealed that both DP1 and DP2 utilize a mechanism akin to the barrel-stave model for penetrating the cell membrane. Furthermore, the predicted results showed that the antimicrobial activity of DP1 was superior to that of NoPv1 without being toxic to human cells. These findings may offer insights for advancing the development of eco-friendly pesticides targeting various oomycete diseases, including late blight.

Analysis of risk characteristics for early progression and late progression in locally advanced rectal cancer patients: a large population-based and validated study.

BACKGROUND AND OBJECTIVE: The current study aimed to explore the factors influencing early progression (EP) and late progression (LP) in locally advanced rectal cancer (LARC) patients. METHODS: The patients were classified into EP and LP groups using one year as a cutoff. The random survival forest model was utilized to calculate the probability of time-to-progression. Besides, inverse probability of treatment weighting (IPTW) analysis and the Surveillance, Epidemiology, and End Results (SEER) were conducted to validate our results. RESULTS: Our study revealed that PNI, CEA level, and pathological stage were independent prognostic factors for PFS both in EP group and LP group. For EP group patients, Group 1 had the highest probability of progression at the 9th month of follow-up, while Group 2 exhibited the highest probability at the 6th month. Group 3, on the other hand, showed two peaks of progression at the 4th and 8th months of follow-up. As for LP group patients, Groups 4, 5, and 6 all exhibited peaks of progression between the 18th and 24th months of follow-up. Furthermore, our results suggested that PNI was also an independent prognostic factor affecting OS in both EP group and LP group. Finally, the analysis of IPTW and SEER database further confirmed our findings. CONCLUSIONS: Our results indicated a significant correlation between immune and nutritional status with PFS and OS in both EP and LP groups. These insights can aid healthcare professionals in effectively identifying and evaluating patients' nutritional status, enabling them to develop tailored nutrition plans and interventions.

Overexpression of GPX2 gene regulates the development of porcine preadipocytes and skeletal muscle cells through MAPK signaling pathway.

Glutathione peroxidase 2 (GPX2) is a selenium-dependent enzyme and protects cells against oxidative damage. Recently, GPX2 has been identified as a candidate gene for backfat and feed efficiency in pigs. However, it is unclear whether GPX2 regulates the development of porcine preadipocytes and skeletal muscle cells. In this study, adenoviral gene transfer was used to overexpress GPX2. Our findings suggest that overexpression of GPX2 gene inhibited proliferation of porcine preadipocytes. And the process is accompanied by the reduction of the p-p38. GPX2 inhibited adipogenic differentiation and promoted lipid degradation, while ERK1/2 was reduced and p-p38 was increased. Proliferation of porcine skeletal muscle cells was induced after GPX2 overexpression, was accompanied by activation in JNK, ERK1/2, and p-p38. Overexpression methods confirmed that GPX2 has a promoting function in myoblastic differentiation. ERK1/2 pathway was activated and p38 was suppressed during the process. This study lays a foundation for the functional study of GPX2 and provides theoretical support for promoting subcutaneous fat reduction and muscle growth.