First-in-class MKK4 inhibitors enhance liver regeneration and prevent liver failure.

Diminished hepatocyte regeneration is a key feature of acute and chronic liver diseases and after extended liver resections, resulting in the inability to maintain or restore a sufficient functional liver mass. Therapies to restore hepatocyte regeneration are lacking, making liver transplantation the only curative option for end-stage liver disease. Here, we report on the structure-based development and characterization (nuclear magnetic resonance [NMR] spectroscopy) of first-in-class small molecule inhibitors of the dual-specificity kinase MKK4 (MKK4i). MKK4i increased liver regeneration upon hepatectomy in murine and porcine models, allowed for survival of pigs in a lethal 85% hepatectomy model, and showed antisteatotic and antifibrotic effects in liver disease mouse models. A first-in-human phase I trial (European Union Drug Regulating Authorities Clinical Trials [EudraCT] 2021-000193-28) with the clinical candidate HRX215 was conducted and revealed excellent safety and pharmacokinetics. Clinical trials to probe HRX215 for prevention/treatment of liver failure after extensive oncological liver resections or after transplantation of small grafts are warranted.

Orchestrating information across tissues via a novel multitask GAT framework to improve quantitative gene regulation relation modeling for survival analysis.

Survival analysis is critical to cancer prognosis estimation. High-throughput technologies facilitate the increase in the dimension of genic features, but the number of clinical samples in cohorts is relatively small due to various reasons, including difficulties in participant recruitment and high data-generation costs. Transcriptome is one of the most abundantly available OMIC (referring to the high-throughput data, including genomic, transcriptomic, proteomic and epigenomic) data types. This study introduced a multitask graph attention network (GAT) framework DQSurv for the survival analysis task. We first used a large dataset of healthy tissue samples to pretrain the GAT-based HealthModel for the quantitative measurement of the gene regulatory relations. The multitask survival analysis framework DQSurv used the idea of transfer learning to initiate the GAT model with the pretrained HealthModel and further fine-tuned this model using two tasks i.e. the main task of survival analysis and the auxiliary task of gene expression prediction. This refined GAT was denoted as DiseaseModel. We fused the original transcriptomic features with the difference vector between the latent features encoded by the HealthModel and DiseaseModel for the final task of survival analysis. The proposed DQSurv model stably outperformed the existing models for the survival analysis of 10 benchmark cancer types and an independent dataset. The ablation study also supported the necessity of the main modules. We released the codes and the pretrained HealthModel to facilitate the feature encodings and survival analysis of transcriptome-based future studies, especially on small datasets. The model and the code are available at http://www.healthinformaticslab.org/supp/.

MolFeSCue: enhancing molecular property prediction in data-limited and imbalanced contexts using few-shot and contrastive learning.

MOTIVATION: Predicting molecular properties is a pivotal task in various scientific domains, including drug discovery, material science, and computational chemistry. This problem is often hindered by the lack of annotated data and imbalanced class distributions, which pose significant challenges in developing accurate and robust predictive models. RESULTS: This study tackles these issues by employing pretrained molecular models within a few-shot learning framework. A novel dynamic contrastive loss function is utilized to further improve model performance in the situation of class imbalance. The proposed MolFeSCue framework not only facilitates rapid generalization from minimal samples, but also employs a contrastive loss function to extract meaningful molecular representations from imbalanced datasets. Extensive evaluations and comparisons of MolFeSCue and state-of-the-art algorithms have been conducted on multiple benchmark datasets, and the experimental data demonstrate our algorithm's effectiveness in molecular representations and its broad applicability across various pretrained models. Our findings underscore MolFeSCues potential to accelerate advancements in drug discovery. AVAILABILITY AND IMPLEMENTATION: We have made all the source code utilized in this study publicly accessible via GitHub at http://www.healthinformaticslab.org/supp/ or https://github.com/zhangruochi/MolFeSCue. The code (MolFeSCue-v1-00) is also available as the supplementary file of this paper.

Phase-Tunable Molybdenum Boride Ceramics as an Emerging Sensitive and Reliable SERS Platform in Harsh Environments.

Traditional surface-enhanced Raman scattering (SERS) sensors rely heavily on the use of plasmonic noble metals, which have limitations due to their high cost and lack of physical and chemical stability. Hence, it is imperative to explore new materials as SERS platforms that can withstand high temperatures and harsh conditions. In this study, the SERS effect of molybdenum boride ceramic powders is presented with an enhancement factor of 5 orders, which is comparable to conventional noble metal substrates. The molybdenum boride powders synthesized through liquid-phase precursor and carbothermal reduction have ß-MoB, MoB2 , and Mo2 B5 phases. Among these phases, ß-MoB demonstrates the most significant SERS activity, with a detection limit for rhodamine 6G (R6G) molecules of 10-9  m. The impressive SERS enhancement can be attributed to strong molecule interactions and prominent charge interactions between R6G and the various phases of molybdenum boride, as supported by theoretical calculations. Additionally, Raman measurements show that the SERS activity remains intact after exposure to high temperature, strong acids, and alkalis. This research introduces a novel molybdenum boride all-ceramic SERS platform capable of functioning in harsh conditions, thereby showing the promising of boride ultrahigh-temperature ceramics for detection applications in extreme environments.

HLAB: learning the BiLSTM features from the ProtBert-encoded proteins for the class I HLA-peptide binding prediction.

Human Leukocyte Antigen (HLA) is a type of molecule residing on the surfaces of most human cells and exerts an essential role in the immune system responding to the invasive items. The T cell antigen receptors may recognize the HLA-peptide complexes on the surfaces of cancer cells and destroy these cancer cells through toxic T lymphocytes. The computational determination of HLA-binding peptides will facilitate the rapid development of cancer immunotherapies. This study hypothesized that the natural language processing-encoded peptide features may be further enriched by another deep neural network. The hypothesis was tested with the Bi-directional Long Short-Term Memory-extracted features from the pretrained Protein Bidirectional Encoder Representations from Transformers-encoded features of the class I HLA (HLA-I)-binding peptides. The experimental data showed that our proposed HLAB feature engineering algorithm outperformed the existing ones in detecting the HLA-I-binding peptides. The extensive evaluation data show that the proposed HLAB algorithm outperforms all the seven existing studies on predicting the peptides binding to the HLA-A*01:01 allele in AUC and achieves the best average AUC values on the six out of the seven k-mers (k=8,9,...,14, respectively represent the prediction task of a polypeptide consisting of k amino acids) except for the 9-mer prediction tasks. The source code and the fine-tuned feature extraction models are available at http://www.healthinformaticslab.org/supp/resources.php.

GANSamples-ac4C: Enhancing ac4C site prediction via generative adversarial networks and transfer learning.

RNA modification, N4-acetylcytidine (ac4C), is enzymatically catalyzed by N-acetyltransferase 10 (NAT10) and plays an essential role across tRNA, rRNA, and mRNA. It influences various cellular functions, including mRNA stability and rRNA biosynthesis. Wet-lab detection of ac4C modification sites is highly resource-intensive and costly. Therefore, various machine learning and deep learning techniques have been employed for computational detection of ac4C modification sites. The known ac4C modification sites are limited for training an accurate and stable prediction model. This study introduces GANSamples-ac4C, a novel framework that synergizes transfer learning and generative adversarial network (GAN) to generate synthetic RNA sequences to train a better ac4C modification site prediction model. Comparative analysis reveals that GANSamples-ac4C outperforms existing state-of-the-art methods in identifying ac4C sites. Moreover, our result underscores the potential of synthetic data in mitigating the issue of data scarcity for biological sequence prediction tasks. Another major advantage of GANSamples-ac4C is its interpretable decision logic. Multi-faceted interpretability analyses detect key regions in the ac4C sequences influencing the discriminating decision between positive and negative samples, a pronounced enrichment of G in this region, and ac4C-associated motifs. These findings may offer novel insights for ac4C research. The GANSamples-ac4C framework and its source code are publicly accessible at http://www.healthinformaticslab.org/supp/.

Proteomics identifies hypothermia induced adiponectin protects corneal endothelial cells via AMPK mediated autophagy in phacoemulsification.

AIM: To explore the molecular mechanism underlying the protective effect of hypothermic perfusion on the corneal endothelium during phacoemulsification. METHODS: Phacoemulsification was performed on New Zealand white rabbits. Perfusate at different temperatures was used during the operation, and the aqueous humor was collected for proteomic sequencing after the operation. Corneal endothelial cell injury was simulated by a corneal endothelial cell oxygen-glucose deprivation/reoxygenation (OGD/R) model in vitro. Flow cytometry and evaluation of fluorescent LC3B puncta were used to detect apoptosis and autophagy, and western blotting was used to detect protein expression. RESULTS: A total of 381 differentially expressed proteins were identified between the two groups. In vitro, 4 ℃ hypothermia significantly reduced apoptosis and promoted autophagy. Apoptosis increased after autophagy was inhibited by 3-Methyladenine (3-MA). Furthermore, adiponectin (ADIPOQ) knockdown inhibited phospho-AMPK and blocked the protective effect of hypothermia on corneal endothelial cells. CONCLUSIONS: We investigated the differential expression of proteins between the hypothermia group and normothermia group by proteomics. Moreover, hypothermia-induced ADIPOQ can reduce apoptosis by promoting AMPK-mediated autophagy.

Mapping global prevalence of menopausal symptoms among middle-aged women: a systematic review and meta-analysis.

BACKGROUND: Women at middle age are puzzled by a series of menopausal disturbances, can be distressing and considerably affect the personal, social and work lives. We aim to estimate the global prevalence of nineteen menopausal symptoms among middle-aged women by performing a systematic review and meta-analysis. METHODS: Comprehensive search was performed in multiple databases from January, 2000 to March, 2023 for relevant studies. Random-effect model with double-arcsine transformation was used for data analysis. RESULTS: A total of 321 studies comprised of 482,067 middle-aged women were included for further analysis. We found varied prevalence of menopausal symptoms, with the highest prevalence of joint and muscular discomfort (65.43%, 95% CI 62.51-68.29) and lowest of formication (20.5%, 95% CI 13.44-28.60). Notably, South America shared dramatically high prevalence in a sort of menopausal symptoms including depression and urogenital symptoms. Besides, countries with high incomes (49.72%) had a significantly lower prevalence of hot flashes than those with low (65.93%), lower-middle (54.17%), and upper-middle (54.72%, p < 0.01), while personal factors, such as menopausal stage, had an influence on most menopausal symptoms, particularly in vaginal dryness. Prevalence of vagina dryness in postmenopausal women (44.81%) was 2-fold higher than in premenopausal women (21.16%, p < 0.01). Furthermore, a remarkable distinction was observed between body mass index (BMI) and prevalence of sleep problems, depression, anxiety and urinary problems. CONCLUSION: The prevalence of menopausal symptoms affected by both social and personal factors which calls for attention from general public.

Different biomarker ratios in peripheral blood have limited value in diagnosing periprosthetic joint infection after total joint arthroplasty: a single-center, retrospective study.

BACKGROUND: Periprosthetic joint infection (PJI) is a severe complication that can occur after total joint arthroplasty (TJA). The timely and accurate diagnosis of PJI is the key to treatment. This study investigated the diagnostic value of platelet to lymphocyte ratio (PLR), platelet count to mean platelet volume ratio (PVR), neutrophil to lymphocyte ratio (NLR) and monocyte to lymphocyte ratio (MLR) in PJI after total knee arthroplasty (TKA) and total hip arthroplasty (THA). METHODS: We performed a retrospective analysis of the patients who underwent revision hip or knee arthroplasty at our Institute between June 2015 and June 2020. Of the 187 patients reviewed, 168 were included in the study. According to the diagnostic criteria of the Musculoskeletal Infection Society (MSIS), 58 patients were in the PJI group, and 110 patients were in the aseptic loosening (AL) group. We recorded and compared the preoperative peripheral blood white blood cell (WBC) count, platelet count (PLT), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), PLR, PVR, NLR, and MLR in both groups. The diagnostic performance of the WBC, PLT, PLR, PVR, NLR, and MLR individually and in combination with the ESR and CRP for PJI diagnosis was evaluated by receiver operating characteristic (ROC) curves, and the sensitivity, specificity, positive predictive value, and negative predictive value were calculated. RESULTS: Compared to those in the AL group, the mean WBC, PLT, ESR, CRP, PLR, PVR, NLR, and MLR in the peripheral blood of the PJI group were significantly greater (P < 0.05). The analysis of the ROC curve revealed that the ESR, CRP, PLR, PVR, NLR, and MLR in peripheral blood had moderate effectiveness in diagnosing PJI, with area under the curve (AUC) values of 0.760 (95% CI: 0.688-0.823), 0.758 (95% CI: 0.687-0.821), 0.714 (95% CI: 0.639-0.781), 0.709 (95% CI: 0.634-0.777), 0.723 (95% CI: 0.649-0.789), and 0.728 (95% CI: 0.654-0.793), respectively. Conversely, the WBC and PLT counts demonstrated poor diagnostic value for PJI, with AUC values of 0.578 (95% CI: 0.499-0.653) and 0.694 (95% CI: 0.619-0.763), respectively. The results of the prediction model calculations revealed that the combined AUC of the WBC, PLT, ESR, CRP, PLR, PVR, NLR, and MLR was the highest at 0.853 (95% CI, 0.790-0.909), indicating good value in the diagnosis of PJI, with a sensitivity of 82.8% and a specificity of 72.7%. Moreover, the novel composite of parameters improved the accuracy and reliability in diagnosing PJI compared to the traditional biomarkers ESR and CRP (P = 0.015). CONCLUSION: Our study suggested that the diagnostic value of the peripheral blood biomarkers PLR, PVR, NLR, and MLR for diagnosing PJI is limited and not superior to that of the ESR or CRP. However, when the WBC, PLT, ESR, CRP, PLR, PVR, NLR, and MLR are combined, the diagnostic performance of PJI in TJA patients can be improved.

Rapid assessment of soil accessible Cr(â ¥) in the field by a portable RGB color sensor.

Field rapid determination of soil accessible Cr(Ⅵ) is of great significance for on-site assessment and decision-making about the health risks of contaminated sites. When the thickness of solutions with various concentrations of Cr(Ⅵ) is constant, there would be a quantitative relationship between the chromogenic difference of Cr(Ⅵ) solutions and the concentration of Cr(Ⅵ). The chromogenic difference could be described by Red (R), Green (G), Blue (B) values. Based on the chromogenic reaction between 1,5-diphenylcarbazide and Cr(Ⅵ), this study first established the calibration curve between the chromogenic difference and the concentration of Cr(Ⅵ) in standard solution with or without 0.01 M CaCl2, using an RGB color sensor. This is the subsequent determination basis of the method for rapidly assessing accessible Cr(Ⅵ) in the field (M-RGB). Then, the concentration of accessible Cr(Ⅵ) of contaminated soil with "hand-shaking + standing" field extraction method was compared with "end-over-end shaking" laboratory extraction method. Finally, the accessible Cr(Ⅵ) of contaminated soil extractants was determined via M-RGB integrating the field extraction method. Results indicated there was a highly significant linear relationship between colorimetric difference value (∆E) and Cr(Ⅵ) concentration in the range of 0.1-3 mg/L (R2 > 0.99, P < 0.01), based on the Euclidean formula for calculating ∆E. The "hand-shaking + standing" field extraction method was effective in obtaining accessible Cr(Ⅵ) extractants with or without 0.01 M CaCl2, with the high extraction efficiency within 100±1%. The concentrations of accessible Cr(Ⅵ) in various polluted soils determined by M-RGB were consistent with that determined by the ultraviolet-visible spectrophotometry, with the relative error within ±5%, and the relative standard deviation ≤ 20%. The spiked recovery experiments showed that the recovery of M-RGB was between 95% and 105%, which means M-RGB could realize the trace analysis for accessible Cr(Ⅵ) in the field.

Transport Behavior of Cd2+ in Highly Weathered Acidic Soils and Shaping in Soil Microbial Community Structure.

The mining and smelting site soils in South China present excessive Cd pollution. However, the transport behavior of Cd in the highly weathered acidic soil layer at the lead-zinc smelting site remains unclear. Here, under different conditions of simulated infiltration, the migration behavior of Cd2+ in acid smelting site soils at different depths was examined. The remodeling effect of Cd2+ migration behavior on microbial community structure and the dominant microorganisms in lead-zinc sites soils was analyzed using high-throughput sequencing of 16S rRNA gene amplicons. The results revealed a specific flow rate in the range of 0.3-0.5 mL/min that the convection and dispersion have no obvious effect on Cd2+ migration. The variation of packing porosity could only influence the migration behavior by changing the average pore velocity, but cannot change the adsorption efficiency of soil particles. The Cd has stronger migration capacity under the reactivation of acidic seepage fluid. However, in the alkaline solution, the physical properties of soil, especially pores, intercept the Cd compounds, further affecting their migration capacity. The acid-site soil with high content of SOM, amorphous Fe oxides, crystalline Fe/Mn/Al oxides, goethite, and hematite has stronger ability to adsorb and retain Cd2+. However, higher content of kaolinite in acidic soil will increase the potential migration of Cd2+. Besides, the migration behavior of Cd2+ results in simplified soil microbial communities. Under Cd stress, Cd-tolerant genera (Bacteroides, Sphingomonas, Bradyrhizobium, and Corynebacterium) and bacteria with both acid-Cd tolerance (WCHB 1-84) were distinguished. The Ralstonia showed a high enrichment degree in alkaline Cd2+ infiltration solution (pH 10.0). Compared to the influence of Cd2+ stress, soil pH had a stronger ability to shape the microbial community in the soil during the process of Cd2+ migration.

Reconstructing the cytokine view for the multi-view prediction of COVID-19 mortality.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a rapidly developing and sometimes lethal pulmonary disease. Accurately predicting COVID-19 mortality will facilitate optimal patient treatment and medical resource deployment, but the clinical practice still needs to address it. Both complete blood counts and cytokine levels were observed to be modified by COVID-19 infection. This study aimed to use inexpensive and easily accessible complete blood counts to build an accurate COVID-19 mortality prediction model. The cytokine fluctuations reflect the inflammatory storm induced by COVID-19, but their levels are not as commonly accessible as complete blood counts. Therefore, this study explored the possibility of predicting cytokine levels based on complete blood counts. METHODS: We used complete blood counts to predict cytokine levels. The predictive model includes an autoencoder, principal component analysis, and linear regression models. We used classifiers such as support vector machine and feature selection models such as adaptive boost to predict the mortality of COVID-19 patients. RESULTS: Complete blood counts and original cytokine levels reached the COVID-19 mortality classification area under the curve (AUC) values of 0.9678 and 0.9111, respectively, and the cytokine levels predicted by the feature set alone reached the classification AUC value of 0.9844. The predicted cytokine levels were more significantly associated with COVID-19 mortality than the original values. CONCLUSIONS: Integrating the predicted cytokine levels and complete blood counts improved a COVID-19 mortality prediction model using complete blood counts only. Both the cytokine level prediction models and the COVID-19 mortality prediction models are publicly available at http://www.healthinformaticslab.org/supp/resources.php .

The fluorescence regulation of a tri-functional oligonucleotide probe HEX-OND in detecting Pb(II), cysteine, and K(I) based on two G-quadruplex forms.

A novel tri-functional probe HEX-OND was developed for detecting Pb(II), cysteine (Cys), and K(I) by fluorescence quenching, recovery, and amplification strategies respectively, based on Pb(II)-induced chair-type G-quadruplex (CGQ) and K(I)-induced parallel G-quadruplex (PGQ). The thermodynamic mechanism was illustrated as that HEX-OND transformed into CGQ by associating equimolar Pb(II) (K1 = 1.10 ± 0.25 × 106 L/mol), forcing (G)2 spontaneously approaching and static-quenching HEX (5'-hexachlorofluorescein phosphoramidite) in the photo-induced electron transfer (PET) way by the van der Waals force and hydrogen bond (K2 = 5.14 ± 1.65 × 107 L/mol); the additional Cys recovered fluorescence in the molecular ratio of 2:1 via Pb(II)-precipitation induced CGQ destruction (K3 = 3.03 ± 0.77 × 109 L/mol); the equimolar K(I) induced HEX-OND transforming into PGQ (K4 = 3.53 ± 0.30 × 104 L/mol) and specifically associating with the equimolar N-methyl mesoporphyrin IX (NMM) by hydrophobic force (K5 = 3.48 ± 1.08 × 105 L/mol), leading to the fluorescence enhancement. Moreover, the practicability results showed that the detection limits reached a nanomolar level for Pb(II) and Cys and micromolar for K(I), with mere disturbances for 6, 10, and 5 kinds of other substances, respectively; no significant deviations of the real sample detection results were found between the well-understood methods with ours in detecting Pb(II) and Cys, and K(I) could be recognized and quantified even in the presence of Na(I) with 5000 and 600 fold respectively. The results demonstrated the triple-function, sensitivity, selectivity, and tremendous application feasibility of the current probe in sensing Pb(II), Cys, and K(I).

Screening, characterization and specific binding mechanism of aptamers against human plasminogen Kringle 5.

Plasminogen Kringle 5 is one of the most potent cytokines identified to inhibit the proliferation and migration of vascular endothelial cells. Herein, six aptamer candidates that specifically bind to Kringle 5 were generated by the systematic evolution of ligands by exponential enrichment (SELEX). After 10 rounds of screening against Kringle 5, a highly enriched ssDNA pool was sequenced and the representative aptamers were subjected to binding assays to evaluate their affinity and specificity. The preferred aptamer KG-4, which demonstrated a low dissociation constant (Kd) of âˆ¼ 432 nM and excellent selectivity for Kringle 5. A conserved "motif" of eight bases located at the stem-loop intersection, common to the aptamer, was further confirmed as the recognition element for binding with Kringle 5. The bulge formed by the motif and depression on the lysine binding site of Kringle 5 were both located at the binding interface, and the "induced fit" between their structures played a central role in the recognition process. Kringle 5 interacts KG-4 primarily through enthalpy-driven van der Waals forces and hydrogen bond. The key nucleotides A34 and C35 at motif on KG-4 and the positively charged amino acids in the loop 1 and loop 4 regions on Kringle 5 play a major role in the interaction. Furthermore, KG-4 dose-dependently reduced the proliferation inhibition of vascular endothelial cells by Kringle 5 and had a blocking effect on the function of Kringle 5 in inhibiting migration and promoting apoptosis of vascular endothelial cells in vitro. This study put a new light on protein-aptamer binding mechanism and may provide insight into the treatment of ischemic diseases by target depletion of Kringle 5.

Micro electrical fields induced MSC-sEVs attenuate neuronal cell apoptosis by activating autophagy via lncRNA MALAT1/miR-22-3p/SIRT1/AMPK axis in spinal cord injury.

Spinal cord injury (SCI) is a traumatic condition of the central nervous system that causes paralysis of the limbs. Micro electric fields (EF) have been implicated in a novel therapeutic approach for nerve injury repair and regeneration, but the effects of human umbilical cord mesenchymal stem cell-derived small extracellular vesicles that are induced by micro electric fields (EF-sEVs) stimulation on SCI remain unknown. The aim of the present study was to investigate whether EF-sEVs have therapeutic effects a rat model of SCI. EF-sEVs and normally conditioned human umbilical cord mesenchymal stem cells-derived small extracellular vesicles (CON-sEVs) were collected and injected intralesionally into SCI model rats to evaluate the therapeutic effects. We detect the expression of candidate long noncoding RNA metastasis-associated lung adenocarcinoma transcript 1 (lncRNA-MALAT1) in EF-sEVs and CON-sEVs. The targets and downstream effectors of lncRNA-MALAT1 were investigated using luciferase reporter assays. Using both in vivo and in vitro experiments, we demonstrated that EF-sEVs increased autophagy and decreased apoptosis after SCI, which promoted the recovery of motor function. We further confirmed that the neuroprotective effects of EF-sEVs in vitro and in vivo correlated with the presence of encapsulated lncRNA-MALAT1 in sEVs. lncRNA-MALAT1 targeted miR-22-3p via sponging, reducing miR-22-3p's suppressive effects on its target, SIRT1, and this translated into AMPK phosphorylation and increased levels of the antiapoptotic protein Bcl-2. Collectively, the present study identified that the lncRNA-MALAT1 in EF-sEVs plays a neuroprotective role via the miRNA-22-3p/SIRT1/AMPK axis and offers a fresh perspective and a potential therapeutic approach using sEVs to improve SCI.

Small Target-YOLOv5: Enhancing the Algorithm for Small Object Detection in Drone Aerial Imagery Based on YOLOv5.

Object detection in drone aerial imagery has been a consistent focal point of research. Aerial images present more intricate backgrounds, greater variation in object scale, and a higher occurrence of small objects compared to standard images. Consequently, conventional object detection algorithms are often unsuitable for direct application in drone scenarios. To address these challenges, this study proposes a drone object detection algorithm model based on YOLOv5, named SMT-YOLOv5 (Small Target-YOLOv5). The enhancement strategy involves improving the feature fusion network by incorporating detection layers and implementing a weighted bidirectional feature pyramid network. Additionally, the introduction of the Combine Attention and Receptive Fields Block (CARFB) receptive field feature extraction module and DyHead dynamic target detection head aims to broaden the receptive field, mitigate information loss, and enhance perceptual capabilities in spatial, scale, and task domains. Experimental validation on the VisDrone2021 dataset confirms a significant improvement in the target detection accuracy of SMT-YOLOv5. Each improvement strategy yields effective results, raising the average precision by 12.4 percentage points compared to the original method. Detection improvements for large, medium, and small targets increase by 6.9%, 9.5%, and 7.7%, respectively, compared to the original method. Similarly, applying the same improvement strategies to the low-complexity YOLOv8n results in SMT-YOLOv8n, which is comparable in complexity to SMT-YOLOv5s. The results indicate that, relative to SMT-YOLOv8n, SMT-YOLOv5s achieves a 2.5 percentage point increase in average precision. Furthermore, comparative experiments with other enhancement methods demonstrate the effectiveness of the improvement strategies.

Complete genome analysis of Lactobacillus fermentum YLF016 and its probiotic characteristics.

Lactobacillus fermentum (L. fermentum) YLF016 is a well-characterized probiotic with several favorable characteristics. This study aimed to analyze the probiotic characteristics of L. fermentum and uncover the genes implicated in its potential probiotic ability on the base of its genomics features. The complete genome of L. fermentum YLF016 was found to have a circular chromosome of 2,094,354 bp, and 51.46% G + C content without any plasmid. Its chromosome contained 2,130 predicted protein-encoding genes, 58 tRNA, and 15 rRNA-encoding genes. Also, it was found to have many other probiotic properties, such as a high survival rate in the gastrointestinal tract with strong adherence to intestinal cells, antibacterial activity against pathogens, and antioxidant activity. Moreover, the genome sequence analysis demonstrated specific genes coding for carbon metabolism pathway, genetic adaption, stress resistance, and adhesive ability. Further analysis revealed its non-hemolytic activity and its non-functional ability of virulence factors. In conclusion, L. fermentum YLF016 possesses many valuable probiotic properties that refer to its potential probiotic ability.

Effects of pH variations caused by redox reactions and pH buffering capacity on Cd(II) speciation in paddy soils during submerging/draining alternation.

Incubation experiments were conducted to investigate the influencing factors of pH variation in different paddy soils during submerging/draining alternation and the relationship between pH buffering capacity (pHBC) and Cd speciation in ten paddy soils developed from different parent materials (including 8 acid paddy soils and 2 alkaline paddy soils). The soil pHBC and the changes in soil pH, Eh, Fe2+, Mn2+, SO42- and Cd speciation were determined. The results showed that there was a significant positive correlation between cation exchange capacity (CEC) and pHBC of these paddy soils, indicating that soil CEC is a key factor affecting the pHBC of paddy soils. The contribution of Fe(III) oxide reduction to H+ consumption is far greater than the reduction of Mn(IV)/Mn(III) oxides and SO42- during the submerging. For example, the contribution of the reduction of manganese oxides, SO42- and iron oxides to H+ consumption in the paddy soils from Anthrosol at 15 d submerging was 1.2%, 11.6% and 87.2%, respectively. This confirms that the reduction of Fe(III) oxides plays a leading role in increasing soil pH. Importantly, we noticed that during submerging, soil pH was increased and resulted in the content of available Cd in soils being reduced. This was due to the transformation of Cd to less active forms. Also, there was a significant positive correlation between the change rate of available Cd, the percentage of acid extractable Cd and pH variation. This suggests that the variation in soil pH was responsible for the transformation of Cd speciation. In addition, the change rate of available Cd and the percentage of acid extractable Cd concentration were significantly negatively correlated with soil pHBC. The soil with higher pHBC experienced less pH change, and thus the change rate of available Cd and the percentage of acid extractable Cd concentration were less for the soil. The results of this study can provide a basis for the remediation of Cd-contaminated acidic paddy soils.

Cadmium, lead and arsenic contamination in an abandoned nonferrous metal smelting site in southern China: Chemical speciation and mobility.

The investigation of chemical speciation of primary toxic metal(loid)s (Cd, Pb, and As) in soil profile in nonferrous metal smelting site is a key to the assessment of their mobility characteristics and formulation of subsequent remediation strategy. In this study, 74 soil samples were collected at 12 different soil profiles; soil physio-chemical properties and total content of Cd, Pb and As and corresponding chemical speciation were also determined. The results showed that the mean total concentration followed the order of Pb > As > Cd. A large proportion of Pb, Cd and As were accumulated in upper soil profiles (depth < 3 m). Heavy pollution of Pb, Cd and As were observed in the whole soil profile at the area of fuel oil storage tank (ZY6) and lead smelting area (ZY8). The dominant fraction of Cd was exchangeable fraction (F1); Pb was dominant in Fe/Mn oxides-bound fraction (F3) in most cases; Crystallized Fe/Al hydrous oxides bound fraction (F4) generally accounted for a large proportion of As. Mobility factor (MF) followed the order Cd > As > Pb, indicating that Cd was the most mobile element in soil profiles. Pearson correlation analysis found that MFCd was significantly positively correlated to soil silt; the F4 fraction percentage of As was significantly positively correlated to soil redox potential (Eh). Additionally, MFCd/Pb was found to be positively correlated to crystalline iron (Fec), while negatively correlated to amorphous iron (Feo). The findings reported in this study, on the basis of distribution characteristics of chemical speciation could provide a new solution for future soil remediation at the site. Long-term solutions to metal(loid)s pollution might be offered by microbial-assisted soil washing technique that promotes the transformation of Fe/Mn oxides-bound fraction and organic/sulfide-bound fraction.

Characterization and identification of SFDC-1, a novel AmpC-type ß-lactamase in Serratia fonticola.

The clinical and environmental infections caused by AmpC ß-lactamases have been increasingly reported recently. In this study, we characterize the novel chromosome-encoded AmpC ß-lactamase SFDC-1 identified in Serratia fonticola strain R28, which was isolated from a rabbit raised on a farm in southern China. SFDC-1 shared the highest amino acid identity of 79.6% with the functionally characterized AmpC ß-lactamase gene blaYRC-1 , although it had highly homologous functionally uncharacterized relatives in the same species from different sources, including some of the clinical significance. The cloned blaSFDC-1 exhibited resistance to a broad spectrum of ß-lactam antibiotics, including most cephalosporins with the highest resistance to ampicillin, cefazolin and ceftazidime, with increased MIC levels ≥128-fold compared with the control strains. The purified SFDC-1 showed catalytic activities against ß-lactams with the highest catalytic activity to cefazolin. The genetic context of blaSFDC-1 and its relatives was conserved in the chromosome, and no mobile genetic elements were found surrounding them.