Background Fermented rhizome functional foods, derived from species such as Curcuma longa, Zingiber officinale, and Panax notoginseng, have gained attention for their potential therapeutic effects in obesity management. We reviewed current literature to evaluate the efficacy of fermented rhizome postbiotics in preclinical obesity models, encompassing anti-adipogenic, thermogenic, gut microbiota-modulatory, and anti-inflammatory roles. This systematic review focused on fermentation organisms, dosages, and underlying mechanisms. Methods A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Embase from inception until April 2026. Inclusion criteria were studies using in vivo or in vitro models assessing fermented rhizome effects on obesity-related outcomes with comparisons to control groups. A total of 10 studies were included. Study quality was assessed using SYRCLE's Risk of Bias Tool and ToxRTool. Results From 1307 studies retrieved, 10 met inclusion criteria across five rhizome species, fermented predominantly with Lactobacillus plantarum and Aspergillus oryzae. All eight in vivo studies reported reductions in body weight and improved lipid profiles. Fermented preparations consistently outperformed unfermented counterparts in all six direct comparisons. Gut microbiota analyses revealed enrichment of Akkermansia muciniphila and an improved Bacteroidetes/Firmicutes ratio. Six mechanistic axes were identified: adipogenesis suppression, AMPK–SIRT1–PGC-1α activation, gut microbiota–SCFA–brown adipose tissue thermogenesis, intestinal barrier reinforcement, inflammatory and ER stress attenuation, and appetite regulation. Conclusions Preclinical evidence, derived predominantly from in vivo diet-induced obesity models, complemented by in vitro mechanistic studies, suggests that fermented rhizome products may contribute to anti-obesity effects through multiple mechanisms. This evidence derives from studies with predominantly unclear-to-high risk of bias (SYRCLE assessment) and no clinical data, and should therefore be regarded as hypothesis-generating rather than directly translatable. Standardized protocols and clinical investigations are needed to confirm therapeutic potential in obesity management.
Optimizing biomass pyrolysis for environmental remediation is bottlenecked by the complex, non-linear thermochemical pathways governing the cation exchange capacity (CEC) of biochar. To circumvent costly empirical trial-and-error, this study aimed to develop a generalized machine learning framework capable of accurately predicting biochar CEC while decoupling its underlying mechanistic pathways. A comprehensive dataset encompassing elemental biomass compositions and operational parameters was modeled using a Gradient Boosting Decision Tree architecture. To ensure robust out-of-sample generalization, structural hyperparameters were optimized across four distinct algorithms: Statistical analysis revealed that Gaussian Process Optimization (GPO) achieved the optimal predictive equilibrium, yielding an exceptional testing coefficient of determination of 0.9353 with minimal error variations, effectively suppressing the overfitting observed in aggressively exploitative Bayesian variants. Additionally, the integration of Shapley Additive Explanations (SHAP) provided critical mathematical interpretability. Global and directional feature analyses validated a dual-pathway mechanism, demonstrating that CEC is primarily driven by the resilient inorganic ash fraction, while secondary organic functional potential is significantly throttled by devolatilization at elevated pyrolysis temperatures. This optimized framework offers a reliable computational foundation for tailoring biochar synthesis without exhaustive physical characterizations. It should be noted that due to current literature data constraints, the model omits critical predictors such as lignocellulosic ratios, heating rate, and categorical feedstock types, which remains a major limitation for future frameworks to address.
Nowadays, RNA therapies represent a cutting-edge therapeutic modality for several human conditions, due to their targeting of the genetic cause of the disease. Within this group, increasing interest is converging onto microRNAs, short non-coding RNA sequences playing a crucial role in cellular processes. In this framework, recent studies assessed the direct correlation between the downregulation of microRNA-29b (miR-29b) and the progression of Alzheimer’s disease, postulating the administration of this oligonucleotide as a treatment for this condition. Despite the great potential, the current manufacturing approaches mainly based on in vitro synthesis are featured by scalability issues, large environmental footprint, and a final product characterized by high immunogenic responses when administrated. These issues may be alleviated by the recombinant production of pre-miR-29b-1. However, this has been reported so far at very small scales and titers, definitely not translatable to a manufacturing scale. In this work, continuous perfusion cultures of the transformed marine bacterium Rhodovulum sulfidophilum were established for the recombinant production of pre-miR-29b-1 with high throughput. Starting from batch liter-scale cultures, the study assessed the role of sodium chloride content in the expansion medium, highlighting a trade-off between microbial growth and product release at increasing salt concentration. From here, we developed the first example of perfusion process for pre-miR-29b-1 biomanufacturing, which allowed to increase the volumetric productivity by 4 times compared to batch operations, in the best-case scenario. These outcomes underline the potential combination of recombinant technology and perfusion cultures to improve process throughput in a sustainable manner.
Modern biomedical science is characterized by a rapid increase in the volume of scientific publications and the growing complexity of the research landscape, which reinforces the need for quantitative methods of analyzing scientific literature, including bibliometrics. This graphical review aims to systematize the methodological approaches to bibliometric analysis and its areas of application in the health sciences, as well as to present visual guidelines for analyzing the structure, dynamics, and interconnections of the biomedical research landscape. The paper examines the key stages of bibliometric research, from the development of search strategies and data processing to methods of scientific mapping and visualization, which allow the identification of thematic clusters and research trends. The main directions of bibliometric application in the health sciences are systematized, including disease research, clinical trial analysis, pharmaceutical development, public health, precision medicine, digital health, mental health, the study of medical misinformation, and issues related to chronic diseases and population aging. Bibliometric analysis offers a quantitative and scalable approach to exploring scientific literature, enabling the identification of key thematic areas, collaboration networks, and emerging trends in biomedical research. Its limitations include database coverage, language and regional biases, disciplinary differences, citation delays, and the fact that citations do not necessarily indicate endorsement. Future developments in bibliometrics are linked to integrating artificial intelligence, machine learning, and semantic analysis, as well as combining bibliometric methods with systematic reviews to enable deeper insights into scientific knowledge. Thus, bibliometrics represents a powerful tool for analyzing the structure and dynamics of health sciences research and can inform strategic decision-making in science policy and healthcare system development.
Pain ranks among the most frequent nonmotor manifestations of Parkinson's disease (PD), yet the morphofunctional condition of the brainstem pain-modulating nuclei is poorly characterized in experimental models. The periaqueductal gray (PAG) and the raphe magnus nucleus (RMG) form the principal descending antinociceptive circuit and are regarded as secondary targets of PD-related neurodegeneration. In the present exploratory study, a rotenone-induced rat model is used to assess neuronal morphology and metabolic activity in the PAG and the RMG and to test the neuroprotective potential of hydrocortisone (HC). Calcium-dependent acid phosphatase (Ca2+-ACP) histochemistry is applied as a dual morphofunctional tool that reports enzymatic metabolic activity together with cellular architecture through lead phosphate deposition. Application of this method to both nuclei under HC treatment in a rotenone PD model has not been reported previously and constitutes the principal novelty of this work. Rotenone exposure produces marked neurodegenerative alterations, which include irregular somatic morphology, nuclear displacement, chromatolysis, dendritic atrophy, and reduced Ca2+-ACP activity. Densitometric analysis with one-way analysis of variance (ANOVA) and Tukey's post hoc test, computed with the animal as the unit of analysis (n = 3 Norm, n = 4 PD, n = 8 PD + HC), shows significant group differences for every parameter measured in both nuclei (p < 0.001). Hydrocortisone treatment is associated with substantial preservation of somatic architecture, nuclear positioning, and dendritic integrity, and with recovery of Ca2+-ACP reactivity to approximately 75 to 80% of control values; the values of the PD + HC group nevertheless remain significantly below those of the intact controls (p < 0.05). The results indicate that the pain-modulating brainstem nuclei are susceptible to PD-related neurodegeneration and that HC affords substantial although partial protection of neuronal morphology and metabolic activity under neurotoxic conditions. Confirmation in larger, balanced, and mechanistically validated cohorts is required.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive deterioration, synaptic failure, and selective neuronal loss in conjunction with the pathological accumulation of amyloid-beta (A(3) peptides. The present study investigates the neuroprotective potential of proline-rich peptide-1 (PRP-1), a hypothalamic immunomodulatory neuropeptide, in two rat models of AD established by intracerebroventricular (ICV) administration of A(325-35 and A(31-42 fragments. These models correspond to early and advanced stages of A(3-induced pathology, respectively, and are therefore complementary rather than equivalent to familial or sporadic AD in humans; the role of amyloid-beta in sporadic AD remains a subject of active investigation. Disruption of intracellular calcium (Ca2+) homeostasis, glutamatergic excitation-inhibition imbalance, and GABAergic dysregulation are recognized as central mechanisms in AD-associated synaptic impairment. Electrophysiological analyses encompassing single-neuron spike recordings and peri-event time histogram (PETH) averaging are applied to hippocampal (HP) neurons following high-frequency stimulation (HFS) of the entorhinal cortex (EC). A stage-dependent modulation of hippocampal neuronal spiking patterns by PRP-1 is demonstrated: neurons exhibiting excitatory response patterns are more completely restored in the A(325-35 model, consistent with an earlier pathological stage, whereas neurons exhibiting inhibitory response patterns are more prominently but incompletely modulated in the A(31-42 model, representative of advanced disease. This differential profile indicates that PRP-1 selectively rebalances excitatory and inhibitory neuronal spiking activity in a stage-dependent manner, supporting its candidacy as a potential therapeutic agent for the attenuation of AD progression.
The manipulation of beneficial microorganisms transcends conventional biotechnology to become the biogenic infrastructure of a resilient agriculture. Although the CRISPR/Cas9 system has established itself as a superior genome editing tool, mainly due to its precision, simplicity, and cost-effectiveness, its full translation into agromicrobial ecosystems faces critical biological and technical bottlenecks. This review comprehensively evaluates the implementation of CRISPR systems in fundamental taxa, such as entomopathogenic fungi, Trichoderma, Bacillus, and diazotrophic bacteria, confronting systemic challenges that include the cytotoxicity of Cas9 overexpression, the frequency of off-target mutations, and structural instability in organisms. Additionally, Brazilian bioinnovation has subverted these limitations through the development of marker-free genomic architectures and the optimization of virulence factors in biocontrol agents, establishing a new paradigm of microbial engineering. The evolution of these tools requires not only the improvement of delivery methods, currently inefficient in several species, but also a radical modernization of regulatory frameworks. This paper discusses how the legal classification of these organisms under Brazilian biosafety will shape the future of intellectual property (IP) and the commercial viability of next-generation microbial biopesticides and inoculants. Ultimately, it proposes that overcoming these technical obstacles and changing public perception are imperative for genome editing to catalyze a sustainable revolution in global agricultural productivity.
The creation of Sustainable Development Goals (SDGs) is a crucial step in addressing global challenges. However, achieving these objectives requires a focus on sustainable bioresource utilization. This paper discusses the potential of papaya biomass in contributing to several SDGs, including Zero Hunger, Good Health and Well-Being, Clean Water and Sanitation, and Affordable and Clean Energy. Various studies have highlighted the diverse applications of papaya, showcasing its use in functional foods, animal feeds, green metallic nanoparticles, carbon dots, biochar, bio-adsorbents, and biodiesel. Notably, acute and sub-chronic toxicity studies have confirmed the safety of papaya-derived products, making them suitable for large-scale commercial use. By leveraging papaya biomass, we can create sustainable solutions that support human well-being and environmental sustainability. This review aims to highlight the importance of papaya valorization in achieving SDGs and promoting a more sustainable future.
Melatonin plays a central role in plant growth regulation and abiotic stress tolerance, and serotonin N-acetyltransferase (SNAT) catalyzes a key step in its biosynthetic pathway. SNAT proteins belong to the GCN5-related Nacetyltransferase (GNAT) superfamily, members of which share conserved acetyltransferase domains but may differ in substrate specificity. Despite the exceptional stress resilience of foxtail millet (Setaria italica), a genomewide analysis of SNAT-related GNAT genes in this species has not yet been reported. In this study, we performed a comprehensive identification and characterization of the SNAT-like GNAT acetyltransferase gene family in foxtail millet. A total of 29 SiSNAT/GNAT genes were identified and unevenly distributed across all nine chromosomes. Phylogenetic analysis revealed clustering with homologs from other monocots, indicating lineagespecific expansion. Gene structure and motif analyses showed substantial diversity, ranging from intronless genes to complex multi-exon members, while all proteins possessed conserved GNAT acetyltransferase domains. Promoter analysis revealed abundant stress- and hormone-responsive cis-elements, suggesting transcriptional regulation under multiple abiotic stresses. Expression profiling by qRT-PCR demonstrated that several SiSNAT genes were strongly induced under drought, salinity, heat, and cold treatments, indicating potential roles in stress adaptation. Protein interaction and functional enrichment analyses linked SiSNAT proteins to acetylationrelated metabolic pathways, including tryptophan metabolism associated with melatonin biosynthesis. This study provides the first genome-wide overview of SNAT-like GNAT genes in foxtail millet and establishes a foundation for understanding their roles in melatonin-associated stress tolerance in cereals.
Existing web-based tools for identifying disease- and trait-associated genetic variants often struggle with scalability and limited database coverage. Their usability in routine genetic analysis and research is often reduced by a lack of support for whole-genome variants and incompatibility with the Genome Reference Consortium Human Build 38 (GRCh38). We developed ShinyDisVar, a web application built with the R Shiny framework. The application supports large-scale variant analysis from genomes by accepting whole-genome variant calling format (VCF) files and querying six integrated disease- and trait-related variant databases: GWAS Catalog, GWASdb, GRASP, GADCDC, Johnson and O'Donnell Database, and ClinVar. All databases were mapped to the GRCh38 genome assembly. Benchmarking was conducted using whole-genome VCF files from ten individuals in the 1000 Genomes Project, each containing 3.87 to 4.74 million variants. Moreover, unlike existing tools, ShinyDisVar uniquely reports disease and trait frequencies, quantifying how often each disease or trait appears across matched variants alongside per-database hit frequency. ShinyDisVar completed variant reading and analysis within 42 to 59 s per sample. Validation tests demonstrated 100% sensitivity and 100% specificity when comparing outputs to known pathogenic and negative control datasets. The platform supports up to 9.5 million variants per file and delivers results in both tabular and graphical formats, allowing users to explore disease- and trait-associations interactively and export results for further analysis. ShinyDisVar addresses the limitations of current web tools by supporting whole-genome VCF input, integrating multiple curated disease and trait databases, and providing fast, accurate, and accessible variant analysis. It enables researchers and clinicians to identify disease- and trait-associated variants without requiring local computational infrastructure or programming expertise. ShinyDisVar is freely available as a user-friendly solution for large-scale genomic variant interpretation in both research and clinical contexts.
Salt-sensitive hypertension (SSH) is a major contributor to cardiovascular and renal morbidity and is characterized by an impaired ability to excrete excess dietary sodium, resulting in extracellular fluid expansion, vascular dysfunction, and persistent elevation of blood pressure. In humans, SSH involves a complex interplay among defective renal pressure–natriuresis, maladaptive activation of the renin–angiotensin–aldosterone system and sympathetic nervous system, endothelial dysfunction, immune-mediated inflammation, and gut microbiota dysbiosis. In contrast, marine fishes inhabit environments containing extremely high sodium chloride concentrations while maintaining osmotic and cardiovascular stability without developing hypertension. Their resilience is enabled by highly specialized osmoregulatory systems involving seawater ingestion, intestinal desalination, active branchial salt secretion, epithelial ion transporters, aquaporin-mediated water recovery, and reduced renal dependence for sodium elimination. This review synthesizes current evidence on the pathophysiology of human SSH and the molecular physiology of marine fish osmoregulation to identify translational insights for kidney and cardiovascular protection. Particular attention is given to conserved ion transport pathways, including Na+/K+-ATPase, NKCC, CFTR, ANO1, aquaporins, claudins, and Na+/H+ exchangers, highlighting their functional parallels across vertebrates. We further propose the Marine Osmoregulation-Inspired Sodium Resilience Model (MOISRM), a conceptual framework describing layered mechanisms of sodium tolerance and cardiovascular protection. Finally, we discuss translational opportunities involving dietary sodium reduction, potassium optimization, natriuretic therapies, RAAS inhibition, immunomodulation, microbiome-targeted interventions, and novel epithelial transporter targets. By integrating comparative physiology with translational medicine, this review positions marine osmoregulation as a promising framework for advancing therapeutic strategies against salt-sensitive hypertension and kidney injury.
Background Group B Streptococcus (GBS) is a leading cause of neonatal infection. Rapid identification of maternal colonization is essential for timely intrapartum prophylaxis. This study evaluated, under laboratory conditions, the diagnostic performance of a molecular point-of-care test (mPOCT) compared with a commercial real-time PCR assay in Vietnamese pregnant women. Methods Rectovaginal swabs from 404 pregnant women were tested using the iPonatic molecular point-of-care test (Sansure Biotech) and a commercial real-time PCR assay (Sacace™ Strep B Real-TM Quant). The study relied mainly on retrospective, frozen, archived specimens (363/404, 89.9%), with a smaller prospective subset of fresh samples (41/404, 10.1%). Discordant results were resolved using additional PCR assays targeting cfb and sip genes. Diagnostic accuracy metrics, likelihood ratios, and agreement statistics were calculated. Results Using a single-run protocol reflective of intended point-of-care use, the iPonatic mPOCT showed a sensitivity of 88.0% (95% CI: 80.7–93.3) and a specificity of 98.6% (95% CI, 96.5–99.6). While specificity was high, the observed sensitivity likely reflects the retrospective use of most archived specimens rather than limitations of the system, as sample storage and handling may have reduced the detectable bacterial load compared with fresh samples. Conclusion The iPonatic mPOCT demonstrated potential as a rapid molecular GBS detection test with a turnaround time of approximately 60 min. However, because the evaluation was conducted mainly on archived specimens under laboratory conditions, the findings should be interpreted as preliminary analytical evidence. Prospective studies using fresh intrapartum specimens and the intended point-of-care workflow are required before routine standalone implementation.
Antibiotic resistance is a major global health threat, driving the need for alternative antimicrobial strategies. Bacteriophage-derived endolysins are promising agents due to their rapid and specific bactericidal activity, but their clinical application is limited by poor stability, short half-life, and inability to penetrate Gram-negative outer membranes. Nanotechnology-based delivery systems offer potential solutions to these limitations. This review summarizes recent advances in polymeric nanoparticles, liposomal systems, metal-based nanoparticles, and self-assembling peptides for enhancing endolysin efficacy. These platforms improve stability, bioavailability, and membrane penetration while enabling controlled and targeted delivery. Despite promising preclinical outcomes, clinical translation remains limited due to regulatory, manufacturing, and immunological challenges. Addressing these barriers is essential for advancing nanotechnology-enhanced endolysins toward clinical application.
Plant-derived exosome-like nanovesicles (PELNs), ranging from 30 to 200 nm, are lipid bilayer membrane nanovesicles isolated from plant tissues that are structurally similar to mammalian exosomes. PELNs contain miRNAs, proteins, lipids, and secondary metabolites that contribute to their diverse therapeutic activities. Due to their easy availability, low immunogenicity, high biocompatibility, relative safety and cost-effectiveness, PELNs are promising therapeutic modalities and drug encapsulation and delivery. Recent studies have highlighted the potential of PELNs to enter cells, modulate cellular activities, and treat various diseases, including inflammation, obesity, and cancer in preclinical models. Despite these encouraging outcomes, standardized methods for PELNs isolation and purification methods are lacking, and the mechanisms governing their cellular uptake and therapeutic effects remain unclear. This review discusses recent developments in PELNs-related research, focusing on disease treatment, underlying mechanisms, and highlights research gaps and future prospects for clinical translation.
Cryptic viral elements (CVEs) are virus-derived genomic sequences integrated into bacterial chromosomes that have lost the ability to form infectious particles but are retained through evolutionary processes. Emerging evidence indicates that some CVEs are functionally active rather than inert, contributing to stress adaptation, gene regulation, and genome stability in certain bacterial systems, including probiotic genera such as Lactobacillus and Bifidobacterium. For instance, defective prophage regions have been associated with oxidative stress tolerance and persistence under nutrient-limited conditions, although these roles remain context- and straindependent. This review critically examines the origin, diversity, and functional relevance of CVEs in probiotic genomes, distinguishing experimentally supported functions from inferred roles in metabolic flexibility and horizontal gene transfer. Current bioinformatic approaches for CVE detection are evaluated, with emphasis on their limitations, including sequence degeneration and annotation biases. While CVEs have been proposed as potential tools for strain improvement and microbiome modulation, direct experimental validation remains limited. Key challenges include incomplete functional characterization and unresolved biosafety concerns. Addressing these gaps will be essential to assess the feasibility of leveraging CVEs in applied microbiology and biotechnology.
In this study, a lignin-degrading bacterial strain, designated SFD3, was isolated from soil and assigned to the genus Escherichia. Molecular identification based on 16S rRNA gene sequencing revealed 98.46% similarity to Escherichia coli and a maximum similarity of 98.66% to Escherichia fergusonii, indicating that precise species-level classification is inconclusive. Therefore, the isolate was conservatively designated as Escherichia sp. SFD3. Phenotypic characterization on eosin methylene blue (EMB) agar showed green metallic sheen colonies, consistent with characteristics commonly associated with E. coli, supporting its affiliation within the genus. The corresponding sequencing information was registered in the NCBI database under accession number PQ368848. To evaluate ligninolytic potential, primers (ECF & ECR) targeting the laccase-like multicopper oxidase (CueO) gene were designed, confirming its presence (accession number PQ493743). This enzyme showed a great capability in oxidizing 3,4-dimethoxy benzyl alcohol (veratryl alcohol), 3-ethylbenzothiazoline-6-sulfonic acid (ABTS), and 2,6-dimethoxyphenol (2,6-DMP) with the highest activities of 340 U L- 1, 4850 U L- 1, and 70 U L- 1, respectively. Low-molecular-weight compounds, including different alkanes and phenols, produced by the strain SFD3 during the delignification process were assessed and identified by GC-MS and FT-IR, and the lignin removal rate by this isolate was measured at 44% after 8 days of incubation. Overall, the discovery of a native Escherichia strain with inherent lignin-degrading capability is noteworthy, as members of this genus are not typically associated with ligninolytic activity. This finding suggests the potential of Escherichia sp. SFD3 as a promising candidate in biorefinery platforms for the valorization of lignocellulosic biomass.
Background: Cervical cancer remains a major global health burden among women. Despite the effectiveness of chemotherapeutic agents such as Cyclophosphamide (CTX), severe systemic toxicity and drug resistance limit their clinical potential. This study investigated the synergistic antitumor effects of CTX in combination with a novel Lactobacillus strain using a transwell co-culture system that enables paracrine interactions without direct bacterial contact. Methods: HeLa cervical cancer cells were exposed to CTX, Lactobacillus, or their combination. Cell viability was evaluated using the MTT assay, while apoptosis was assessed through flow cytometry. Expression levels of Caspase-3, Caspase-9, Bax, Bcl-2, and P53 were determined via quantitative real-time PCR. Results: A pronounced synergistic cytotoxic effect was observed in the combined treatment group. The IC50 of CTX decreased more than 400-fold, while maintaining strong antiproliferative activity (50.16 +/- 2.31% cell viability). This fold change was calculated based on the ratio of IC50 values of CTX in monotherapy versus CTX in combination with Lactobacillus casei Ab.343 SH in the Transwell co-culture system. Gene expression analysis revealed significant upregulation of Caspase-3, Caspase-9, and Bax, with concurrent downregulation of Bcl-2, indicating activation of the intrinsic apoptotic pathway. The results suggest that Lactobacillus-derived metabolites enhance CTX-induced apoptosis via non-contact signaling mechanisms.. Conclusion: Combining CTX with this probiotic strain substantially enhances apoptosis and cytotoxicity in cervical cancer cells while potentially lowering the required chemotherapeutic dose. This combination therapy highlights a promising and safe adjuvant strategy to improve clinical outcomes in cervical cancer treatment.
Predicting the heavy metal adsorption capacity of biochar is a significant challenge due to complex physicochemical mechanisms and the limitations of traditional experimental approaches. This study aimed to develop and validate a robust, interpretable machine learning framework by optimizing Gradient Boosting Decision Trees (GBDT) for this predictive task. Using a comprehensive dataset of 359 experimental points, we compared four hyperparameter optimization heuristics and found that Gaussian Process Optimization (GPO) yielded a model with superior generalization performance. The final GBDT-GPO model achieved a coefficient of determination (R2) of 0.9784 and a mean squared error (MSE) of 0.0035 on an unseen test set, in contrast to other methods like Evolution Strategies, which showed significant overfitting. Furthermore, Shapley Additive Explanations (SHAP) analysis identified initial metal concentration and solution pH as the dominant factors governing adsorption, outweighing physical properties like surface area. This research establishes a highly accurate and interpretable computational strategy that can guide the rational design of biochar and optimize its application in water treatment.
Background: Traditional Chinese Medicine formulations such as Qinwei Oral Granules (QWG) have shown analgesic and anti-inflammatory effects in gout; however, high-quality placebo-controlled evidence remains limited. Methods: In this phase III, multicenter, randomized, double-blind, placebo-controlled trial, 476 patients with acute gouty arthritis from 12 hospitals in China were randomized (3:1) to receive QWG (12 g granules dissolved in water, three times daily; GMP-manufactured, quality controlled by HPLC fingerprinting) or matching placebo for 7 days. The primary endpoint was pain resolution, defined as a VAS pain score <= 10 mm sustained for >= 48 h without rescue medication. Results: In the Full Analysis Set, pain resolution at 168 h was achieved in 60.7% (n = 359) of QWG vs 33.9% (n = 115) of placebo (risk ratio 2.10; 95% CI 1.48-2.98; P < 0.001). Median time to resolution exceeded 168 h in placebo, confirming superiority of QWG (log-rank P < 0.001). Secondary endpoints, including reductions in C-reactive protein (10.987 (18.003) vs -13.346 (18.366) mg/L; P < 0.001) and erythrocyte sedimentation rate (16.94 (49.67) vs -17.32 (20.76) mm/h; P < 0.001), were all significantly improved in the QWG group. Findings were consistent in the Per-Protocol Set. Adverse events occurred in 33.15% of QWG vs 29.81% of placebo, mainly mild gastrointestinal discomfort; no serious adverse reactions were reported. Conclusions: QWG significantly accelerated pain resolution and reduced systemic inflammation compared with placebo, with a favorable safety profile. These findings support QWG as a potential therapeutic option for acute gouty arthritis.
Single-stage microbial production of polyhydroxyalkanoates (PHA) requests concurrent microbial selection, biomass maintenance, and intracellular polymer storage within the same unit, thereby hindering the attainment of high-level PHA storage. Two-stage sequencing batch reactors (SBRs), designated as A-SBR and B-SBR, were established to develop efficient PHA production by mixed microbial cultures (MMC). Our results showed that A-SBR had developed a continuous biomass with a stable PHA storage capacity of 31.1+6.4%, with a maximum PHA content of 44.3%. On this basis, B-SBR achieved efficient PHA storage of 63.2+10.7% during the steady state with a peak value of 86.8%, with continuously receiving the PHA-storing biomass from A-SBR. Correspondingly, the PHA yields of A-SBR and B-SBR were 0.2+0.1 and 0.5+0.1 g CODPHA/g COD, respectively. Notably, B-SBR achieved a peak PHA yield of 0.8 g CODPHA/g COD, promising its superior PHA production potency. The 16S rRNA gene amplicon sequencing revealed that the two-stage SBRs developed rich and distinct PHA-producing populations, which together occupied 37.9%-54.9% and 33.6%-62.3% of the total microbial populations in A-SBR and B-SBR, respectively. Notably, Allobrachymonas and Paracoccus dominated in A-SBR, and Paracoccus, Allobrachymonas, and Thauera dominated in B-SBR. Prediction of microbial functional profiles further validated the dominance of enzymes essential for PHA biosynthesis. This study was the first to validate the high efficiency of MMC-based anoxic PHA production in a two-stage SBR configuration, which promises high rate PHA production in a cost-saving manner owing to the anoxic operation mode and thus encourages further efforts on the development of MMC-based two-stage anoxic PHA production.
