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OBJECTIVES: To evaluate the concordance of results between the HORIZON-Pivotal Fracture Trial (PFT) and a non-randomized database study designed to emulate the trial. METHODS: HORIZON-PFT evaluated the efficacy of zoledronic acid vs placebo in reducing the risk of hip fractures and found a 41% risk reduction over a 3-year treatment period (HR = 0.59; 95% CI 0.42 to 0.83). Using two U.S. claims databases from 08/2007 to 12/2020 or 06/2021 we applied eligibility criteria from HORIZON-PFT and identified women with osteoporosis who initiated zoledronic acid or raloxifene as a proxy for placebo. The study protocol was registered on ClinicalTrials.gov (NCT04736693) before inferential analyses. We compared HORIZON-PFT and database study results using prespecified metrics. RESULTS: Due to low adherence in clinical practice, on-treatment follow up was truncated at 18 months in the database study. The hip fracture risk after 18 months was 9.3/1000 in the trial and 8.3/1000 in the database analysis. In the database study, zoledronic acid was associated with a 28% reduction in hip fractures risk compared to raloxifene (HR = 0.72; 95% CI 0.51 to 0.92). The attenuated effect of zoledronic acid in the database study may be explained by its shorter follow-up, as the interpolated estimate of the effect in HORIZON-PFT at 18 months was HRRCT 0.74, nearly identical to the observational estimate HRdatabase 0.72. CONCLUSION: Real-world emulation of the HORIZON-PFT found that zoledronic acid reduced hip fractures risk over an 18-month follow-up period. Limited adherence in clinical practice diminished the magnitude of its preventive effect and precluded long-term estimation of effectiveness in this setting.
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Chemical synthesis plays a crucial role in confirming and revising the structures of natural products. Through meticulous synthetic efforts, NMR spectroscopic and single-crystal X-ray diffraction analyses, DFT calculations, and mass spectrometric investigations, we revised the structure of securingine E. The revised structure of securingine E was unambiguously confirmed by its chemical synthesis.
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OBJECTIVE: Extrapyramidal symptoms (EPS) are common side effects of antipsychotic drugs. Despite the growing interest in exploring objective biomarkers for EPS prevention and the potential use of voice in detecting clinical disorders, no studies have demonstrated the relationships between vocal changes and EPS. Therefore, we aimed to determine the associations between voice changes and antipsychotic dosage, and further investigated whether speech characteristics could be used as predictors of EPS. METHODS: Forty-two patients receiving or expected to receive antipsychotic drugs were recruited. Drug-induced parkinsonism of EPS was evaluated using the Simpson-Angus Scale (SAS). Participants' voice data consisted of 16 neutral sentences and 2 second-long /Ah/utterances. Thirteen voice features were extracted from the obtained voice data. Each voice feature was compared between groups categorized based on SAS total score of below and above "0.6." The associations between antipsychotic dosage and voice characteristics were examined, and vocal trait variations according to the presence of EPS were explored. RESULTS: Significant associations were observed between specific vocal characteristics and antipsychotic dosage across both datasets of 1-16 sentences and /Ah/utterances. Notably, Mel-Frequency Cepstral Coefficients (MFCC) exhibited noteworthy variations in response to the presence of EPS. Specifically, among the 13 MFCC coefficients, MFCC1 (t=-4.47, p<0.001), MFCC8 (t=-4.49, p<0.001), and MFCC12 (t=-2.21, p=0.029) showed significant group differences in the overall statistical values. CONCLUSION: Our results suggest that MFCC may serve as a predictor of detecting drug-induced parkinsonism of EPS. Further research should address potential confounding factors impacting the relationship between MFCC and antipsychotic dosage, possibly improving EPS detection and reducing antipsychotic medication side effects.
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Necroptosis, a cell death mechanism with the characteristics of both apoptosis and necrosis, is proposed as a promising therapeutic approach for cancer therapy. Induction of necroptosis for cancer therapy may be possible through the regulation of the expression of a key factor gene receptor-interacting protein kinase-3 (RIPK3) via in vitro transcription (IVT) mRNA delivery. However, mRNA is susceptible to degradation and has a low delivery efficiency, which highlights the requirement of a proper delivery vehicle for intracellular delivery. Therefore, a new mRNA delivery system based on the nanostructured silica nanoparticles, termed mRNA-protective nanocage (mPN) has been developed. High-efficiency expression of RIPK3 and induction of necroptosis is achieved through delivery of RIPK3 IVT mRNA with mPN in vitro and in vivo models. Importantly, the mPN carrying RIPK3 mRNA distributed locally in tumors upon intravascular injection, and successfully induced necroptosis and immune cell infiltration, a hallmark of necroptosis. the suppression of tumor growth in a murine cancer model, demonstrating the synergistic effect of RIPK3 mRNA- and immune cell-mediated therapy is also observed. These findings suggest the potential for anticancer therapy through necroptosis induction and provide a strategy for the development of mRNA-based nanomedicine.
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The mechanical strength of magnesium implants undergoes a rapid decline after implantation due to bioabsorption, which can lead to the risk of rupture. To ensure sustained mechanical strength and initiate bioabsorption selectively upon specific external stimuli until the bone regains sufficient support, we developed a biosafe near-infrared light (NIR)-sensitive polymer coating using polycaprolactone (PCL) and Ti3C2 (MXenes). The synthetic MXene powders were characterized using SEM, EDS, and XRD, and the amount of MXenes had a proliferation-promoting effect on MC3T3-E1, as observed through cell assays. The PCL-MXene coating was successfully prepared on the magnesium surface using the casting coating method, and it can protect the magnesium surface for up to 28 days by decreasing the corrosion ratio. However, the coating can be easily degraded after exposure to NIR light for 20 minutes to expose the magnesium substrate, especially in a liquid environment. Meanwhile, the magnesium implant with the PCL-MXene coating has no cytotoxicity toward MC3T3-E1. These findings can provide a new solution for the development of controlled degradation implants.
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The diagnosis of anaphylaxis is based on the clinical history. The utility of tryptase measurements in clinical setting is limited. Mas-related G protein-coupled receptor-X2 (MRGPRX2) is expressed in mast cells and is involved in the degranulation of these cells. We evaluated the potential of MRGPRX2 as a diagnostic biomarker in patients with iodinated contrast media (ICM)-induced immediate hypersensitivity reactions (IHRs). A total of 173 patients with documented ICM-induced IHR within 4 months from registration were enrolled and skin tests for the culprit ICM were performed. The time interval was evaluated as the duration between the onset of ICM-induced IHR and the measurement of serum MRGPRX2 levels. Serum MRGPRX2 concentration was determined using an enzyme-linked immunosorbent assay kit. Of the 173 patients, 33 and 140 were included in the anaphylaxis and non-anaphylaxis groups, respectively. Serum MRGPRX2 levels were significantly higher in the anaphylaxis than in the non-anaphylaxis group (29.9 ± 24.1 vs. 20.7±17.5, P = 0.044). Serum MRGPRX2 showed a moderate predictive ability for anaphylaxis, with an area under the curve of 0.61 (P = 0.058). When groups were classified based on the time interval, T1(0-2months) and T2 (2-4months), patients with anaphylaxis had higher MRGPRX2 levels compared to the non-anaphylaxis group in the T2 group (36.5±19.2 vs. 20.5±19.0, P = 0.035). This pilot study shows that serum MRGPRX2 is a potential long-term biomarker for predicting anaphylaxis, particularly ICM-induced anaphylaxis. Further studies are needed to determine the role of MRGPRX2 in anaphylaxis in a larger population of patients with various drug-induced IHRs.
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BACKGROUND: For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialised tools are used. Three tools have been proven useful to personalise drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging. METHODS: In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 45 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)). RESULTS: Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings. CONCLUSION: All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimise treatment effects, minimise side effects and ultimately reduce the global burden of diseases, personalised drug treatment has not yet become the standard of care in psychiatry.
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Front-of-package (FOP) is one of the most direct communication channels connecting manufacturers and consumers, as it displays crucial information such as certification, nutrition, and health. Traditional methods for obtaining information from FOPs often involved manual collection and analysis. To overcome these labor-intensive characteristics, new methods using two artificial intelligence (AI) approaches were applied for information monitoring of FOPs. In order to provide practical implementations, a case study was conducted on infant food products. First, FOP images were collected from Amazon.com. Then, from the FOP images, 1) the certification usage status of the infant food group was obtained by recognizing the certification marks using object detection. Moreover, 2) the nutrition and health-related texts written on the images were automatically extracted based on optical character recognition (OCR), and the associations between health-related texts were identified by network analysis. The model attained a 94.9% accuracy in identifying certification marks, unveiling prevalent certifications like Kosher. Frequency and network analysis revealed common nutrients and health associations, providing valuable insights into consumer perception. These methods enable fast and efficient monitoring capabilities, which can significantly benefit various food industries. Moreover, the AI-based approaches used in the study are believed to offer insights for related industries regarding the swift transformations in product information status.
Subject(s)
Artificial Intelligence , Infant Food , Humans , Infant , Food Labeling , Food PackagingABSTRACT
The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist to efficiently test for differences across subgroups in the thousands of multiple comparisons generated as part of a PheWAS. In this study, we developed an approach that maximizes the power to test for heterogeneous genotype-phenotype associations and applied this approach to an IL6R PheWAS among individuals of African (AFR) and European (EUR) ancestries. We identified 29 traits with differences in IL6R variant-phenotype associations, including a lower risk of type 2 diabetes in AFR (OR 0.96) vs EUR (OR 1.0, p-value for heterogeneity = 8.5 × 10-3), and higher white blood cell count (p-value for heterogeneity = 8.5 × 10-131). These data suggest a more salutary effect of IL6R blockade for T2D among individuals of AFR vs EUR ancestry and provide data to inform ongoing clinical trials targeting IL6 for an expanding number of conditions. Moreover, the method to test for heterogeneity of associations can be applied broadly to other large-scale genotype-phenotype screens in diverse populations.
Subject(s)
Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/genetics , Genetic Association Studies , Phenotype , Polymorphism, Single Nucleotide , Receptors, Interleukin-6/geneticsABSTRACT
It is highly challenging to reproducibly prepare semiconducting polymers with targeted molecular weight tailored for next-generation photovoltaic applications. Once such an easily accessible methodology is established, which can not only contribute to overcome the current limitation of the statistically determined nature of semiconducting polymers, but also facilitate rapid incorporation into the broad synthetic chemists' toolbox. Here, we describe a simple yet robust ultrasonication-assisted Stille polymerization for accessing semiconducting polymers with high-precision tailored molecular weights (from low to ultrahigh molecular weight ranges) while mitigating their interbatch variations. We propose that ultrasound-induced simultaneous physical and chemical events enable precise control of the semiconducting polymers' molecular weights with high reproducibility to satisfy all the optical/electrical and morphological demands of diverse types of high-performance semiconducting polymer-based devices; as demonstrated in in-depth experimental screenings in applications of both organic and perovskite photovoltaics. We believe that this methodology provides a fast development of new and existing semiconducting polymers with the highest-level performances possible on various photovoltaic devices.
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Polymer solar cells (PSCs) rely on a blend of small molecular acceptors (SMAs) with polymer donors, where thermodynamic relaxation of SMAs poses critical concerns on operational stability. To tackle this issue, tethered SMAs, wherein multiple SMA-subunits are connected to the aromatic-core via flexible chains, are proposed. This design aims to an elevated glass transition temperature (Tg) for a dynamical control. However, attaining an elevated Tg value with additional SMA subunits introduces complexity to the molecular packing, posing a significant challenge in realizing both high stability and power conversion efficiency (PCE). In this study, we initiate isomer engineering on the benzene-carboxylate core and find that meta-positioned dimeric BDY-ß exhibits more favorable molecular packing compared to its para-positioned counterpart, BDY-α. With this encouraging result, we expand our approach by introducing an additional SMA unit onto the aromatic core of BDY-ß, maintaining a meta-position relative to each SMA unit location in the tethered acceptor. This systematic aromatic-core engineering results in a star-shaped C3h-positioned molecular geometry. The supramolecular interactions of SMA units in the trimer contribute to enhancements in Tg value, crystallinity, and a red-shifted absorption compared to dimers. These characteristics result in a noteworthy increase in PCE to 18.24 %, coupled with a remarkable short-circuit current density of 27.06â mA cm-2. More significantly, the trimer-based devices delivered an excellent thermal stability with over 95 % of their initial efficiency after 1200â h thermal degradation. Our findings underscore the promise and feasibility of tethered trimeric structures in achieving highly ordered aggregation behavior and increased Tg value in PSCs, simultaneously improving in device efficiency and thermal stability.
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Securinega alkaloids have intrigued chemists since the isolation of securinine in 1956. This family of natural products comprises a securinane subfamily with a piperidine substructure and norsecurinane alkaloids featuring a pyrrolidine core. From a biosynthetic perspective, the piperidine moiety in securinane alkaloids derives from lysine, whereas the pyrrolidine moiety in norsecurinane natural products originates from ornithine, marking an early biogenetic divergence. Herein, we introduce a single-atom deletion strategy that enables the late-stage conversion of securinane to norsecurinane alkaloids. Notably, for the first time, this method enabled the transformation of piperidine-based (allo)securinine into pyrrolidine-based (allo)norsecurinine. Straightforward access to norsecurinine from securinine, which can be readily extracted from the plant Flueggea suffruticosa, abundant across the Korean peninsula, holds promise for synthetic studies of norsecurinine-based oligomeric securinega alkaloids.
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BACKGROUND: Osteoarthritis (OA) patients taking prescription opioids for pain are at increased risk of fall or fracture, and the concomitant use of interacting drugs may further increase the risk of these events. AIMS: To identify prescription opioid-related medication combinations associated with fall or fracture. MATERIALS & METHODS: We conducted a case-crossover-based screening of two administrative claims databases spanning 2003 through 2021. OA patients were aged 40 years or older with at least 365 days of continuous enrollment and 90 days of continuous prescription opioid use before their first eligible fall or fracture event. The primary analysis quantified the odds ratio (OR) between fall and non-opioid medications dispensed in the 90 days before the fall date after adjustment for prescription opioid dosage and confounding using a case-time-control design. A secondary analogous analysis evaluated medications associated with fracture. The false discovery rate (FDR) was used to account for multiple testing. RESULTS: We identified 41 693 OA patients who experienced a fall and 24 891 OA patients who experienced a fracture after at least 90 days of continuous opioid therapy. Top non-opioid medications by ascending p-value with OR > 1 for fall were meloxicam (OR 1.22, FDR = 0.08), metoprolol (OR 1.06, FDR >0.99), and celecoxib (OR 1.13, FDR > 0.99). Top non-opioid medications for fracture were losartan (OR 1.20, FDR = 0.80), alprazolam (OR 1.14, FDR > 0.99), and duloxetine (OR 1.12, FDR = 0.97). CONCLUSION: Clinicians may seek to monitor patients who are co-prescribed drugs that act on the central nervous system, especially in individuals with OA.
Subject(s)
Fractures, Bone , Osteoarthritis , Prescription Drugs , Humans , Analgesics, Opioid/adverse effects , Osteoarthritis/drug therapy , Osteoarthritis/epidemiology , Osteoarthritis/chemically induced , Fractures, Bone/etiology , Fractures, Bone/chemically induced , PrescriptionsABSTRACT
Single-component organic solar cells (SCOSCs) with covalently bonding donor and acceptor are becoming increasingly attractive because of their superior stability over traditional multicomponent blend organic solar cells (OSCs). Nevertheless, the efficiency of SCOSCs is far behind the state-of-the-art multicomponent OSCs. Herein, by combination of the advantages of three-component and single-component devices, this work reports an innovative three-in-one strategy to boost the performance of SCOSCs. In this three-in-one strategy, three independent components (PM6, D18, and PYIT) are covalently linked together to create a new single-component active layer based on ternary conjugated block copolymer (TCBC) PM6-D18-b-PYIT by a facile polymerization. Precisely manipulating the component ratios in the polymer chains of PM6-D18-b-PYIT is able to broaden light utilization, promote charge dynamics, optimize, and stabilize film morphology, contributing to the simultaneously enhanced efficiency and stability of the SCOSCs. Ultimately, the PM6-D18-b-PYIT-based device exhibits a power conversion efficiency (PCE) of 14.89%, which is the highest efficiency of the reported SCOSCs. Thanks to the aggregation restriction of each component and chain entanglement in the three-in-one system, the PM6-D18-b-PYIT-based SCOSC displays significantly higher stability than the corresponding two-component (PM6-D18:PYIT) and three-component (PM6:D18:PYIT). These results demonstrate that the three-in-one strategy is facile and promising for developing SCOSCs with superior efficiency and stability.
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We aimed to evaluate the effects of obesity treatment with behavioral therapy (BT) and cognitive behavioral therapy (CBT) interventions compared with multiple comparators and find effective techniques or combinations of techniques in BT and CBT interventions for weight loss. We systematically searched electronic databases and selected randomized controlled trials using CBT or BT intervention for obesity treatment in overweight adults or adults with obesity without psychological symptoms. Both pairwise meta-analysis and network meta-analysis were performed to comprehensively evaluate the comparative effects between interventions. We classified the techniques used in BT and CBT interventions and compared the treatment effects between techniques. Compared with no treatment as a common comparator, CBT was most effective for weight loss, followed by BT, usual care (UC), and minimal care (MC). CBT was a more effective intervention than BT, but the effect of CBT compared to BT was not remarkable in network estimates. The most used BT techniques were feedback and monitoring, and the most used CBT technique was cognitive restructuring. Our results indicated that CBT and BT are effective interventions for weight loss, and that successful weight loss requires more aggressive interventions such as BT or CBT than MC and UC.
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BACKGROUND: We aimed to determine whether integrating concepts from the notes from the electronic health record (EHR) data using natural language processing (NLP) could improve the identification of gout flares. METHODS: Using Medicare claims linked with EHR, we selected gout patients who initiated the urate-lowering therapy (ULT). Patients' 12-month baseline period and on-treatment follow-up were segmented into 1-month units. We retrieved EHR notes for months with gout diagnosis codes and processed notes for NLP concepts. We selected a random sample of 500 patients and reviewed each of their notes for the presence of a physician-documented gout flare. Months containing at least 1 note mentioning gout flares were considered months with events. We used 60% of patients to train predictive models with LASSO. We evaluated the models by the area under the curve (AUC) in the validation data and examined positive/negative predictive values (P/NPV). RESULTS: We extracted and labeled 839 months of follow-up (280 with gout flares). The claims-only model selected 20 variables (AUC = 0.69). The NLP concept-only model selected 15 (AUC = 0.69). The combined model selected 32 claims variables and 13 NLP concepts (AUC = 0.73). The claims-only model had a PPV of 0.64 [0.50, 0.77] and an NPV of 0.71 [0.65, 0.76], whereas the combined model had a PPV of 0.76 [0.61, 0.88] and an NPV of 0.71 [0.65, 0.76]. CONCLUSION: Adding NLP concept variables to claims variables resulted in a small improvement in the identification of gout flares. Our data-driven claims-only model and our combined claims/NLP-concept model outperformed existing rule-based claims algorithms reliant on medication use, diagnosis, and procedure codes.
Subject(s)
Gout , Aged , Humans , United States/epidemiology , Gout/diagnosis , Gout/epidemiology , Natural Language Processing , Electronic Health Records , Medicare , Symptom Flare Up , AlgorithmsABSTRACT
Large areas and simple processing methods are necessary for the commercialization of organic photovoltaics (OPVs). However, the efficiency drop due to the variation in thickness of OPVs limits their large-scale applications. Regioregular polymers with good crystallinity and packing properties that exhibit high charge mobility and extraction ability can help overcome these limitations. In this study, a regioregular polymer named PDBD-2FBT was synthesized. The crystallinity and packing properties of PDBD-2FBT were enhanced by a simple thermal treatment. Using PDBD-2FBT material as a donor and Y6-HU as an acceptor, we fabricated binary blend OPV devices. The devices with optimized active layer thickness achieved a power conversion efficiency (PCE) of 14.14%. A PCE of 13.18% was maintained even in thick-film conditions (400 nm), and thickness tolerance was observed. Based on the thickness tolerance, a 5-line module measuring 36 cm2 was fabricated via the bar-coating method, and a PCE of approximately 10% was achieved.
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Prokaryotes play an important role in marine nitrogen and methane cycles. However, their community changes and metabolic modifications to the concurrent impact of ocean warming (OW), acidification (OA), deoxygenation (OD), and anthropogenicnitrogen-deposition (AND) from the surface to the deep ocean remains unknown. We examined here the amplicon sequencing approach across the surface (0-200 m; SL), intermediate (200-1000 m; IL), and deep layers (1000-2200 m; DL), and characterized the simultaneous impacts of OW, OA, OD, and AND on the Western North Pacific Ocean prokaryotic changes and their functional pattern in nitrogen and methane cycles. Results showed that SL possesses higher ammonium oxidation community/metabolic composition assumably the reason for excess nitrogen input from AND and modification of their kinetic properties to OW adaptation. Expanding OD at IL showed hypoxic conditions in the oxygen minimum layer, inducing higher microbial respiration that elevates the dimerization of nitrification genes for higher nitrous oxide production. The aerobic methane-oxidation composition was dominant in SL presumably the reason for adjustment in prokaryotic optimal temperature to OW, while anaerobic oxidation composition was dominant at IL due to the evolutionary changes coupling with higher nitrification. Our findings refocus on climate-change impacts on the open ocean ecosystem from the surface to the deep-environment integrating climate-drivers as key factors for higher nitrous-oxide and methane emissions.
Subject(s)
Ecosystem , Seawater , Pacific Ocean , Methane , NitrogenABSTRACT
Twigs of Morus alba have been used in traditional medicine to treat muscle-related symptoms such as aches, numbness, and stiffness. Despite its clinical use in traditional medicine, its active compounds and mode of action have not yet been investigated. Therefore, we aimed to isolate the compounds from the twigs of M. alba and deduce active compounds, key gene targets, and mechanism of action against sarcopenia using network pharmacology analysis. Using various isolation techniques and spectroscopic methods, 43 phytochemicals, including 3 new flavonoids, were isolated and performed network pharmacology analysis. According to the computational-assistant analysis, 28 compounds, 9 genes, and the PI3K-Akt-mTOR signaling pathway were deduced as expected active compounds (EAC), key targets, and the main signaling pathway. To verify the predicted results, the cell proliferation activities of the EAC were evaluated. Especially, moracin E and M significantly increased by 130% (p < 0.001) and 57% (p < 0.05), respectively, which have more than 2- and 1.5-fold stronger effects compared to the control. Furthermore, both increased the expression level of proteins involved in the PI3K-Akt-mTOR signaling pathway and myogenic proteins, including myogenin and MyoD. This study demonstrated that moracin E and M exhibit cell proliferative effects on skeletal muscle cells through the PI3K-Akt-mTOR signaling pathway.
Subject(s)
Morus , Proto-Oncogene Proteins c-akt , Cell Proliferation , Morus/chemistry , Muscle, Skeletal/metabolism , Phosphatidylinositol 3-Kinases/metabolism , Proto-Oncogene Proteins c-akt/metabolism , Signal Transduction , TOR Serine-Threonine Kinases/metabolismABSTRACT
Staphylococcus aureus is a commensal skin bacterium and a causative agent of infectious diseases. Biofilm formation in S. aureus is a mechanism that facilitates the emergence of resistant strains. This study proposes a mechanism for the regulation of biofilm formation in S. aureus through strain-specific physiological changes induced by the plant steroid diosgenin. A comparison of diosgenin-induced changes in the expression of regulatory genes associated with physiological changes revealed the intracellular regulatory mechanisms involved in biofilm formation. Diosgenin reduced biofilm formation in S. aureus ATCC 6538 and methicillin-resistant S. aureus (MRSA) CCARM 3090 by 39% and 61%, respectively. Conversely, it increased biofilm formation in S. aureus ATCC 29213 and MRSA CCARM 3820 by 186% and 582%, respectively. Cell surface hydrophobicity and extracellular protein and carbohydrate contents changed in a strain-specific manner in response to biofilm formation. An assessment of the changes in gene expression associated with biofilm formation revealed that diosgenin treatment decreased the expression of icaA and spa and increased the expression of RNAIII, agrA, sarA, and sigB in S. aureus ATCC 6538 and MRSA CCARM 3090; however, contrasting gene expression changes were noted in S. aureus ATCC 29213 and MRSA CCARM 3820. These results suggest that a regulatory mechanism of biofilm formation is that activated sigB expression sequentially increases the expression of sarA, agrA, and RNAIII. This increased RNAIII expression decreases the expression of spa, a surface-associated adhesion factor. An additional regulatory mechanism of biofilm formation is that activated sigB expression decreases the expression of an unknown regulator that increases the expression of icaA. This in turn decreases the expression of icaA, which decreases the synthesis of polysaccharide intercellular adhesins and ultimately inhibits biofilm formation. By assessing strain-specific contrasting regulatory signals induced by diosgenin in S. aureus without gene mutation, this study elucidated the signal transduction mechanisms that regulate biofilm formation based on physiological and gene expression changes.