DB-1310, an ADC comprised of a novel anti-HER3 antibody conjugated to a DNA topoisomerase I inhibitor, is highly effective for the treatment of HER3-positive solid tumors.

BACKGROUND: HER3 (ErbB3), a member of the human epidermal growth factor receptor family, is frequently overexpressed in various cancers. Multiple HER3-targeting antibodies and antibody-drug conjugates (ADCs) were developed for the solid tumor treatment, however none of HER3-targeting agent has been approved for tumor therapy yet. We developed DB-1310, a HER3 ADC composed of a novel humanized anti-HER3 monoclonal antibody covalently linked to a proprietary DNA topoisomerase I inhibitor payload (P1021), and evaluate the efficacy and safety of DB-1310 in preclinical models. METHODS: The binding of DB-1310 to Her3 and other HER families were measured by ELISA and SPR. The competition of binding epitope for DB-1310 and patritumab was tested by FACS. The sensitivity of breast, lung, prostate and colon cancer cell lines to DB-1310 was evaluated by in vitro cell killing assay. In vivo growth inhibition study evaluated the sensitivity of DB-1310 to Her3 + breast, lung, colon and prostate cancer xenograft models. The safety profile was also measured in cynomolgus monkey. RESULTS: DB-1310 binds HER3 via a novel epitope with high affinity and internalization capacity. In vitro, DB-1310 exhibited cytotoxicity in numerous HER3 + breast, lung, prostate and colon cancer cell lines. In vivo studies in HER3 + HCC1569 breast cancer, NCI-H441 lung cancer and Colo205 colon cancer xenograft models showed DB-1310 to have dose-dependent tumoricidal activity. Tumor suppression was also observed in HER3 + non-small cell lung cancer (NSCLC) and prostate cancer patient-derived xenograft (PDX) models. Moreover, DB-1310 showed stronger tumor growth-inhibitory activity than patritumab deruxtecan (HER3-DXd), which is another HER3 ADC in clinical development at the same dose. The tumor-suppressive activity of DB-1310 synergized with that of EGFR tyrosine kinase inhibitor, osimertinib, and exerted efficacy also in osimertinib-resistant PDX model. The preclinical assessment of safety in cynomolgus monkeys further revealed DB-1310 to have a good safety profile with a highest non severely toxic dose (HNSTD) of 45 mg/kg. CONCLUSIONS: These finding demonstrated that DB-1310 exerted potent antitumor activities against HER3 + tumors in in vitro and in vivo models, and showed acceptable safety profiles in nonclinical species. Therefore, DB-1310 may be effective for the clinical treatment of HER3 + solid tumors.

Assessing Permutationally Invariant Polynomial and Symmetric Gradient Domain Machine Learning Potential Energy Surfaces for H3O2.

The singly hydrated hydroxide anion OH-(H2O) is of central importance to a detailed molecular understanding of water; therefore, there is strong motivation to develop a highly accurate potential to describe this anion. While this is a small molecule, it is necessary to have an extensive data set of energies and, if possible, forces to span several important stationary points. Here, we assess two machine-learned potentials, one using the symmetric gradient domain machine learning (sGDML) method and one based on permutationally invariant polynomials (PIPs). These are successors to a PIP potential energy surface (PES) reported in 2004. We describe the details of both fitting methods and then compare the two PESs with respect to precision, properties, and speed of evaluation. While the precision of the potentials is similar, the PIP PES is much faster to evaluate for energies and energies plus gradient than the sGDML one. Diffusion Monte Carlo calculations of the ground vibrational state, using both potentials, produce similar large anharmonic downshift of the zero-point energy compared to the harmonic approximation of the PIP and sGDML potentials. The computational time for these calculations using the sGDML PES is roughly 300 times greater than using the PIP one.

Tell Machine Learning Potentials What They Are Needed For: Simulation-Oriented Training Exemplified for Glycine.

Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surfaces (PESs) in many chemical simulations. The MLPs are often evaluated with the root-mean-square errors on the test set drawn from the same distribution as the training data. Here, we systematically investigate the relationship between such test errors and the simulation accuracy with MLPs on an example of a full-dimensional, global PES for the glycine amino acid. Our results show that the errors in the test set do not unambiguously reflect the MLP performance in different simulation tasks, such as relative conformer energies, barriers, vibrational levels, and zero-point vibrational energies. We also offer an easily accessible solution for improving the MLP quality in a simulation-oriented manner, yielding the most precise relative conformer energies and barriers. This solution also passed the stringent test by diffusion Monte Carlo simulations.

No Headache for PIPs: A PIP Potential for Aspirin Runs Much Faster and with Similar Precision Than Other Machine-Learned Potentials.

Assessments of machine-learning (ML) potentials are an important aspect of the rapid development of this field. We recently reported an assessment of the linear-regression permutationally invariant polynomial (PIP) method for ethanol, using the widely used (revised) rMD17 data set. We demonstrated that the PIP approach outperformed numerous other methods, e.g., ANI, PhysNet, sGDML, and p-KRR, with respect to precision and notably with respect to speed [Houston et al., J. Chem. Phys. 2022, 156, 044120]. Here, we extend this assessment to the 21-atom aspirin molecule, using the rMD17 data set, with a focus on the speed of evaluation. Both energies and forces are used for training, and the precision of several PIPs is examined for both. Normal mode frequencies, the methyl torsional potential, and 1d vibrational energies for an OH stretch are presented. We show that the PIP approach achieves the level of precision obtained from other ML methods, e.g., atom-centered neural network methods, linear regression ACE, and kernel methods, as reported by Kovács et al. in J. Chem. Theory Comput. 2021, 17, 7696-7711. More significantly, we show that the PIP PESs run much faster than all other ML methods, whose timings were evaluated in that paper. We also show that the PIP PES extrapolates well enough to describe several internal motions of aspirin, including an OH stretch.

Recent Progress on Conversion of Lignocellulosic Biomass by MOF-Immobilized Enzyme.

The enzyme catalysis conversion of lignocellulosic biomass into valuable chemicals and fuels showed a bright outlook for replacing fossil resources. However, the high cost and easy deactivation of free enzymes restrict the conversion process. Immobilization of enzymes in metal-organic frameworks (MOFs) is one of the most promising strategies due to MOF materials' tunable building units, multiple pore structures, and excellent biocompatibility. Also, MOFs are ideal support materials and could enhance the stability and reusability of enzymes. In this paper, recent progress on the conversion of cellulose, hemicellulose, and lignin by MOF-immobilized enzymes is extensively reviewed. This paper focuses on the immobilized enzyme performances and enzymatic mechanism. Finally, the challenges of the conversion of lignocellulosic biomass by MOF-immobilized enzyme are discussed.

Transcranial direct current stimulation suggests a causal role of the medial prefrontal cortex in learning social hierarchy.

Social hierarchies can be inferred through observational learning of social relationships between individuals. Yet, little is known about the causal role of specific brain regions in learning hierarchies. Here, using transcranial direct current stimulation, we show a causal role of the medial prefrontal cortex (mPFC) in learning social versus non-social hierarchies. In a Training phase, participants acquired knowledge about social and non-social hierarchies by trial and error. During a Test phase, they were presented with two items from hierarchies that were never encountered together, requiring them to make transitive inferences. Anodal stimulation over mPFC impaired social compared with non-social hierarchy learning, and this modulation was influenced by the relative social rank of the members (higher or lower status). Anodal stimulation also impaired transitive inference making, but only during early blocks before learning was established. Together, these findings demonstrate a causal role of the mPFC in learning social ranks by observation.

Clinical and cost-effectiveness of an adapted intervention for preschoolers with moderate to severe intellectual disabilities displaying behaviours that challenge: the EPICC-ID RCT.

Background: Stepping Stones Triple P is an adapted intervention for parents of young children with developmental disabilities who display behaviours that challenge, aiming at teaching positive parenting techniques and promoting a positive parent-child relationship. Objective: To evaluate the clinical and cost-effectiveness of level 4 Stepping Stones Triple P in reducing behaviours that challenge in children with moderate to severe intellectual disabilities. Design, setting, participants: A parallel two-arm pragmatic multisite single-blind randomised controlled trial recruited a total of 261 dyads (parent and child). The children were aged 30-59 months and had moderate to severe intellectual disabilities. Participants were randomised, using a 3 : 2 allocation ratio, into the intervention arm (Stepping Stones Triple P; n = 155) or treatment as usual arm (n = 106). Participants were recruited from four study sites in Blackpool, North and South London and Newcastle. Intervention: Level 4 Stepping Stones Triple P consists of six group sessions and three individual phone or face-to-face contacts over 9 weeks. These were changed to remote sessions after 16 March 2020 due to the coronavirus disease 2019 pandemic. Main outcome measure: The primary outcome measure was the parent-reported Child Behaviour Checklist, which assesses the severity of behaviours that challenge. Results: We found a small non-significant difference in the mean Child Behaviour Checklist scores (-4.23, 95% CI -9.98 to 1.52, p = 0.146) in the intervention arm compared to treatment as usual at 12 months. Per protocol and complier average causal effect sensitivity analyses, which took into consideration the number of sessions attended, showed the Child Behaviour Checklist mean score difference at 12 months was lower in the intervention arm by -10.77 (95% CI -19.12 to -2.42, p = 0.014) and -11.53 (95% CI -26.97 to 3.91, p = 0.143), respectively. The Child Behaviour Checklist mean score difference between participants who were recruited before and after the coronavirus disease 2019 pandemic was estimated as -7.12 (95% CI -13.44 to -0.81) and 7.61 (95% CI -5.43 to 20.64), respectively (p = 0.046), suggesting that any effect pre-pandemic may have reversed during the pandemic. There were no differences in all secondary measures. Stepping Stones Triple P is probably value for money to deliver (-£1057.88; 95% CI -£3218.6 to -£46.67), but decisions to roll this out as an alternative to existing parenting interventions or treatment as usual may be dependent on policymaker willingness to invest in early interventions to reduce behaviours that challenge. Parents reported the intervention boosted their confidence and skills, and the group format enabled them to learn from others and benefit from peer support. There were 20 serious adverse events reported during the study, but none were associated with the intervention. Limitations: There were low attendance rates in the Stepping Stones Triple P arm, as well as the coronavirus disease 2019-related challenges with recruitment and delivery of the intervention. Conclusions: Level 4 Stepping Stones Triple P did not reduce early onset behaviours that challenge in very young children with moderate to severe intellectual disabilities. However, there was an effect on child behaviours for those who received a sufficient dose of the intervention. There is a high probability of Stepping Stones Triple P being at least cost neutral and therefore worth considering as an early therapeutic option given the long-term consequences of behaviours that challenge on people and their social networks. Future work: Further research should investigate the implementation of parenting groups for behaviours that challenge in this population, as well as the optimal mode of delivery to maximise engagement and subsequent outcomes. Study registration: This study is registered as NCT03086876 (https://www.clinicaltrials.gov/ct2/show/NCT03086876?term=Hassiotis±Angela&draw=1&rank=1). Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: HTA 15/162/02) and is published in full in Health Technology Assessment; Vol. 28, No. 6. See the NIHR Funding and Awards website for further award information.

Research shows that in children without learning disabilities, parenting groups which support parents to develop skills to manage behaviours that challenge in their child can be helpful. The National Institute of Health and Care Excellence recommended that more research was needed to strengthen the evidence for such interventions for children with moderate to severe learning disability who are more likely to display behaviours that challenge in England. In this study, we tested in real-world conditions a programme called level 4 Stepping Stones Triple P, which has shown positive results in trials outside of the United Kingdom. Trained therapists delivered six groups and three individual sessions over 9 weeks to parents of children aged 30­59 months with moderate to severe learning disabilities. Two hundred and sixty-one parents were allocated to one of two arms by chance (randomisation): one received Stepping Stones Triple P and treatment as usual and the other treatment as usual only. Treatment as usual included support and advice by general practitioners or community child development teams. Our primary outcome was parent-reported child behaviour at 12 months after randomisation. We also collected data on other outcomes and carried out interviews with parents, service managers and therapists to find out their views about Stepping Stones Triple P. We did not find that Stepping Stones Triple P reduces behaviours that challenge in the child more than treatment as usual at 12 months. However, when we looked at people who received more than half of the sessions, there was a larger reduction in behaviours which suggests that Stepping Stones Triple P works for families if they attend the full programme. Stepping Stones Triple P seems to be good value for money, as we found that at 12 months (covering 10 months of costs), the Stepping Stones Triple P cost £1058 less than treatment as usual from a health and social care perspective. As such, Stepping Stones Triple P is fairly cheap to deliver and a suitable early intervention for behaviours that challenge especially because of positive feedback from parents. Throughout the trial, we included a Parent Advisory Group that oversaw study materials, interview topic guides and promotion of the study.

Formic Acid-Ammonia Heterodimer: A New Δ-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer.

The formic acid-ammonia dimer is an important example of a hydrogen-bonded complex in which a double proton transfer can occur. Its microwave spectrum has recently been reported and rotational constants and quadrupole coupling constants were determined. Calculated estimates of the double-well barrier and the internal barriers to rotation were also reported. Here, we report a full-dimensional potential energy surface (PES) for this complex, using two closely related Δ-machine learning methods to bring it to the CCSD(T) level of accuracy. The PES dissociates smoothly and accurately. Using a 2d quantum model the ground vibrational-state tunneling splitting is estimated to be less than 10-4 cm-1. The dipole moment along the intrinsic reaction coordinate is calculated along with a Mullikan charge analysis and supports the mildly ionic character of the minimum and strongly ionic character at the double-well barrier.

Ab Initio Potential Energy Surface for NaCl-H2 with Correct Long-Range Behavior.

We report a full dimensional ab initio potential energy surface for NaCl-H2 based on precise fitting of a large data set of CCSD(T)/aug-cc-pVTZ energies. A major goal of this fit is to describe the very long-range interaction accurately. This is done in this instance via the dipole-quadrupole interaction. The NaCl dipole and the H2 quadrupole are available through previous works over a large range of internuclear distances. We use these to obtain exact effect charges on each atom. Diffusion Monte Carlo calculations are done for the ground vibrational state using the new potential.

A New A Priori Method to Avoid Calculation of Negligible Hamiltonian Matrix Elements in CI Calculation.

Hamiltonian matrices typically contain many elements that are negligibly small compared to the diagonal elements, even with methods to prune the underlying basis. Because for general potentials the calculation of H-matrix elements is a major part of the computational effort to obtain eigenvalues and eigenfunctions of the Hamiltonian, there is strong motivation to investigate locating these negligible elements without calculating them or at least avoid calculating them. We recently demonstrated an effective means to "learn" negligible elements using machine learning classification (J. Chem. Phys. 2023, 159, 071101). Here we present a simple, new method to avoid calculating them by using a cut-off value for the absolute difference in the quantum numbers for the bra and ket. This method is demonstrated for many of the same case studies as were used in the paper above, namely for realistic H-matrices of H2O, the vinyl radical, C2H3, and glycine, C2H5NO2. The new method is compared to the recently reported machine learning approach. In addition, we point out an important synergy between the two methods.

[Spatiotemporal Evolution and Quantitative Attribution Analysis of Vegetation NDVI in Greater Khingan Mountains Forest-Steppe Ecotone].

It is of great significance to explore the dynamic variations in vegetation cover and to identify its driving factors for the restoration and sustainable development of the regional ecological environment. Based on MODIS NDVI data from 2000 to 2020 and contemporaneous meteorological, DEM, land use type, and other data, the spatiotemporal variation characteristics of vegetation in the Greater Khingan Mountains forest-steppe ecotone were deeply analyzed, and its future evolution pattern was predicted by using the methods of Sen+Mann-Kendall trend analysis and Hurst index. At the same time, the influence degree and mechanism of each detection factor and its interaction on vegetation spatial differentiation at the scale of the whole area and different physical geographic divisions were quantitatively revealed by introducing the GeoDetector model. The results showed that:① In terms of spatiotemporal variation, the spatiotemporal heterogeneity of NDVI in the Greater Khingan Mountains forest-steppe ecotone was obvious from 2000 to 2020. Temporally, NDVI fluctuated growth at a rate of 0.002 a-1 (P < 0.05) and underwent an upward mutation in 2011. Spatially, NDVI showed a distribution pattern of "increasing from southwest to northeast," and the NDVI grade transfer was mainly "medium vegetation cover→medium-high vegetation cover" during the 21 years, and the area of vegetation improvement was much larger than that of degradation. ② In terms of trend prediction, the future variation trend of NDVI in the Greater Khingan Mountains forest-steppe ecotone was mainly continuous improvement, accounting for 37%, but was mostly weakly sustained. ③ In terms of driving mechanism, the wind speed, evaporation, and relative humidity had the most significant influence on the spatial differentiation of NDVI over the whole area. The influence of natural factors has been decreasing over the past 21 years, whereas the influence of human factors has been increasing, and the main driving factors of NDVI spatial differentiation were quite different in different vegetation, climate, soil, and geomorphic zones. The synergistic effect between each factor at different spatial scales all showed two-factor or non-linear enhancement relationships, which was significantly enhanced compared with the single-factor effect. This study contributes to clarifying the causes of ecological fragility in the forest-steppe ecotone in the northern cold region and provides scientific support for formulating differentiated protection and management plans for vegetation resources under different environmental conditions.

Targeting PKM2 improves the gemcitabine sensitivity of intrahepatic cholangiocarcinoma cells via inhibiting ß-catenin signaling pathway.

Gemcitabine is considered the standard first-line chemotherapeutic agent for patients with intrahepatic cholangiocarcinoma (ICC). However, its therapeutic efficacy is hampered by the development of chemoresistance. Pyruvate kinase M2 (PKM2), a crucial mediator of the final step in glycolysis, has been implicated in the origination and advancement of diverse malignancies. Its expression is increased in many tumor types and this may correlate with increased drug sensitivity. However, the specific effect of PKM2 on the gemcitabine sensitivity in ICC remains to be elucidated. In this research, we aimed to elucidate the role and functional significance of PKM2 in ICC, as well as the heightened susceptibility of ICC cells to gemcitabine by targeting PKM2 and the underlying molecular mechanisms. Immunohistochemical and immunofluorescence analyses revealed elevated expression of PKM2 in both tumor cells and macrophages in human ICC tissues. Reducing PKM2 levels significantly restrained the proliferation of tumor cells, impeded cell cycle advance, induced programmed cell death, and suppressed metastasis. In addition, knockdown or pharmacological inhibition of PKM2 could enhance the response of ICC cells to gemcitabine in vitro. Interestingly, conditioned medium co-culture system suggested that conditioned medium from M2 macrophages increased gemcitabine sensitivity of ICC cells. However, silencing PKM2 or pharmacological inhibition of PKM2 in M2 macrophages did not ameliorate the gemcitabine resistance mediated by M2 macrophages derived conditioned medium. Mechanistically, downregulation of PKM2 repressed the expression of ß-catenin and its downstream transcriptional targets, thereby hindering the propagation of ß-catenin signaling cascade. Finally, the results of the subcutaneous xenograft experiment in nude mice provided compelling evidence of a synergistic interaction between PKM2-IN-1 and gemcitabine in vivo. In summary, we reported that PKM2 may function as an advantageous target for increasing the sensitivity of ICC to gemcitabine treatment. Targeting PKM2 improves the gemcitabine sensitivity of ICC cells via inhibiting ß-catenin signaling pathway.

Separation and quantification of tire and road wear particles in road dust samples: Bonded-sulfur as a novel marker.

Tire road wear particles (TRWPs) are a large source of microplastics in the environment, while the quantification of TRWPs is still challenging due to the complex interferences and the uncertainties and inconsistencies among different methods. This study developed a TRWPs quantification method using optimized pretreatments and bonded-sulfur as marker. Road dust samples (n = 48) were collected, pretreatments including density separation, digestion and extraction were optimized to remove interferences of the bonded-sulfur (minerals, sulfur-containing proteins, hydrosoluble/hydrophobic sulfur-containing substances). Presence of TRWPs in the samples was confirmed by microscopy and scanning electron microscopyenergy dispersive spectrometry. Bonded-sulfur in the samples were quantified by inductively coupled plasmamass spectrometry (ICPMS). Additionally, bonded-sulfur in tire wear particles (TWPs) abraded from tires of top 10 best-selling brands were measured to calculate conversion factor (1.1 ×104 µg/g) for the quantification of TRWPs in real samples. TRWPs contents were 5.40 × 104 µg/g11.02 × 104 µg/g and 2.36 × 104 µg/g5.30 × 104 µg/g in samples from heavy and light traffic roads, respectively. The method provided better recoveries (88-107%, n = 18) and repeatability (RSD=2.0-7.9%, n = 3) compared to methods using rubber, benzothiazole and organic zinc as markers. Furthermore, stability of the bonded-sulfur was validated by Raman and ICPMS. Thus, this accurate and stable quantification method could promote research on TRWPs.

Comparative analysis of e-cigarette prevalence and influencing factors among adolescents in Jiangsu Province, China.

Objective: The objectives of this study were to investigate electronic cigarette (e-cigarette) and cigarette use in Jiangsu Province, China, by analyzing the two-year trends of e-cigarette using and to explore the factors influencing the experimentation and use of e-cigarettes. Methods: We conducted a cross-sectional study following the standard methodology of the Global Youth Tobacco Survey in 2019 and 2021. A three-stage cluster sampling design was applied. Eighty-two schools in 14 districts (counties) in Jiangsu Province were surveyed. All computations were performed using the SPSS 21.0 complex samples procedure. Multivariate logistic regression was used to explore the factors influencing e-cigarette experimentation and use. Results: A total of 12,410 and 12,880 students were surveyed in 2019 and 2021, respectively. E-cigarette experimentation increased from 9.34% in 2019 to 13.07% in 2021 (P < 0.001). E-cigarette use increased from 2.23% in 2019 to 3.74% in 2021 (P < 0.001). The main factors associated with e-cigarette use were cigarette experimentation (OR = 2.700, P < 0.001); male gender (OR = 1.416, P = 0.011); junior high school students (OR = 1.551, P = 0.005) and vocational high school students (OR = 1.644, P = 0.001); more pocket money per week (OR1 = 1.214, P = 0.187; OR2 = 1.686, P = 0.001); exposure to second-hand smoke (SHS) at home (OR = 1.239, P < 0.001); exposure to e-cigarette advertising (OR = 1.855, P < 0.001); believe SHS is harmful (OR = 0.933, P = 0.026); closest friends smoking (OR = 2.501, P < 0.001); believe smoking makes youth look more attractive (OR1 = 1.469, P = 0.040; OR2 = 1.305, P = 0.049); believe tobacco helps youth feel more comfortable in social situations (OR1 = 2.161, P < 0.001; OR2 = 1.635, P = 0.001); will use an e-cigarette product if offered by best friends (OR = 1.322, P < 0.001); intend to use an e-cigarette product in the next 12 months (OR = 1.486, P < 0.001). Conclusion: E-cigarette use among adolescents has been on the rise in recent years. E-cigarette use is associated with past cigarette use and a strong desire to smoke. It is crucial to take health education and tobacco control efforts to reduce adolescents' e-cigarette use rate.

Linezolid dose adjustment according to therapeutic drug monitoring helps reach the goal concentration in severe patients, and the oldest seniors benefit more.

BACKGROUND: The elderly with severe infection increased dramatically in intensive care unit (ICU). Proper antimicrobial therapy help improve the prognosis. Linezolid, as an antimicrobial drug, is commonly utilized to treat patients infected with methicillin-resistant S. aureus and vancomycin-resistant enterococci. Clinical evidence suggests elderly patients prone to linezolid overexposure. Here, we describe the results of three years' linezolid adjustment experiences according to therapeutic drug monitoring (TDM), especially in the oldest old. METHODS: Linezolid therapeutic drug monitoring data were collected between January 2020 and November 2022 from patients who were admitted to ICU and treated with linezolid. All the patients started with a dosage of 600 mg, twice daily. The first TMD was carried out ten minutes before the seventh administration. The dosage adjustment was determined by the doctor according to the first TMD and patients' condition, and the repeated TDM was conducted as required. The dosage adjustment in different age group was recorded. Laboratory data were compared between the old and the oldest old. The high mortality risk of the oldest old was also explored. RESULTS: Data of 556 linezolid TDM from 330 patients were collected. Among which, 31.6%, 54.8%, and 75% of patients had supra-therapeutic linezolid trough concentrations at the first TDM assessment in different age group, leading to the dosage adjustment rate of 31.0%, 40.3%, 68.8% respectively. The linezolid dosage adjustments according to TDM help to reach therapeutic concentration. The oldest old was in high risk of linezolid overexposure with lowercreatinine clearance. The norepinephrine maximum dosage but not linezolid Cmin was associated with 28-day mortality in the oldest old. CONCLUSIONS: Elderly patients with linezolid conventional 600 mg twice-daily dose might be at a high risk of overexposure, especially in the oldest old. The linezolid dosage adjustments according to TDM help reach the therapeutic concentration. The high mortality of the oldest old was not related with initial linezolid overexposure.

Clinical characteristics of severe fever with thrombocytopenia syndrome (SFTS) sepsis and non-SFTS sepsis.

Severe fever with thrombocytopenia syndrome (SFTS) is a new infectious disease caused by bunyavirus, and the critically cases conform to the definition of sepsis. In order to compare the differences between SFTS sepsis and non-SFTS sepsis, a retrospective analysis was performed. Thirty-seven SFTS sepsis and 96 non-SFTS sepsis patients were enrolled. The clinical characteristics, laboratory results were compared between the two groups and independent prognostic risk of mortality were investigated respectively. Compared with non-SFTS sepsis, SFTS cases had lower white blood cell, neutrophil and platelet counts, prolonged activated partial thromboplastin time and decreased fibrinogen, slightly elevated inflammatory indicators. Interleukin-6 (IL-6), and acute physiology and chronic health evaluation Ⅱ (APACHE II) score were independent prognostic risk factors in non-SFTS sepsis. The mortality risk of STFS sepsis was related to the viral clearance. There was no difference in viral load between SFTS survivors and non-survivors on admission. However, the differences were significant on 5th, 7th, 10th, and 14th day, and all SFTS non-survivors died within 14 days. Viral clearance rate on 7th day was an independent risk factor for mortality in SFTS sepsis. The mortality risk of STFS sepsis was related to the viral clearance rate.

Indocyanine green clearance test as a predictor of linezolid overexposure in septic patients.

OBJECTIVES: Hepatic impairment increases the risk of drug overexposure in septic patients. However, there is a lack of effective indicators to predict overexposure risk. The indocyanine green (ICG) clearance test is a helpful method for dynamically assessing hepatic function and perfusion. This study aimed to investigate whether the ICG test could serve as a potential predictor of linezolid trough concentration (Cmin) and to compare its efficacy with that of conventional liver function markers. METHODS: A total of 35 consecutive septic patients treated with linezolid were grouped into either linezolid Cmin of ≤7 µg/mL or >7 µg/mL. Correlations between linezolid Cmin and ICG-PDR (plasma disappearance rate), ICG-R15 (retention ratio after 15 min) and other traditional indicators were analysed by Spearman's rank test. A multivariable regression model was employed to discern factors contributing independently to overexposure. RESULTS: Statistical differences were observed between groups for APACHE II score (P = 0.031), SOFA score (P = 0.018), creatinine clearance (CLCr) (P = 0.003), thrombocytes (P = 0.039), lactate (P = 0.003), ICG-PDR (P < 0.001) and ICG-R15 (P < 0.001). Moreover, linezolid Cmin was correlated with ICG-PDR (ρ = -0.628, P < 0.001), ICG-R15 (ρ = 0.676, P < 0.001) and CLCr (ρ = -0.503, P = 0.002). ICG-PDR was identified as an independent predictor of linezolid overexposure, with an optimal cut-off value of 17.70%/min (93.3% sensitivity, 85.0% specificity; P < 0.001). CONCLUSIONS: This pilot clinical trial represents the first investigation of potential of the ICG test to predict linezolid overexposure in septic patients.

A Status Report on "Gold Standard" Machine-Learned Potentials for Water.

Owing to the central importance of water to life as well as its unusual properties, potentials for water have been the subject of extensive research over the past 50 years. Recently, five potentials based on different machine learning approaches have been reported that are at or near the "gold standard" CCSD(T) level of theory. The development of such high-level potentials enables efficient and accurate simulations of water systems using classical and quantum dynamical approaches. This Perspective serves as a status report of these potentials, focusing on their methodology and applications to water systems across different phases. Their performances on the energies of gas phase water clusters, as well as condensed phase structural and dynamical properties, are discussed.

Machine learning classification can significantly reduce the cost of calculating the Hamiltonian matrix in CI calculations.

Hamiltonian matrices in electronic and nuclear contexts are highly computation intensive to calculate, mainly due to the cost for the potential matrix. Typically, these matrices contain many off-diagonal elements that are orders of magnitude smaller than diagonal elements. We illustrate that here for vibrational H-matrices of H2O, C2H3 (vinyl), and C2H5NO2 (glycine) using full-dimensional ab initio-based potential surfaces. We then show that many of these small elements can be replaced by zero with small errors of the resulting full set of eigenvalues, depending on the threshold value for this replacement. As a result of this empirical evidence, we investigate three machine learning approaches to predict the zero elements. This is shown to be successful for these H-matrices after training on a small set of calculated elements. For H-matrices of vinyl and glycine, of order 15 552 and 8828, respectively, training on a percent or so of elements is sufficient to obtain all eigenvalues with a mean absolute error of roughly 2 cm-1.