Nevin Manimala

Br J Cancer. 2023 Dec 14. doi: 10.1038/s41416-023-02514-5. Online ahead of print.

ABSTRACT

BACKGROUND: Platinum-sensitivity is a phenotypic biomarker of Poly (ADP-ribose) polymerase inhibitors (PARPi) sensitivity in histotypes where PARPi are approved. Approximately one-third of non-small cell lung cancers (NSCLC) are platinum-sensitive. The double-blind, randomized phase II PIPSeN (NCT02679963) study evaluated olaparib, a PARPi, as maintenance therapy for patients with platinum-sensitive advanced NSCLC.

METHODS: Chemonaïve patients with ECOG performance status of 0-1, platinum-sensitive, EGFR- and ALK-wild-type, stage IIIB-IV NSCLC were randomized (R) to receive either olaparib (O) maintenance or a placebo (P). The primary objective was progression-free survival (PFS) from R. Secondary objectives included overall survival (OS) and safety. With an anticipated hazard ratio of 0.65, 144 patients were required to be randomized, and approximately 500 patients enrolled.

RESULTS: The trial was prematurely terminated because anti-PD(L)1 therapy was approved during the trial recruitment. A total of 182 patients were enrolled, with 60 patients randomized: 33 and 27 in the O and P arms, respectively. Patient and tumor characteristics were well-balanced between arms, except for alcohol intake (33% vs 11% in the O and P arms, respectively, p = 0.043). The median PFS was 2.9 and 2.0 months in the O and P arms, respectively (logrank p = 0.99). The median OS was 9.4 and 9.5 months in the O and P arms, respectively (p = 0.28). Grade ≥3 toxicities occurred in 15 and 8 patients in O and P arms, with no new safety concerns.

CONCLUSION: PIPSeN was terminated early after enrollment of only 50% of the pre-planned population, thus being statistically underpowered. Olaparib maintenance did neither improve median PFS nor OS in this patient population.

PMID:38097741 | DOI:10.1038/s41416-023-02514-5

Sci Rep. 2023 Dec 14;13(1):22271. doi: 10.1038/s41598-023-49580-6.

ABSTRACT

Retinal prostheses stimulate inner retinal neurons to create visual perception for blind patients. Implanted arrays have many small electrodes. Not all electrodes induce perception at the same stimulus amplitude, requiring clinicians to manually establish a visual perception threshold for each one. Phosphenes created by single-electrode stimuli can also vary in shape, size, and brightness. Computational models provide a tool to predict inter-electrode variability and automate device programming. In this study, we created statistical and patient-specific field-cable models to investigate inter-electrode variability across seven epiretinal prosthesis users. Our statistical analysis revealed that retinal thickness beneath the electrode correlated with perceptual threshold, with a significant fixed effect across participants. Electrode-retina distance and electrode impedance also correlated with perceptual threshold for some participants, but these effects varied by individual. We developed a novel method to construct patient-specific field-cable models from optical coherence tomography images. Predictions with these models significantly correlated with perceptual threshold for 80% of participants. Additionally, we demonstrated that patient-specific field-cable models could predict retinal activity and phosphene size. These computational models could be beneficial for determining optimal stimulation settings in silico, circumventing the trial-and-error testing of a large parameter space in clinic.

PMID:38097732 | DOI:10.1038/s41598-023-49580-6

Prostate Cancer Prostatic Dis. 2023 Dec 14. doi: 10.1038/s41391-023-00775-y. Online ahead of print.

ABSTRACT

BACKGROUND: Darolutamide is an androgen receptor pathway inhibitor (ARPI) used in patients with prostate cancer (PC). In pivotal trials, it has demonstrated a favorable toxicity profile. There are no head-to-head comparison studies between the different ARPIs, but the efficacy of these drugs seems to be similar making the toxicity profile a key element for treatment selection.

METHODS: We conducted a systematic review of all clinical trials assessing treatment with darolutamide for patients with PC using placebo as the control using the PubMed/Medline and Cochrane library databases. We also performed a meta-analysis to compare the safety of darolutamide versus placebo evaluating adverse events (AE) leading to treatment discontinuation and the rate of the AE reported as “AE of interest” in the ARAMIS trial. The comparison among darolutamide and the placebo group in terms of safety and tolerability was performed using odds ratio (OR) as meta-analytic outcome.

RESULTS: We identified three articles comprising 2902 patients for the systematic review and meta-analysis (1652 treated with darolutamide and 1250 with placebo). Darolutamide did not increase AE leading to treatment discontinuation compared to placebo (pooled OR: 1.176, 95% CI 0.918-1.507, p = 0.633). Regarding the “AE of interest” there was no difference between darolutamide and placebo in terms of asthenia, cardiac arrhythmia, cardiac disorder, coronary artery disorder, depression mood disorder, falls, fatigue, heart failure, hot flushes, hypertension, mental-impairment disorder, rash, seizure and weight loss. The only “AE of interest” with a statistically significant difference in favor of placebo was bone fractures (pooled OR: 1.523, 95% CI 1.081-2.146).

CONCLUSIONS: In our systematic review and meta-analysis, darolutamide showed a toxicity profile comparable to placebo with the exception of bone fractures. In the absence of head-to-head comparison studies between the different ARPIs, the results of our research suggest a preferred use of darolutamide in the approved settings.

PMID:38097723 | DOI:10.1038/s41391-023-00775-y

Sci Rep. 2023 Dec 14;13(1):22238. doi: 10.1038/s41598-023-49491-6.

ABSTRACT

The risk of high-temperature-related diseases is increasing owing to global warming. This study aimed to assess the trend of disease burden caused by high temperatures in Mainland China from 1990 to 2019 and to predict the trend of disease burden over the next 10 years. The latest data were downloaded from the Global Burden of Disease Database (GBD) for analysis, and the disease burden related to high temperature was described by mortality and disability-adjusted life-years (DALYs) and stratified by etiology, sex, and age. Statistical analyses were performed using the R software. In 2019, there were 13,907 deaths attributed to high temperatures in Mainland China, and this was 29.55% higher than the 10,735 deaths in 1990. Overall, the age-standardized mortality and DALYs attributed to high temperatures showed a downward trend from 1990 to 2019. We observed an etiological shift in high-temperature-related diseases. The age-standardized DALYs contribution attributed to high temperatures in 1990 was mainly from communicable, maternal, neonatal, and nutritional diseases (CMNND) (21.81/100,000), followed by injury (18.30/100,000) and non-communicable diseases (10.40/100,000). In 2019, the largest contribution shifted to non-communicable diseases (10.07/100,000), followed by injuries (5.21/100,000), and CMNND (2.30/100,000). The disease burden attributed to high temperatures was higher in males than in females and increased with age. In 2030, the mortality rate and DALYs due to high temperatures are predicted to decrease further, and the largest contribution will come from chronic non-communicable diseases, the occurrence of which will remain at a high level over the next 10 years. The burden of disease due to high temperatures in Mainland China is still heavy, mainly due to population aging and an increase in non-communicable diseases.

PMID:38097708 | DOI:10.1038/s41598-023-49491-6

Sci Rep. 2023 Dec 14;13(1):22282. doi: 10.1038/s41598-023-49704-y.

ABSTRACT

The main goals of the Enhanced recovery after surgery (ERAS) protocol are focused on shortening the length of hospital stay (LOS), expediting convalescence, and reducing morbidity. A balanced perioperative fluid therapy is among the significant interventions incorporated by the ERAS protocol. The article contains extensive discussion surrounding the impact of this individual intervention on short-term outcomes. The aim of this study was to assess the impact of perioperative fluid therapy on short-term outcomes in patients after laparoscopic colorectal cancer surgery. The analysis included consecutive patients, who had undergone laparoscopic colorectal cancer operations between 2013 and 2020. Patients were divided into two groups: restricted (≤ 2500 ml) or excessive (> 2500 ml) perioperative fluid therapy. A standardized ERAS protocol was implemented in all patients. The study outcomes included recovery parameters and the morbidity rate, LOS and 30 days readmission rate. There were 361 and 80 patients in groups 1 and 2, respectively. There were no statistically significant differences between the groups in terms of demographic parameters and factors related to the surgical procedure. Logistic regression showed that restricted fluid therapy as a single intervention was associated with improvement in tolerance of diet on 1st postoperative day (OR 2.18, 95% CI 1.31-3.62, p = 0.003), accelerated mobilization on 1st postoperative day (OR 2.43, 95% CI 1.29-4.61, p = 0.006), lower risk of postoperative morbidity (OR 0.58, 95%CI 0.36-0.98, p = 0.046), shorter LOS (OR 0.49, 95% CI 0.29-0.81, p = 0.005) and reduced readmission rate (OR 0.48, 95% CI 0.23-0.98, p = 0.045). A balanced perioperative fluid therapy on the day of surgery may be associated with faster convalescence, lower morbidity rate, shorter LOS and lower 30 days readmission rate.

PMID:38097695 | DOI:10.1038/s41598-023-49704-y

Sci Rep. 2023 Dec 14;13(1):22261. doi: 10.1038/s41598-023-48426-5.

ABSTRACT

Traditional methods for assessing plant health often lack the necessary attributes for continuous and non-destructive monitoring. In this pilot study, we present a novel technique utilizing a customized fiber optic probe based on attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) with a contact force control unit for non-invasive and continuous plant health monitoring. We also developed a normalized difference mid-infrared reflectance index through statistical analysis of spectral features, enabling differentiation of drought and age conditions in plants. Our research aims to characterize phytochemicals and plant endogenous status optically, addressing the need for improved analytical measurement methods for in situ plant health assessment. The probe configuration was optimized with a triple-loop tip and a 3 N contact force, allowing sensitive measurements while minimizing leaf damage. By combining polycrystalline and chalcogenide fiber probes, a comprehensive wavenumber range analysis (4000-900 cm^-1) was achieved. Results revealed significant variations in phytochemical composition among plant species, for example, red spinach with the highest polyphenolic content and green kale with the highest lignin content. Petioles displayed higher lignin and cellulose absorbance values compared to veins. The technique effectively monitored drought stress on potted green bok choy plants in situ, facilitating the quantification of changes in water content, antioxidant activity, lignin, and cellulose levels. This research represents the first demonstration of the potential of fiber optic ATR-FTIR probes for non-invasive and rapid plant health measurements, providing insights into plant health and advancements in quantitative monitoring for indoor farming practices, bioanalytical chemistry, and environmental sciences.

PMID:38097653 | DOI:10.1038/s41598-023-48426-5

Sci Rep. 2023 Dec 14;13(1):22268. doi: 10.1038/s41598-023-48886-9.

ABSTRACT

Amyloid proteins are often associated with the onset of diseases, including Alzheimer’s, Parkinson’s and many others. However, there is a wide class of functional amyloids that are involved in physiological functions, e.g., formation of microbial biofilms or storage of hormones. Recent studies showed that an amyloid fibril could affect the aggregation of another protein, even from a different species. This may result in amplification or attenuation of the aggregation process. Insight into amyloid cross-interactions may be crucial for better understanding of amyloid diseases and the potential influence of microbial amyloids on human proteins. However, due to the demanding nature of the needed experiments, knowledge of such interactions is still limited. Here, we present PACT (Prediction of Amyloid Cross-interaction by Threading) – the computational method for the prediction of amyloid cross-interactions. The method is based on modeling of a heterogeneous fibril formed by two amyloidogenic peptides. The resulting structure is assessed by the structural statistical potential that approximates its plausibility and energetic stability. PACT was developed and first evaluated mostly on data collected in the AmyloGraph database of interacting amyloids and achieved high values of Area Under ROC (AUC=0.88) and F1 (0.82). Then, we applied our method to study the interactions of CsgA – a bacterial biofilm protein that was not used in our in-reference datasets, which is expressed in several bacterial species that inhabit the human intestines – with two human proteins. The study included alpha-synuclein, a human protein that is involved in Parkinson’s disease, and human islet amyloid polypeptide (hIAPP), which is involved in type 2 diabetes. In both cases, PACT predicted the appearance of cross-interactions. Importantly, the method indicated specific regions of the proteins, which were shown to play a central role in both interactions. We experimentally confirmed the novel results of the indicated CsgA fragments interacting with hIAPP based on the kinetic characteristics obtained with the ThT assay. PACT opens the possibility of high-throughput studies of amyloid interactions. Importantly, it can work with fairly long protein fragments, and as a purely physicochemical approach, it relies very little on scarce training data. The tool is available as a web server at https://pact.e-science.pl/pact/ . The local version can be downloaded from https://github.com/KubaWojciechowski/PACT .

PMID:38097650 | DOI:10.1038/s41598-023-48886-9

Sci Rep. 2023 Dec 14;13(1):22240. doi: 10.1038/s41598-023-49544-w.

ABSTRACT

Accurate and in-time prediction of crop yield plays a crucial role in the planning, management, and decision-making processes within the agricultural sector. In this investigation, utilizing area under irrigation (%) as an exogenous variable, we have made an exertion to assess the suitability of different hybrid models such as ARIMAX (Autoregressive Integrated Moving Average with eXogenous Regressor)-TDNN (Time-Delay Neural Network), ARIMAX-NLSVR (Non-Linear Support Vector Regression), ARIMAX-WNN (Wavelet Neural Network), ARIMAX-CNN (Convolutional Neural Network), ARIMAX-RNN (Recurrent Neural Network) and ARIMAX-LSTM (Long Short Term Memory) as compared to their individual counterparts for yield forecasting of major Rabi crops in India. The accuracy of the ARIMA model has also been considered as a benchmark. Empirical outcomes reveal that the ARIMAX-LSTM hybrid modeling combination outperforms all other time series models in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE) values. For these models, an average improvement of RMSE and MAPE values has been observed to be 10.41% and 12.28%, respectively over all other competing models and 15.83% and 18.42%, respectively over the benchmark ARIMA model. The incorporation of the area under irrigation (%) as an exogenous variable in the ARIMAX framework and the inbuilt capability of the LSTM model to process complex non-linear patterns have been observed to significantly enhance the accuracy of forecasting. The performance supremacy of other hybrid models over their individual counterparts has also been evident. The results also suggest avoiding any performance generalization of individual models for their hybrid structures.

PMID:38097613 | DOI:10.1038/s41598-023-49544-w

Transl Psychiatry. 2023 Dec 14;13(1):392. doi: 10.1038/s41398-023-02690-1.

ABSTRACT

Alcohol Use Disorder (AUD) adversely affects the lives of millions of people, but still lacks effective treatment options. Recent advancements in psychedelic research suggest psilocybin to be potentially efficacious for AUD. However, major knowledge gaps remain regarding (1) psilocybin’s general mode of action and (2) AUD-specific alterations of responsivity to psilocybin treatment in the brain that are crucial for treatment development. Here, we conducted a randomized, placebo-controlled crossover pharmaco-fMRI study on psilocybin effects using a translational approach with healthy rats and a rat model of alcohol relapse. Psilocybin effects were quantified with resting-state functional connectivity using data-driven whole-brain global brain connectivity, network-based statistics, graph theory, hypothesis-driven Default Mode Network (DMN)-specific connectivity, and entropy analyses. Results demonstrate that psilocybin induced an acute wide-spread decrease in different functional connectivity domains together with a distinct increase of connectivity between serotonergic core regions and cortical areas. We could further provide translational evidence for psilocybin-induced DMN hypoconnectivity reported in humans. Psilocybin showed an AUD-specific blunting of DMN hypoconnectivity, which strongly correlated to the alcohol relapse intensity and was mainly driven by medial prefrontal regions. In conclusion, our results provide translational validity for acute psilocybin-induced neural effects in the rodent brain. Furthermore, alcohol relapse severity was negatively correlated with neural responsivity to psilocybin treatment. Our data suggest that a clinical standard dose of psilocybin may not be sufficient to treat severe AUD cases; a finding that should be considered for future clinical trials.

PMID:38097569 | DOI:10.1038/s41398-023-02690-1

Nat Commun. 2023 Dec 14;14(1):8328. doi: 10.1038/s41467-023-43168-4.

ABSTRACT

The self-assembly of complex structures from a set of non-identical building blocks is a hallmark of soft matter and biological systems, including protein complexes, colloidal clusters, and DNA-based assemblies. Predicting the dependence of the equilibrium assembly yield on the concentrations and interaction energies of building blocks is highly challenging, owing to the difficulty of computing the entropic contributions to the free energy of the many structures that compete with the ground state configuration. While these calculations yield well known results for spherically symmetric building blocks, they do not hold when the building blocks have internal rotational degrees of freedom. Here we present an approach for solving this problem that works with arbitrary building blocks, including proteins with known structure and complex colloidal building blocks. Our algorithm combines classical statistical mechanics with recently developed computational tools for automatic differentiation. Automatic differentiation allows efficient evaluation of equilibrium averages over configurations that would otherwise be intractable. We demonstrate the validity of our framework by comparison to molecular dynamics simulations of simple examples, and apply it to calculate the yield curves for known protein complexes and for the assembly of colloidal shells.

PMID:38097568 | DOI:10.1038/s41467-023-43168-4