A programmable targeted protein-degradation platform for versatile applications in mammalian cells and mice.

Myriad physiological and pathogenic processes are governed by protein levels and modifications. Controlled protein activity perturbation is essential to studying protein function in cells and animals. Based on Trim-Away technology, we screened for truncation variants of E3 ubiquitinase Trim21 with elevated efficiency (ΔTrim21) and developed multiple ΔTrim21-based targeted protein-degradation systems (ΔTrim-TPD) that can be transfected into host cells. Three ΔTrim-TPD variants are developed to enable chemical and light-triggered programmable activation of TPD in cells and animals. Specifically, we used ΔTrim-TPD for (1) red-light-triggered inhibition of HSV-1 virus proliferation by degrading the packaging protein gD, (2) for chemical-triggered control of the activity of Cas9/dCas9 protein for gene editing, and (3) for blue-light-triggered degradation of two tumor-associated proteins for spatiotemporal inhibition of melanoma tumor growth in mice. Our study demonstrates that multiple ΔTrim21-based controllable TPD systems provide powerful tools for basic biology research and highlight their potential biomedical applications.

Association of sarcopenia with severe chemotherapy toxicities and survival in patients with advanced gastric cancer.

BACKGROUND: Sarcopenia or skeletal muscle depletion is a poor prognostic factor for gastric cancer (GC). However, existing cutoff values of skeletal muscle index (SMI) for defining sarcopenia have been found to have limitations when clinically applied. This study aimed to determine the optimal cutoff for SMI to predict severe toxicities of chemotherapy and overall survival (OS) in patients with advanced GC. METHODS: Patients with metastatic gastric adenocarcinoma who received first-line palliative chemotherapy between January 2014 and December 2021 at Queen Mary Hospital, Hong Kong, were included in this study. The SMI was determined via a pre-chemotherapy computed tomography scan. Optimal cutoff points of SMI were identified by recursive partitioning analysis. Univariate and multivariate analyses evaluating risk factors of severe chemotherapy toxicities and OS were also performed. RESULTS: A total of 158 patients (male: 108 (68.4%), median age: 65.3) were included. The SMI cutoff to define low SMI was ≤33 cm2/m2 for males and ≤28 cm2/m2 for females; 30 patients (19.0%) had low SMI. Patients with low SMI had a higher incidence of hematological toxicities (63.3% vs 32.0%, P = .001) and non-hematological toxicities (66.7% vs 36.7%, P = .003). Multivariable analysis indicated that low SMI and low serum albumin (≤28 g/L) were independent predictive factors of hematological toxicity, while low SMI and neutrophil-lymphocyte ratio ≥5 were predictive factors of non-hematological toxicity. Moreover, patients with low SMI had a significantly shorter OS (P = .011), lower response rate to chemotherapy (P = .045), and lower utilization of subsequent lines of treatment (P < .001). CONCLUSIONS: Using pre-chemotherapy SMI cutoff (≤33 cm2/m2 for males and 28 cm2/m2 for females) one can identify individuals with a higher risk of severe chemotherapy toxicities and worse prognosis.

Prospective validation of the role of PET/CT in detecting disease after neoadjuvant chemotherapy in advanced ovarian cancer.

OBJECTIVES: The study aimed to compare the diagnostic accuracies of 2-[18F]FDG PET/CT and contrast-enhanced CT (ceCT) after neoadjuvant chemotherapy (NACT) in advanced ovarian cancer (OC). MATERIALS AND METHODS: This study consisted historical observational cohort and prospective validation cohort. Patients with newly diagnosed stage III-IV OC scheduled for NACT were recruited, with imaging performed after three to six cycles of NACT before interval debulking surgery. Nineteen regions in the abdominopelvic cavity were scored for the presence and absence of disease, referenced to the intra-operative findings or histological specimens. Diagnostic metrics were compared using McNemar's test. RESULTS: In the historical cohort (23 patients, age 58 ± 13), 2-[18F]FDG PET had an overall accuracy (Acc) 82%, sensitivity (Sen) 38%, specificity (Spe) 97%, positive predictive value (PPV) 79% and negative predictive value (NPV) 82%; ceCT had an overall Acc 86%, Sen 64%, Spe 93%, PPV 75% and NPV 89%. In the prospective cohort (46 patients, age 59 ± 9), 2-[18F] FDG PET had an overall Acc 87%, Sen 48%, Spe 98%, PPV 84% and NPV 88%; ceCT had an overall Acc 89%, Sen 66%, Spe 95%, PPV 77% and NPV 91%. No significant difference was demonstrated between the two imaging modalities (p > 0.05). High false-negative rates were observed in the right subdiaphragmatic space, omentum, bowel mesentery and serosa. High omental metabolic uptake after NACT was associated with histological non-responders (p < 0.05). CONCLUSION: 2-[18F]FDG PET/CT had no additional value over ceCT with comparable diagnostic accuracy in detecting disease after NACT in advanced OC. CLINICAL RELEVANCE STATEMENT: 2-[18F]FDG PET/CT is not superior to contrast-enhanced CT in determining disease after neoadjuvant chemotherapy in advanced ovarian cancer; contrast-enhanced CT should be suffice for surgical planning before interval debulking surgery. KEY POINTS: • Additional value of 2-[18F]FDG PET/CT over contrast-enhanced CT is undefined in detecting disease after neoadjuvant chemotherapy. • 2-[18F]FDG PET/CT has comparable diagnostic accuracy compared to contrast-enhanced CT. • Contrast-enhanced CT will be suffice for surgical planning after neoadjuvant chemotherapy.

Evaluating the Diagnostic Performance of Large Language Models on Complex Multimodal Medical Cases.

Large language models showed interpretative reasoning in solving diagnostically challenging medical cases.

An integrated simulation-optimization approach for combined allocation of water quantity and quality under multiple uncertainties.

Multiple uncertainties such as water quality processes, streamflow randomness affected by climate change, indicators' interrelation, and socio-economic development have brought significant risks in managing water quantity and quality (WQQ) for river basins. This research developed an integrated simulation-optimization modeling approach (ISMA) to tackle multiple uncertainties simultaneously. This approach combined water quality analysis simulation programming, Markov-Chain, generalized likelihood uncertainty estimation, and interval two-stage left-hand-side chance-constrained joint-probabilistic programming into an integration nonlinear modeling framework. A case study of multiple water intake projects in the Downstream and Delta of Dongjiang River Basin was used to demonstrate the proposed model. Results reveal that ISMA helps predict the trend of water quality changes and quantitatively analyze the interaction between WQQ. As the joint probability level increases, under strict water quality scenario system benefits would increase [3.23, 5.90] × 109 Yuan, comprehensive water scarcity based on quantity and quality would decrease [782.24, 945.82] × 106 m3, with an increase in water allocation and a decrease in pollutant generation. Compared to the deterministic and water quantity model, it allocates water efficiently and quantifies more economic losses and water scarcity. Therefore, this research has significant implications for improving water quality in basins, balancing the benefits and risks of water quality violations, and stabilizing socio-economic development.

Study on the habitat evolution after dam removal in a habitat-alternative tributary of large hydropower station.

The establishment of large hydropower stations in the main stream poses a threat to fish habitats. Selecting suitable tributaries as alternative habitats is a practical measure for ecological environment protection during large hydropower station's construction. The small dams constructed on certain tributaries need to be removed in order to restore river connectivity. The removal of dams will activate hydro-sedimentary dynamics and change the original habitat in terms of topography and hydrodynamics. To explore the evolution of fish habitats following the removal of small dams, a dam-removed reach of a habitat-alternative tributary was selected as the research object, and the model of water-sediment transport and riverbed evolution in strongly disturbed dam-removed reaches and the model of fish habitat suitability evaluation were established. The key parameters calibration and model verification were completed by field monitoring results. The simulation results showed dramatic evolution in the reservoir riverbed in the initial stage after dam removal and during the high discharge period. One year after dam removal, there was a noticeable 4.0 m incision in front of the dam, along with a decrease in channel slope at the dam site from about 4.8% to approximately 1.5%. Downstream of the dam, alterations to the riverbed were mainly concentrated near the dam, and sedimentary bodies with a height of around 2.0 m have formed on the left bank following the high discharge period. The fish habitat in most areas of the dam-removed reach was suitable, except for the downstream high-velocity area. To compare the evolution process of fish habitat under two dam removal periods in wet and dry seasons, two dam removal schemes were implemented in March and June. The results showed that the riverbed evolved more gradually in the March scheme, creating a larger and continuous suitable habitat for fish. Therefore, the March scheme was recommended. By revealing the evolutionary pattern of fish habitat after dam removal, this research provides a reliable model for assessing and restoring habitats in dam-removed reaches, and enjoys significant implications for protecting river ecology in hydropower development reaches.

A unified deep learning framework for water quality prediction based on time-frequency feature extraction and data feature enhancement.

Deep learning methods exhibited significant advantages in mapping highly nonlinear relationships with acceptable computational speed, and have been widely used to predict water quality. However, various model selection and construction methods resulted in differences in prediction accuracy and performance. Hence, a unified deep learning framework for water quality prediction was established in the paper, including data processing module, feature enhancement module, and data prediction module. In the established model, the data processing module based on wavelet transform method was applied to decomposing complex nonlinear meteorology, hydrology, and water quality data into multiple frequency domain signals for extracting self characteristics of data cyclic and fluctuations. The feature enhancement module based on Informer Encoder was used to enhance feature encoding of time series data in different frequency domains to discover global time dependent features of variables. Finally, the data prediction module based on the stacked bidirectional long and short term memory network (SBiLSTM) method was employed to strengthen the local correlation of feature sequences and predict the water quality. The established model framework was applied in Lijiang River in Guilin, China. The maximum relative errors between the predicted and observed values for dissolved oxygen (DO), chemical oxygen demand (CODMn) were 12.4% and 20.7%, suggesting a satisfactory prediction performance of the established model. The validation results showed that the established model was superior to all other models in terms of prediction accuracy with RMSE values 0.329, 0.121, MAE values 0.217, 0.057, SMAPE values 0.022, 0.063 for DO and CODMn, respectively. Ablation tests confirmed the necessity and rationality of each module for the established model framework. The established method provided a unified deep learning framework for water quality prediction.

Periodic inundation accelerates the release process of organic carbon from plant litter.

The total organic carbon (OC) from plant litter in riparian zones is an important nutrient source for aquatic organisms and plays a crucial role in the nutrient cycling of river ecosystems. Nevertheless, the total amount of OC in dammed rivers gradually decreases, and the restoration methods are rarely researched. A hypothesis was proposed that the periodic inundation altered the process of OC release from plant litter. To explore the impact of periodic inundation on OC release from litter in the riparian zone, litter bags in situ tests were conducted in the Yalong River. Three inundation treatments were conducted for the test samples, which were NS (never submerged by water), PIS (periodic submerged), and PMS (permanent submerged). Results indicated that the amount of OC released from litters in PIS treatment was about 1.1 times that in PMS treatment, and about 2.1 times that in NS treatment. The average release rate coefficient k of PIS treatment (at mean water level) was the highest (12.8 × 10-4 d-1), followed by PMS treatment (11.0 × 10-4 d-1), and NS treatment (5.6 × 10-4 d-1), which demonstrated that the periodic inundation was critical for OC release. The mean water level was a demarcation line where there was a significant difference in the release of OC in the riparian zone (p < 0.05). Flow velocity alone could account for 84% of the variation in OC release rate, while the flow velocity and inundation duration together could achieve an explanatory degree of 86%. This research can provide a valuable scientific basis for the protection and restoration of river ecosystems, especially for the recovery of OC concentration in dammed rivers.

An improved approach for evaluating landscape ecological risks and exploring its coupling coordination with ecosystem services.

The rapid urbanization has accelerated the destruction of regional ecosystems, triggering ecological risks and threatening sustainable development. Landscape ecological risk (LER) evaluation is an effective tool to mitigate such negative impacts. However, the existing evaluation systems exhibit certain subjectivity. Therefore, an improved LER evaluation method was proposed, which incorporates ecosystem services (ESs) to characterize landscape vulnerability. The method was validated using the Pearl River Delta urban agglomeration (PRDUA) as the study area. The results showed that the optimal grain size and extent for landscape pattern analysis in the PRDUA were determined to be 150 m and 6km × 6 km, respectively. The comparison results with the traditional LER evaluation method demonstrated the improved method's superior rationality and reliability. The hotspot analysis based on the Getis-Ord Gi* method revealed that the hotspots of LER were mainly concentrated in the densely populated areas of the south-central region of the PRDUA. The coupling coordination degree (CCD) between LERs and ESs showed four different levels of development in both temporal and spatial dimensions, generally dominated by moderately balanced development and lagging ESs, reflecting the unbalanced ecological environment and socio-economic development of the PRDUA. It is recommended that the ecosystems in the PRDUA be managed and protected separately according to the delineated Ecological Protection Area (EPA), Urban Built-up Area (UBA), and Urban Ecological Boundary Area (UEBA). This study can provide an important reference for regional ecosystem conservation and management.

Presence of tumour capsule on contrast-enhanced CT is associated with improved outcomes of stereotactic body radiation therapy in hepatocellular carcinoma patients.

PURPOSE: Stereotactic body radiation therapy (SBRT) is a novel local therapy for the treatment of hepatocellular carcinoma (HCC). While effective, there is currently no reliable radiological marker to guide patient selection. In this study, we investigated the prognostic value of capsule appearance on contrast-enhanced computed tomography (CT) for patients undergoing SBRT. MATERIALS AND METHODS: Between 2006 and 2017, 156 consecutive patients with Child-Pugh score class A/B and HCC ≥ 5 cm who underwent SBRT were retrospectively analysed. Baseline triple-phase CTs of the abdomen were reviewed for the presence of capsule appearances and correlated with objective response rate (ORR), overall survival (OS) and pattern of treatment failure. RESULTS: Capsule appearance on CT was present in 83 (53.2%) patients. It was associated with improved ORR by Response Evaluation Criteria in Solid Tumours (RECIST) (60.2 vs. 24.7%, p < 0.001) and Modified Response Evaluation Criteria in Solid Tumours (mRECIST) (78.3 vs. 34.2%, p < 0.001). The presence of a capsule was also associated with superior 2­year local control (89.1 vs. 51.4%, p < 0.001) and 2­year OS (34.1 vs. 14.8%, p < 0.01). Hepatic out-field failure was the dominant mode of progression, which was less common in patients with intact capsule (54.2 vs. 60.3%, p = 0.01). CONCLUSION: Capsule appearance on CT could potentially be a non-invasive prognostic marker for selecting HCC patients to undergo SBRT. A larger cohort is warranted to validate our findings.