Derivation and validation of a novel preoperative risk prediction model for surgical site infection in pancreaticoduodenectomy and comparison of preoperative antibiotics with different risk stratifications in retrospective cohort

BACKGROUND

Surgical site infections (SSIs) are common postoperative complications of pancreaticoduodenectomy.

AIM

To develop a model for preoperative identification of the risk of SSI that may improve outcomes and guide preoperative antibiotics.

METHODS

The prediction model was built by meta-analysis. After literature search and inclusion, data extraction, and quantitative synthesis, the prediction model was established based on the pooled odds ratio of predictors. A single-centre retrospective cohort was the validation cohort. Receiver operating characteristic curves and area under the curve were used to assess the model's ability. We also created a decision curve and a calibration plot to assess the nomogram. The effects of prophylactic antibiotics on SSI were compared between groups by multivariable logistic regression with different risk stratifications.

FINDINGS

Twenty-eight studies were included in the meta-analysis, 17 studies in the derivation cohort. Age, male gender, body mass index, pancreatic duct diameter, high-risk diagnosis, and preoperative biliary drainage were selected to build the prediction model. The model was validated in an external cohort. The cut-off value was 3.5 and area under the curve (AUC) was 0.76 in open pancreaticoduodenectomy (OPD). In laparoscopic pancreaticoduodenectomy, the cut-off value was 4.5 and AUC was 0.69. Decision curve and calibration plot showed good usability of the model, especially in OPD. Multivariable logistic regression did not indicate differences between broad- and narrow-spectrum antibiotics for SSI in different risk stratifications.

CONCLUSION

The model can identify patients with a high risk of SSI preoperatively. The choice of prophylactic antibiotics under different risk stratifications should be investigated further.

Clinical standards for drug-susceptible TB in children and adolescents

BACKGROUND: These clinical standards aim to provide guidance for diagnosis, treatment, and management of drug-susceptible TB in children and adolescents.METHODS: Fifty-two global experts in paediatric TB participated in a Delphi consensus process. After eight rounds of revisions, 51/52 (98%) participants endorsed the final document.RESULTS: Eight standards were identified: Standard 1, Age and developmental stage are critical considerations in the assessment and management of TB; Standard 2, Children and adolescents with symptoms and signs of TB disease should undergo prompt evaluation, and diagnosis and treatment initiation should not depend on microbiological confirmation; Standard 3, Treatment initiation is particularly urgent in children and adolescents with presumptive TB meningitis and disseminated (miliary) TB; Standard 4, Children and adolescents should be treated with an appropriate weight-based regimen; Standard 5, Treating TB infection (TBI) is important to prevent disease; Standard 6, Children and adolescents should receive home-based/community-based treatment support whenever possible; Standard 7, Children, adolescents, and their families should be provided age-appropriate support to optimise engagement in care and clinical outcomes; and Standard 8, Case reporting and contact tracing should be conducted for each child and adolescent.CONCLUSION: These consensus-based clinical standards, which should be adapted to local contexts, will improve the care of children and adolescents affected by TB.

Simple method for visual detection of nitrite using fluorescence and colorimetry by poly (tannic acid) nanoparticles

The nitration reaction of nitrite and phenolic substances was first used to identify and detect NO₂^- by taking fluorescent poly (tannic acid) nanoparticles (FPTA NPs) as sensing platform. With the low cost, good biodegradable and convenient water-soluble FPTA NPs, a fluorescent and colorimetric dual modes detecting assay was realized. In fluorescent mode, the linear detection range of NO₂^- was 0-36 μM, the LOD was as low as 3.03 nM, and the response time was 90 s. In colorimetric mode, the linear detection range of NO₂^- was 0-46 μM, and the LOD was as low as 27 nM. Besides, a smartphone with FPTA NPs@ agarose hydrogel formed a portable detection platform to test the fluorescent and visible color changes of FPTA NPs for NO₂^- sensing as well as for accurate visualization and quantitative detection of NO₂^- in actual water and food samples.

Organophosphate Level Evaluation for the Poisoning Treatment by Enzyme Activation Regeneration Strategy with Oxime-Functionalized ZIF-8 Nanoparticles

In this work, two nanometal-organic frameworks (NMOFs) of ZIF-8-1 and ZIF-8-2 were designed and synthesized with a "missing linker" defects strategy by using Oxime-1 and Oxime-2 as coligands, respectively. ZIF-8-2 exhibited an excellent performance in comparison to that of ZIF-8-1 in activating and regenerating the activity of BChE suppressed by demeton-S-methyl (DSM) and could rapidly detoxify DSM in poisoned serum samples within 24 min. Additionally, the synthesized fluorescence probe of IND-BChE with high quantum yields, large Stokes shifts, and superior water solubility could be used for the detection of both butyrylcholinesterase (BChE) and DSM in a lower LOD of 0.63 mU/mL (BChE) and 0.086 μg/mL (DSM). By the difference in fluorescent intensity of IND-BChE with and without ZIF-8-2, a highly linear relationship of IND-BChE with DSM concentration was found (R² = 0.9889), and the LOD was 0.073 μg/mL. In addition, an intelligent detection platform of ZIF-8-2@IND-BChE@agarose hydrogel combined with a smartphone formed a point-of-care test for DSM -poisoned serum samples and also realized satisfactory results. Unlike other detection methods of nerve agents, this assay first combined an NMOF reactivator for detoxification and detection of BChE enzyme activity and then quantification of OP nerve agents, which was of great significance in treatment of organophosphate poisoning.

Inhibition of YAP1 activity ameliorates acute lung injury through promotion of M2 macrophage polarization

The balance of M1/M2 macrophage polarization plays an important role in regulating inflammation during acute lung injury (ALI). Yes-associated protein (YAP1) is a key protein in the Hippo-YAP1 signaling pathway and is involved in macrophage polarization. We aimed to determine the role of YAP1 in pulmonary inflammation following ALI and regulation of M1/M2 polarization. Pulmonary inflammation and injury with upregulation of YAP1 were observed in lipopolysaccharide (LPS)-induced ALI. The YAP1 inhibitor, verteporfin, attenuated pulmonary inflammation and improved lung function in ALI mice. Moreover, verteporfin promoted M2 polarization and inhibited M1 polarization in the lung tissues of ALI mice and LPS-treated bone marrow-derived macrophages (BMMs). Additionally, siRNA knockdown confirmed that silencing Yap1 decreased chemokine ligand 2 (CCL2) expression and promoted M2 polarization, whereas silencing large tumor suppressor 1 (Lats1) increased CCL2 expression and induced M1 polarization in LPS-treated BMMs. To investigate the role of inflammatory macrophages in ALI mice, we performed single-cell RNA sequencing of macrophages isolated from the lungs. Thus, verteporfin could activate the immune-inflammatory response, promote the potential of M2 macrophages, and alleviate LPS-induced ALI. Our results reveal a novel mechanism where YAP1-mediated M2 polarization alleviates ALI. Therefore, inhibition of YAP1 may be a target for the treatment of ALI.

Baicalin inhibits pressure overload-induced cardiac hypertrophy by regulating the SIRT3-dependent signaling pathway

BACKGROUND

The conserved sirtuin protein sirtuin 3 (SIRT3) is a vital protective protein for cardiac hypertrophy. Inhibition of SIRT3 accelerated the development of heart hypertrophy. On the other hand, myocardial hypertrophy was prevented by overexpressing SIRT3. SIRT3 has been proposed as a potential therapeutic target for managing or averting heart hypertrophy. Baicalin, a flavonoid extracted from the Scutellaria baicalensis plant, has anti-cardiovascular properties, including protection against cardiac hypertrophy. However, the molecular mechanism of the anti-hypertrophic effect of baicalin is not well known.

PURPOSE

In this study, we aim to investigate the effect of baicalin on cardiac hypertrophy and explored its underlying molecular mechanisms.

STUDY-DESIGN/METHODS

Abdominal aortic constriction (AAC)-induced mouse cardiac hypertrophy and angiotensin II (Ang II)-induced cardiomyocyte hypertrophy models were established. After baicalin treatment, cardiac hypertrophy was monitored by detecting the expression of hypertrophic genes and cell surface area. Echocardiogram was performed to check the heart function in vivo. Moreover, the protein expression of the SIRT3-dependent pathway was detected by Western blotting.

RESULTS

In this work, we demonstrated that baicalin might suppress the cell surface area and the expression of the Ang II -induced myosin heavy chain β (β-MHC), brain natriuretic polypeptide (BNP), and atrial natriuretic factor (ANF). Additionally, it reduced the AAC rats' hypertrophic impact. We also found that baicalin prevents cardiac hypertrophy by regulating SIRT3/LKB1/AMPK signaling pathway. Moreover, we showed that baicalin upregulated the SIRT3 protein expression by inhibiting proteasome and by the activation of 20 S proteasome subunit beta type-5 (PSMB5).

CONCLUSION

These results offer the first proof that baicalin inhibits cardiac hypertrophy due to its effect on the SIRT3-dependent signaling pathway, indicating its potential for treating cardiac hypertrophy and heart failure. The present study provides a preliminary experimental basis for the clinical application of baicalin and baicalin-like compounds.

Modeling regional nitrogen cycle in the atmosphere: Present situation and its response to the future emissions control strategy

Reactive nitrogen (Nr) cycle in the atmosphere has an important affection on terrestrial ecosystems, which has not been fully understood and its response to the future emissions control strategy is not clear. Taking the Yangtze River Delta (YRD) as an example, we explored the regional Nr cycle (emissions, concentrations, and depositions) and its source apportionment in the atmosphere in January (winter) and July (summer) 2015 and projected its changes under emissions control by 2030 using the CMAQ model. We examined the characteristics of Nr cycle and found that Nr suspends in the air mainly as NO, NO₂, and NH₃ gases and deposits to the earth's surface mainly as HNO₃, NH₃, NO₃^-, and NH₄⁺. Due to the higher NO_x than NH₃ emissions, oxidized nitrogen (OXN) but not reduced nitrogen (RDN) is the major component in Nr concentration and deposition, especially in January. Nr concentration and deposition show an inverse correlation, with a high concentration in January and low in July but the opposite for deposition. We further apportioned the regional Nr sources for both concentration and deposition using the Integrated Source Apportionment Method (ISAM) incorporated in the CMAQ model. It shows that local emissions are the major contributors and this characteristic is more significant in concentration than deposition, for RDN than OXN species, and in July than in January. The contribution from North China (NC) is important for Nr in YRD, especially in January. In addition, we revealed the response of Nr concentration and deposition to the emission control to achieve the target of carbon peak in the year 2030. After the emission reduction, the relative responses of OXN concentration and deposition are generally about 100 % to the reduction of NO_x emissions (~50 %), while the relative responses of RDN concentration are higher than 100 % and the relative responses of RDN deposition are significantly lower than 100 % to the reduction of NH₃ emissions (~22 %). Consequently, RDN will become the major component in Nr deposition. The smaller reduction of RDN wet deposition than sulfur wet deposition and OXN wet deposition will raise the pH of precipitation and help alleviate the acid rain problem, especially in July.

Self-Consistent Quantum Mechanics/Embedded Charge Study on Aggregation-Enhanced Delayed Fluorescence of Cu(I) Complexes: Luminescence Mechanism and Molecular Design Strategy

To elucidate the luminescence mechanism of highly efficient blue Cu(N^N)(POP)⁺-type thermally activated delayed fluorescence (TADF) materials, we have selected Cu(pytfmpz)(POP)⁺ (1) and Cu(pympz)(POP)⁺ (2) as targets to investigate the photophysical properties in both solution and solid phases. The self-consistent electrostatic potential (ESP) embedded charge within the quantum mechanics/molecular mechanics (QM/MM) method demonstrates a greater advantage over the charge equilibrium (QEQ) in accurately calculating atomic charges and reasonably describing the polarization effect, ultimately resulting in a favorable consistency between simulation and experimental measurements. After systematic and quantitative simulation, it has been found that complex 2, with an electron-donating group of -CH₃, exhibits a much more blue-shifted spectrum and a significantly enhanced efficiency in comparison to complex 1 with -CF₃. This is due to the widened HOMO-LUMO gap as well as the narrowed energy gap between the lowest singlet and triplet excited states (ΔE_ST), respectively. Then, the designed complex 3 is introduced with a stronger electron donor and larger tert-butyl group, which plays a key role in simultaneously suppressing the structural distortion and reducing the ΔE_ST. This leads to a faster reverse intersystem crossing process than that of the two experimental complexes in solution, turning out to be a new deep-blue-emitting material with excellent TADF performance.

Construction and validation of a prognostic prediction model for gastric cancer using a series of genes related to lactate metabolism

Background

Gastric cancer (GC) is one of the most common clinical malignant tumors worldwide, with high morbidity and mortality. The commonly used tumor-node-metastasis (TNM) staging and some common biomarkers have a certain value in predicting the prognosis of GC patients, but they gradually fail to meet the clinical demands. Therefore, we aim to construct a prognostic prediction model for GC patients.

Methods

A total of 350 cases were included in the STAD (Stomach adenocarcinoma) entire cohort of TCGA (The Cancer Genome Atlas), including the STAD training cohort of TCGA (n = 176) and the STAD testing cohort of TCGA (n = 174). GSE15459 (n = 191), and GSE62254 (n = 300) were for external validation.

Results

Through differential expression analysis and univariate Cox regression analysis in the STAD training cohort of TCGA, we screened out five genes among 600 genes related to lactate metabolism for the construction of our prognostic prediction model. The internal and external validations showed the same result, that is, patients with higher risk score were associated with poor prognosis (all p < 0.05), and our model works well without regard of patients' age, gender, tumor grade, clinical stage or TNM stage, which supports the availability, validity and stability of our model. Gene function analysis, tumor-infiltrating immune cells analysis, tumor microenvironment analysis and clinical treatment exploration were performed to improve the practicability of the model, and hope to provide a new basis for more in-depth study of the molecular mechanism for GC and for clinicians to formulate more reasonable and individualized treatment plans.

Conclusions

We screened out and used five genes related to lactate metabolism to develop a prognostic prediction model for GC patients. The prediction performance of the model is confirmed by a series of bioinformatics and statistical analysis.

[Diagnosis and treatment of finger flexion contracture caused by forearm flexor disease]

Objective

To summarize the clinical characteristics, differential diagnosis, and treatment methods of finger flexion contracture caused by three kinds of forearm flexor diseases.

Methods

Between December 2008 and August 2021, 17 patients with finger flexion contracture were treated, including 8 males and 9 females, aged 5-42 years, with a median of 16 years. The disease duration ranged from 1.5 months to 30 years, with a median of 13 years. The etiology included 6 cases of Volkmann's contracture, all of which were flexion deformity of the 2nd to 5th fingers, accompanied by limitation of thumb dorsiflexion in 3 cases and limitation of wrist dorsiflexion in 3 cases; 3 cases of pseudo-Volkmann's contracture, including 2 cases of flexion deformity of middle, ring, and little fingers, and 1 case of flexion deformity of ring and little fingers; 8 cases of ulnar finger flexion contracture caused by forearm flexor disease or anatomical variations, all of which were flexion deformity of middle, ring, and little fingers. Operations such as slide of flexor and pronator teres origin, excision of abnormal fibrous cord and bony prominence, and release of entrapped muscle (tendon) were performed. Hand function was evaluated according to WANG Haihua's hand function rating standard or modified Buck-Gramcko classification standard, and muscle strength was evaluated according to British Medical Research Council (MRC) muscle strength rating standard.

Results

All patients were followed up 1-10 years (median, 1.5 years). At last follow-up, 8 patients with contracture caused by forearm flexor disease or anatomical variations and 3 patients with pseudo-Volkmann's contracture achieved excellent hand function, with muscle strength of grade M5 in 6 cases and grade M4 in 5 cases. One patient with mild Volkmann's contracture and 3 patients with moderate Volkmann's contracture without severe nerve damage had excellent hand function in 2 cases and good in 2 cases, with muscle strength of grade M5 in 1 case and grade M4 in 3 cases. Two patients with moderate or severe Volkmann's contracture had poor hand function, with 1 case of muscle strength of grade M3 and 1 case of grade M2, which improved when compared with those before operation. The overall excellent and good rate of hand function and the proportion of patients with muscle strength of grade M4 and above were 88.2% (15/17), respectively.

Conclusion

The finger flexion contracture caused by different etiology can be differentiated by analyzing the history, physical examination, radiographs, and intraoperative findings. After different surgical treatments, such as resection of contracture band, release of compressed muscle (tendon), and downward movement of flexor origin, most patients have a good outcome.

Single-cell sequencing of PIT1-positive pituitary adenoma highlights the pro-tumour microenvironment mediated by IFN-γ-induced tumour-associated fibroblasts remodelling

BACKGROUND

PIT1-positive pituitary adenoma (PIT1-PA) is one of the most important lineages of pituitary adenoma (PA), which causes systematic endocrine disorders and a worse prognosis. Tumour-associated fibroblast (TAF) is a crucial stroma cell type in the tumour microenvironment (TME). However, cellular and functional heterogeneity of TAF and immune cells in PIT1-PA have not been fully investigated.

METHODS

By single-cell RNA sequencing of four PIT1-PAs and further analyses, we characterised the molecular and functional profiles of 28 different cell subtypes.

RESULTS

PA stem cells in PIT1/SF1-positve PA were in a hybrid epithelial/mesenchymal state, and differentiated along the PIT1- and SF- dependent branches. C1Q was overwhelmingly expressed in tumour-associated macrophages, indicating its pro-tumoral functionality. PIT1-PA progression was characterised by lower cell-cell communication strength and higher cell adhesion-associated signals, indicating the immunosuppressive but pro-invasive microenvironment. IFN-γ signal repressed functional remodelling of myofibroblastic TAF (mTAF) towards inflammatory TAF/antigen-presenting TAF. IFN-γ inhibited mTAF phenotypes and N-cadherin expression through STAT3 signal axis. CDH2 knockdown in TAFs abrogated their pro-tumour function in PAs.

CONCLUSIONS

Our study builds up a cellular landscape of PIT1-PA TME and highlights anti-tumour function of IFN-γ mediated TAF remodelling, which benefits clinical treatments and drug development.

Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study

Purpose

To develop machine learning-based radiomics models derive from different MRI sequences for distinction between benign and malignant PI-RADS 3 lesions before intervention, and to cross-institution validate the generalization ability of the models.

Methods

The pre-biopsy MRI datas of 463 patients classified as PI-RADS 3 lesions were collected from 4 medical institutions retrospectively. 2347 radiomics features were extracted from the VOI of T2WI, DWI and ADC images. The ANOVA feature ranking method and support vector machine classifier were used to construct 3 single-sequence models and 1 integrated model combined with the features of three sequences. All the models were established in the training set and independently verified in the internal test and external validation set. The AUC was used to compared the predictive performance of PSAD with each model. Hosmer–lemeshow test was used to evaluate the degree of fitting between prediction probability and pathological results. Non-inferiority test was used to check generalization performance of the integrated model.

Results

The difference of PSAD between PCa and benign lesions was statistically significant (P = 0.006), with the mean AUC of 0.701 for predicting clinically significant prostate cancer (internal test AUC = 0.709 vs. external validation AUC = 0.692, P = 0.013) and 0.630 for predicting all cancer (internal test AUC = 0.637 vs. external validation AUC = 0.623, P = 0.036). T2WI-model with the mean AUC of 0.717 for predicting csPCa (internal test AUC = 0.738 vs. external validation AUC = 0.695, P = 0.264) and 0.634 for predicting all cancer (internal test AUC = 0.678 vs. external validation AUC = 0.589, P = 0.547). DWI-model with the mean AUC of 0.658 for predicting csPCa (internal test AUC = 0.635 vs. external validation AUC = 0.681, P = 0.086) and 0.655 for predicting all cancer (internal test AUC = 0.712 vs. external validation AUC = 0.598, P = 0.437). ADC-model with the mean AUC of 0.746 for predicting csPCa (internal test AUC = 0.767 vs. external validation AUC = 0.724, P = 0.269) and 0.645 for predicting all cancer (internal test AUC = 0.650 vs. external validation AUC = 0.640, P = 0.848). Integrated model with the mean AUC of 0.803 for predicting csPCa (internal test AUC = 0.804 vs. external validation AUC = 0.801, P = 0.019) and 0.778 for predicting all cancer (internal test AUC = 0.801 vs. external validation AUC = 0.754, P = 0.047).

Conclusions

The radiomics model based on machine learning has the potential to be a non-invasive tool to distinguish cancerous, noncancerous and csPCa in PI-RADS 3 lesions, and has relatively high generalization ability between different date set.

Arrestin-dependent nuclear export of phosphodiesterase 4D promotes GPCR-induced nuclear cAMP signaling required for learning and memory

G protein-coupled receptors (GPCRs) promote the expression of immediate early genes required for learning and memory. Here, we showed that β2-adrenergic receptor (β2AR) stimulation induced the nuclear export of phosphodiesterase 4D5 (PDE4D5), an enzyme that degrades the second messenger cAMP, to enable memory consolidation. We demonstrated that the endocytosis of β2AR phosphorylated by GPCR kinases (GRKs) mediated arrestin3-dependent nuclear export of PDE4D5, which was critical for promoting nuclear cAMP signaling and gene expression in hippocampal neurons for memory consolidation. Inhibition of the arrestin3-PDE4D5 association prevented β2AR-induced nuclear cAMP signaling without affecting receptor endocytosis. Direct PDE4 inhibition rescued β2AR-induced nuclear cAMP signaling and ameliorated memory deficits in mice expressing a form of the β2AR that could not be phosphorylated by GRKs. These data reveal how β2AR phosphorylated by endosomal GRK promotes the nuclear export of PDE4D5, leading to nuclear cAMP signaling, changes in gene expression, and memory consolidation. This study also highlights the translocation of PDEs as a mechanism to promote cAMP signaling in specific subcellular locations downstream of GPCR activation.

Ultrasensitivity Detecting AChE through "Covalent Assembly" and Signal Amplification Strategic Approaches and Applied to Screen Its Inhibitor

An ultrasensitivity detecting assay for acetylcholinesterase (AChE) activity was developed based on "covalent assembly" and signal amplification strategic approaches. After hydrolyzing thioacetylcholine by AChE and participation of thiol in a self-inducing cascade accelerated by the Meldrum acid derivatives of 2-[bis(methylthio) methylene] malonitrile (CA-2), mercaptans triggered an intramolecular cyclization assembly by the probe of 2-(2,2-dicyanovinyl)-5-(diethylamino) phenyl 2,4-dinitrobenzenesulfonate (Sd-I) to produce strong fluorescence. The limit of detection for AChE activity was as low as 0.0048 mU/mL. The detection system also had a good detecting effect on AChE activity in human serum and could also be used to screen its inhibitors. By constructing a Sd-I@agarose hydrogel with a smartphone, a point-of-care detection of AChE activity was achieved again.

Supramolecular Exosome Array for Efficient Capture and In Situ Detection of Protein Biomarkers

Exosomes are an emerging source for disease biomarker discovery due to the high stability of proteins protected by phospholipid bilayers. However, liquid biopsy with exosomes remains challenging due to the extreme complexity of biological samples. Herein, we introduced an amphiphile-dendrimer supramolecular probe (ADSP) for the efficient capture and high-throughput analysis of exosomes, enabling the array-based assay for marker proteins. Amphiphilic amphotericin B was functionalized onto highly branched globular dendrimers, which can then insert into the exosome membrane efficiently, forming a supramolecular complex through multivalent interactions between the probe and the bilayer of exosomes. The ADSP can be easily coated onto magnetic beads or the nitrocellulose membrane, facilitating the capture of exosomes from a minimum amount of clinical samples. The captured exosomes can be detected with target protein antibodies via Western blotting or in a high-throughput array-based dot blotting format. This new strategy exhibited excellent extraction capability from trace body fluids with superior sensitivity (less than 1 μL plasma), good quantitation ability (R² > 0.99), and high throughput (96 samples in one batch) using clinical plasma samples. The combination of proteomics and ADSP will provide a platform for the discovery and validation of protein biomarkers for cancer diagnosis and prognosis.

Amorphous InGaZnO Thin-Film Transistors with Double-Stacked Channel Layers for Ultraviolet Light Detection

Amorphous InGaZnO thin film transistors (a-IGZO TFTs) with double-stacked channel layers (DSCL) were quite fit for ultraviolet (UV) light detection, where the best DSCL was prepared by the depositions of oxygen-rich (OR) IGZO followed by the oxygen-deficient (OD) IGZO films. We investigated the influences of oxygen partial pressure (P_O) for DSCL-TFTs on their sensing abilities by experiments as well as Technology Computer Aided Design (TCAD) simulations. With the increase in P_O values for the DSCL depositions, the sensing parameters, including photogenerated current (I_photo), sensitivity (S), responsivity (R), and detectivity (D*) of the corresponding TFTs, apparently degraded. Compared with P_O variations for the OR-IGZO films, those for the OD-IGZO depositions more strongly influenced the sensing performances of the DSCL-TFT UV light detectors. The TCAD simulations showed that the variations of the electron concentrations (or oxygen vacancy (V_O) density) with P_O values under UV light illuminations might account for these experimental results. Finally, some design guidelines for DSCL-TFT UV light detectors were proposed, which might benefit the potential applications of these novel semiconductor devices.

Dual attention guided multiscale neural network trained with curriculum learning for noninvasive prediction of Gleason Grade Group from MRI

BACKGROUND

The Gleason Grade Group (GG) is essential in assessing the malignancy of prostate cancer (PCa) and is typically obtained by invasive biopsy procedures in which sampling errors could lead to inaccurately scored GGs. With the gradually recognized value of bi-parametric magnetic resonance imaging (bpMRI) in PCa, it is beneficial to noninvasively predict GGs from bpMRI for early diagnosis and treatment planning of PCa. However, it is challenging to establish the connection between bpMRI features and GGs.

PURPOSE

In this study, we propose a dual attention-guided multiscale neural network (DAMS-Net) to predict the 5-scored GG from bpMRI and design a training curriculum to further improve the prediction performance.

METHODS

The proposed DAMS-Net incorporates a feature pyramid network (FPN) to fully extract the multiscale features for lesions of varying sizes and a dual attention module to focus on lesion and surrounding regions while avoiding the influence of irrelevant ones. Furthermore, to enhance the differential ability for lesions with the inter-grade similarity and intra-grade variation in bpMRI, the training process employs a specially designed curriculum based on the differences between the radiological evaluations and the ground truth GGs.

RESULTS

Extensive experiments were conducted on a private dataset of 382 patients and the public PROSTATEx-2 dataset. For the private dataset, the experimental results showed that the proposed network performed better than the plain baseline model for GG prediction, achieving a mean quadratic weighted Kappa (K_w ) of 0.4902 and a mean positive predictive value of 0.9098 for predicting clinically significant cancer (PPV_GG>1 ). With the application of curriculum learning, the mean K_w and PPV_GG>1 further increased to 0.5144 and 0.9118, respectively. For the public dataset, the proposed method achieved state-of-the-art results of 0.5413 K_w and 0.9747 PPV_GG>1 .

CONCLUSION

The proposed DAMS-Net trained with curriculum learning can effectively predict GGs from bpMRI, which may assist clinicians in early diagnosis and treatment planning for PCa patients.

Integrated multi-omics analysis identifies CD73 as a prognostic biomarker and immunotherapy response predictor in head and neck squamous cell carcinoma

BACKGROUND

Advances in tumor immunotherapy have been developed for patients with advanced recurrent or metastatic (R/M) HNSCC. However, the response of most HNSCC patients to immune checkpoint inhibitors (ICI) remains unsatisfactory. CD73 is a promising target for tumor immunotherapy, but its role in HNSCC remains insufficient. In this study, we aim to explore the function of CD73 in HNSCC.

METHODS

Transcriptomic and clinical data of TCGA-HNSC were downloaded from UCSC Xena for analysis of CD73 mRNA expression and prognosis. Immunohistochemical assay were performed to validate the expression of CD73 in tumor tissues and its relationship with CD8+ T cells. GSEA analysis was performed with the "clusterProfiler" R package. Immune infiltration analysis was calculated with ESTIMATE, CIBERSORT and MCP-counter algorithms. Single-cell transcriptomic data was originated from GSE103322. Cell clustering, annotation and CD73 expression were from the TISCH database. Correlation data between CD73 and tumor signatures were obtained from the CancerSEA database. Somatic mutation data were obtained from TCGA-HNSC and analyzed by "maftools" R package. Immune efficacy prediction was performed using TIDE algorithm and validated with the IMvigor210 cohort.

RESULTS

Compared with normal tissues, both mRNA and protein expressions of CD73 were elevated in tumor tissues (P = 9.7×10-10, P = 7.6×10-5, respectively). Kaplan-Meier analysis revealed that patients with high expression of CD73 had worse overall survival (log-rank P = 0.0094), and CD73 could be used as a diagnostic factor for HNSCC (AUC = 0.778). Both bulk RNA-seq and single-cell RNA-seq analysis showed that high CD73 expression can promote EMT and metastasis, samples with high CD73 expression had reduced CD8+ T cells. Furthermore, it was found that CD73-high group was more prone to have mutations in TP53, HRAS and CDKN2A, and were negatively correlated with TMB (P = 0.0055) and MSI (P = 0.00034). Mutational signature analysis found that CD73 was associated with APOBEC signature. Immunotherapy efficacy analysis showed that CD73-high group was less sensitive to immune efficacy.

CONCLUSIONS

Our results demonstrate that CD73 has an inhibitory effect on the tumor microenvironment, and is more likely to be unresponsive to ICI therapy. Collectively, targeting CD73 may provide new insights for tumor targeted therapy and/or immunotherapy.

Phase 1 multicenter, dose-expansion study of ARX788 as monotherapy in HER2-positive advanced gastric and gastroesophageal junction adenocarcinoma

ARX788 is an anti-human epidermal growth factor receptor 2 (HER2) antibody-drug conjugate with AS269 as cytotoxic payload. In this phase 1 multicenter dose-expansion clinical trial, patients with HER2-positive advanced gastric/gastroesophageal junction adenocarcinoma failing to respond to prior trastuzumab-based standard treatment were enrolled. Between July 15^th, 2019, and March 14^th, 2022, 30 participants were enrolled. Twenty-eight (93.3%) patients experienced at least one drug-related adverse event (AE) and 13.3% experienced grade 3 ARX788-related AEs. The confirmed objective response rate is 37.9% (95% confidence interval [CI]: 20.7%-57.7%) and the disease control rate is 55.2% (95% CI: 35.7%-73.6%). With a median follow up of 10 months, the median progression-free survival and overall survival are 4.1 (95% CI: 1.4-6.4) and 10.7 months (95% CI: 4.8-not reached), respectively. The median duration of response is 8.4 (95% CI: 2.1-18.9) months. ARX788 is well tolerated and has promising anti-tumor activity in patients with HER2-positive advanced gastric adenocarcinoma (ChinaDrugTrials.org.cn: CTR20190639).

Promoter methylation-regulated miR-148a-3p inhibits lung adenocarcinoma (LUAD) progression by targeting MAP3K9

Lung adenocarcinoma (LUAD) characterized by high metastasis and mortality is the leading subtype of non-small cell lung cancer. Evidence shows that some microRNAs (miRNAs) may act as oncogenes or tumor suppressor genes, leading to malignant tumor occurrence and progression. To better understand the molecular mechanism associated with miRNA methylation in LUAD progression and clinical outcomes, we investigated the correlation between miR-148a-3p methylation and the clinical features of LUAD. In the LUAD cell lines and tumor tissues from patients, miR-148a-3p was found to be significantly downregulated, while the methylation of miR-148a-3p promoter was notably increased. Importantly, miR-148a-3p hypermethylation was closely associated with lymph node metastasis. We demonstrated that mitogen-activated protein (MAP) kinase kinase kinase 9 (MAP3K9) was the target of miR-148a-3p and that MAP3K9 levels were significantly increased in both LUAD cell lines and clinical tumor tissues. In A549 and NCI-H1299 cells, overexpression of miR-148a-3p or silencing MAP3K9 significantly inhibited cell growth, migration, invasion and cytoskeleton reorganization accompanied by suppressing the epithelial-mesenchymal transition. In a nude mouse xenograft assay we found that tumor growth was effectively inhibited by miR-148a-3p overexpression. Taken together, the promoter methylation-associated decrease in miR-148a-3p could lead to lung cancer metastasis by targeting MAP3K9. This study suggests that miR-148a-3p and MAP3K9 may act as novel therapeutic targets for the treatment of LUAD and have potential clinical applications.

Versatile Nano-PROTAC-Induced Epigenetic Reader Degradation for Efficient Lung Cancer Therapy

Recent evidence has indicated that overexpression of the epigenetic reader bromodomain-containing protein 4 (BRD4) contributes to a poor prognosis of lung cancers, and the suppression of its expression promotes cell apoptosis and leads to tumor shrinkage. Proteolysis targeting chimera (PROTAC) has recently emerged as a promising therapeutic strategy with the capability to precisely degrade targeted proteins. Herein, a novel style of versatile nano-PROTAC (CREATE (CRV-LLC membrane/DS-PLGA/dBET6)) is developed, which is constructed by using a pH/GSH (glutathione)-responsive polymer (disulfide bond-linked poly(lactic-co-glycolic acid), DS-PLGA) to load BRD4-targeted PROTAC (dBET6), followed by the camouflage with engineered lung cancer cell membranes with dual targeting capability. Notably, CREATE remarkably confers simultaneous targeting ability to lung cancer cells and tumor-associated macrophages (TAMs). The pH/GSH-responsive design improves the release of dBET6 payload from nanoparticles to induce pronounced apoptosis of both cells, which synergistically inhibits tumor growth in both subcutaneous and orthotopic tumor-bearing mouse model. Furthermore, the efficient tumor inhibition is due to the direct elimination of lung cancer cells and TAMs, which remodels the tumor microenvironment. Taken together, the results elucidate the construction of a versatile nano-PROTAC enables to eliminate both lung cancer cells and TAMs, which opens a new avenue for efficient lung cancer therapy via PROTAC.

Nanomaterial integrated 3D printing for biomedical applications

3D printing technology, otherwise known as additive manufacturing, has provided a promising tool for manufacturing customized biomaterials for tissue engineering and regenerative medicine applications. A vast variety of biomaterials including metals, ceramics, polymers, and composites are currently being used as base materials in 3D printing. In recent years, nanomaterials have been incorporated into 3D printing polymers to fabricate innovative, versatile, multifunctional hybrid materials that can be used in many different applications within the biomedical field. This review focuses on recent advances in novel hybrid biomaterials composed of nanomaterials and 3D printing technologies for biomedical applications. Various nanomaterials including metal-based nanomaterials, metal-organic frameworks, upconversion nanoparticles, and lipid-based nanoparticles used for 3D printing are presented, with a summary of the mechanisms, functional properties, advantages, disadvantages, and applications in biomedical 3D printing. To finish, this review offers a perspective and discusses the challenges facing the further development of nanomaterials in biomedical 3D printing.