PROteolysis TArgeting Chimeras (PROTACs) has been exploited to degrade putative protein targets. However, the antitumor performance of PROTACs is impaired by their insufficient tumour distribution. Herein, we present de novo designed polymeric PROTAC (POLY-PROTAC) nanotherapeutics for tumour-specific protein degradation. The POLY-PROTACs are engineered by covalently grafting small molecular PROTACs onto the backbone of an amphiphilic diblock copolymer via the disulfide bonds. The POLY-PROTACs self-assemble into micellar nanoparticles and sequentially respond to extracellular matrix metalloproteinase-2, intracellular acidic and reductive tumour microenvironment. The POLY-PROTAC NPs are further functionalized with azide groups for bioorthogonal click reaction-amplified PROTAC delivery to the tumour tissue. For proof-of-concept, we demonstrate that tumour-specific BRD4 degradation with the bioorthogonal POLY-PROTAC nanoplatform combine with photodynamic therapy efficiently regress tumour xenografts in a mouse model of MDA-MB-231 breast cancer. This study suggests the potential of the POLY-PROTACs for precise protein degradation and PROTAC-based cancer therapy. Proteolysis targeting chimeras (PROTACs) have emerged as promising cancer therapy agents but have suffered from systemic toxicity issues. Here, the authors report on the creation of polymeric PROTAC nanoparticles for tumour targeting delivery and demonstrate protein degradation in vivo, in combination with photodynamic therapy. PROTACs are generally composed of a warhead that binds to the protein of interest (POI), a ligand-hijacking endogenous E3 ubiquitin ligase, and a linker connecting the warhead and the ligand6. PROTACs can label the POI with ubiquitin by recognising the E3 ligase and subsequently degrade the POI through the ubiquitin-proteasome system (UPS)9. Compared to small molecule inhibitors, PROTACs can potentially degrade any intracellular protein, including undruggable targets 12. Furthermore, PROTACs are potent agents that can circumvent acquired drug resistance by degrading whole proteins after a short drug exposure time and a low dosage14. Despite being promising, conventional small molecular PROTACs generally display unfavourable pharmacokinetics and lack tumour specificity, which might cause systemic toxicity due to their nonspecific distribution in normal tissues16. Thus, it remains a formidable challenge to achieve tumour-specific delivery and potentiate the antitumor potency of conventional PROTACs.Heterobifunctional PROteolysis TArgeting Chimeras (PROTACs) hold promising potential for cancer therapy, as they can degrade oncoproteins, particularly undruggable targets22. These decorated PROTACs have shown increased cellular uptake in vitro. In particular, aptamer-PROTAC conjugates have displayed increased tumour accumulation and antitumor potency in vivo compared to conventional PROTACs22. Nevertheless, these ligand-PROTAC conjugates suffer from low serum stability, limited tumour penetration and heterogeneous expression of the receptors in different tumour cells and cancer types. Furthermore, opto-PROTACs were developed for ultraviolet light-inducible protein degradation24. These photoactivatable PROTACs have been demonstrated to spatiotemporally control protein degradation in vitro27. However, clinical translation of opto-PROTACs is restricted by the poor tissue penetration profile of ultraviolet light with short wavelength . Therefore, precise PROTAC delivery to the tumour and efficient POI degradation inside tumour cells remain formidable challenges.To achieve tumour-targeted delivery of PROTACs, several ligand modification strategies  have been investigated in recent yearsIn this work we rationally engineer a polymeric PROTAC (POLY-PROTAC) nanoplatform for tumour-targeted degradation of the bromodomain and extraterminal (BET) protein BRD4. We first synthesise four von Hipel-Lindau (VHL)-based small molecular PROTACs and then design a series of reduction-activatable POLY-PROTACs and self-assemble into micellar nanoparticles (NPs) for systemic PROTAC delivery Fig. . We subs28. To design a BRD4-targeted POLY-PROTAC, we selected the VHL ligand for PROTAC synthesis since the hydroxyl group of VHL can be reversibly caged via a disulfide spacer. The ability of the modified PROTACs to bind VHL can be restored by GSH-triggered cleavage of the disulfide bond in the cytosol of tumour cells.BET family proteins, in particular BRD4, have been investigated as promising antitumor targets due to their crucial role in gene transcription30. Western blot assays validated that all four PROTACs remarkably degraded BRD4 in MDA-MB-231 breast cancer cells in vitro and consequently suppressed downstream c-Myc expression. Noticeably, the compounds ARV771 and MZ1 reduced BRD4 expression more efficiently than their analogues. The half-degradation concentration (DC50) of ARV771 was 1.9-fold lower than that of mARV771  of the PROTACs were tens of times lower than that of the BRD4 inhibitor JQ1   and mass spectrometry (MS) measurements  Fig.  to rever33, and reduction-triggered delivery of the BRD4 PROTACs. The resultant POLY-PROTACs were termed according to the PROTAC molecule used: PD7 (based on Me-ARV771) or PDM (based on Me-MZ1). An MMP-2-cleavable GPLGLAG (GG) heptapeptide spacer35, was introduced into the PD7 POLY-PROTAC  to promote tumour-specific accumulation and cellular uptake of the POLY-PROTAC NPs  (termed PGDA) diblock copolymer was synthesised by grafting PPa onto the pendant hydroxyl groups of PGDH  and the acid-ionisable 2-(diisopropylamino)ethyl methacrylate (DPA) monomer for intracellular acidity 37. At neutral pH (7.4), dynamic light scattering (DLS) data and transmission electron microscopy (TEM) examinations revealed an average hydrodynamic diameter of ~55 nm and a spherical morphology of the POLY-PROTAC NPs with a narrow particle size distribution (polydispersity index (PDI) < 0.2). In contrast, amorphous aggregates appeared at pH 6.0 due to acid-induced protonation of the DPA groups and dissociation of the POLY-PROTAC NPs , which mimics the acidic microenvironment of endosome organelles (pH = 5.8~6.5)  Fig. . This phHPLC examinations showed that in the absence of GSH, ARV771 was marginally released from the PGD7 NPs under both neutral and acidic conditions (pH = 7.4 and 6.0) Fig. . In cont39. MDA-MB-231 breast tumour cells were then incubated with PDA7 or dePEGylated PGDA7 NPs for the desired time durations. Flow cytometry measurements identified an ~2.8-fold higher intracellular fluorescence signal in the PGDA7 group than in the PDA7 group  multicellular spheroid (MCS) MDA-MB-231 tumour model in vitro. CLSM images showed that after 12 h of incubation, the MMP-2-insensitive PDA7 NPs were primarily entrapped in the peripheral areas and marginally penetrated into the deep areas of the MCSs Fig. . In cont50 of the PGD7 and PGDM NPs, which were 1.9- and 3.1-fold lower than their MMP-2-insensitive PD7 and PDM counterparts, respectively, and comparable to those of free ARV771 and MZ1  and the POLY-PROTAC NPs  Fig. , verifyi3. In vivo fluorescence imaging displayed clear tumour distribution of the PGDA7 NPs over time  injection at an identical ARV771 dose of 10 mg/kg and PPa dose of 5.0 mg/kg when the tumour volume reached 200 mmime Fig. , which cion Fig. .Fig. 4StThe tumour-specific distribution of the PGDA7 NPs was confirmed by ex vivo fluorescence imaging of the major organs  and the tumour tissue at 48 h post-injection Fig. . CLSM ex3 and i.v. injected with PBS, ARV771 or the PGD7 NPs at an identical ARV771 dosage of 10 mg/kg. The treatments were repeated every three days for a total of five injections  staining of the tumour sections Fig. . Immunoh42, we next designed an extracellular tumour acidity-activatable pretargeted NPs for tumour-targeted delivery of the dibenzocyclooctyne (DBCO) groups   diblock copolymer  Fig.  and with3PGDH)  NPs. The azide group on the surface of the N3@PGD7 NPs was expected to perform in-situ click reaction with DBCO groups in the acidic tumour microenvironment. Both the PED and N3@PGD7 NPs displayed good serum stability in 10% (V/V) foetal bovine serum-containing neutral buffer solution (pH 7.4)  and PDT dramatically regressed 95% of tumour growth, which was 1.5-fold more efficient than BRD4 degradation alone caused by PED + N3@PGDA7 treatment.The antitumor performance of combining PDT with BRD4 degradation was next investigated in vivo. MDA-MB-231 tumour-bearing BALB/c nude mice were randomly grouped when the tumour volumes reached ~ 100 mmser Fig. . The N3@3@PGDA7 and PDT prolonged the survival of the tumour-bearing mice by 40% compared to those in the PED + N3@PGDA7 group, with 40% of the animals surviving 100 days post-treatment  than N3@PGDA7 NP alone, validating that the increased intratumoural distribution of ARV771 via the in situ bioorthogonal reaction contributed to BRD4 degradation in vivo  and degraded BRD4 (3.0-fold) than PED + N3@PGD7, verifying the synergistic apoptosis-induction profile caused by combined PDT and BRD4 degradation , and these are both under investigation in our laboratory for potentiated antitumor performance.In comparison with their small molecular PROTAC counterparts, the POLY-PROTAC NPs reported in this study possess several distinct advantages. First, the POLY-PROTAC NPs with MMP-2-liable PEG coronas elongated the blood circulation of the small molecular PROTACs, while the PEG coronas were cleaved via intratumoural MMP-2 to facilitate PROTAC tumour-specific accumulation and retention. Second, the POLY-PROTAC NPs can disintegrate in the intratumoural acidic microenvironment. The PROTAC prodrug can thus be restored in the cytosol via GSH-mediated cleavage of the disulfide bond. Furthermore, we demonstrated that the POLY-PROTAC NPs can be adapted for bioorthogonal click reaction-enforced tumour specificity. Remarkably, the azide-modified POLY-PROTAC NPs showed 3.9-fold higher tumour accumulation than their small molecule counterparts via an in situ click reaction with the pretargeted NPs, which therefore further boosted PROTAC-based cancer therapy. Moreover, other kinds of stimuli-activatable chemical bonds In summary, a POLY-PROTAC prodrug strategy was developed for the tumour-specific delivery of PROTACs in this study. We demonstrated that this POLY-PROTAC nanoplatform can be activated by multiple stimuli , which can achieve increased tumour accumulation, deep tumour penetration and enhanced protein degradation performance compared with its small molecule counterpart. The POLY-PROTAC nanoplatform with an extracellular tumour acidity-triggered bioorthogonal click reaction remarkably enhanced tumour-specific PROTAC delivery. This clickable POLY-PROTAC nanoplatform can be further applied with PDT for protein degradation and combination therapy, as this combinatorial treatment suppressed over 95% of MDA-MB-231 TNBC tumour growth. The extracellular acidic microenvironment containing MMP-2 has been well documented in various solid tumours. Therefore, this acid-activatable bioorthogonal POLY-PROTAC nanoplatform can be further employed for combination therapy to treat a broad spectrum of cancers by integrating multiple therapeutic regimens . Taken together, the proposed POLY-PROTAC nanoplatform might provide a novel avenue to potentiate PROTAC-based cancer therapy.113-NH2) and azide-poly(ethylene glycol) amine (N3-PEG113-NH2) were purchased from Seebio Biotech. Co., Ltd . Pyropheophorbide a (PPa) and Bis(4-nitrophenyl) carbonate were purchased from Dibai biotechnology CO., LTD. . Tert-butyl ((2 S)−1-((4 R)−4-hydroxy-2-(((S)−1-(4-(4-methylthiazol-5-yl)phenyl)ethyl)carbamoyl)pyrrolidin-1-yl)−3,3-dimethyl-1oxobutan −2-yl) carbamate was obtained from Ruozhi Chemical Technology Co., LTD. .1-(3-Dimethylaminopropyl)−3-ethylcarbodiimide hydrochloride (EDCI), 1-Hydroxybenzotriazole (HOBT), 4-Dimethylaminopyridine (DMAP), Trifluoroacetic acid (TFA), N, N-Diisopropylethylamine (DIEA), N,N-Dimethylacetamide , Dichloromethane , Dimethyl sulfoxide , N,N-Dimethylformamide , 2,2’-Azobis (2-methylpropionitrile (AIBN), and methanol  were purchased from J&K Chemicals . 4-Cyano-4-(dodecylsulfanylthiocarbonyl) sulfanylpentanoic acid (CDP), 2-(diisopropylamino) ethyl methacrylate (DPA), IV Gelatinase, Triethylene glycol and tert-butyl (S)−2-(4-(4-chlorophenyl)−2,3,9-trimethyl-6H-thienotriazolodiazepin-6-yl)acetate (JQ1) were obtained from Sigma-Aldrich . Bis(2-hydroxyethyl) disulfide, Triphosgene, 2-bromoethanol, 2-hydroxyethyl methacrylate, Methacryloyl chloride and methacryloyl chloride N-ethylpropan-1-amine were purchased from TCI . Tert-butyl 2-(3-(2-aminoethoxy)propoxy)acetate, tert-butyl-2-(2-(2-(2-aminoethoxy)ethoxy)ethoxy) acetate were all purchased from Shanghai Tebo Chemical Technology Co., LTD. Fmoc-protected heptapeptide Gly-Pro-Leu-Gly-Leu-Ala-Gly (Fmoc-GPLGLAG) was synthesised by GL Biochem. Co., Ltd . Methoxy poly(ethylene glycol) amine (mPEGDulbecco’s modified eagle medium (DMEM), 0.25% trypsin-EDTA, penicillin/streptomycin solution, PBS buffer solution (1×), bovine serum albumin , BCA protein quantification kit, protein marker (10-190 kDa), TBST buffer solution (10×), HEPES buffer solution (2×), 4’,6-Diamidino-2-phenylindole dihydrochloride (DAPI), Anti-fade solution, Lyso-green DND-189, singlet oxygen fluorescent probe SOSG, reactive oxygen species fluorescent probe DCFH-DA, cell counting kit-8 (CCK-8), MG132 proteasome inhibitor and ECL luminescence reagent were purchased from Meilun Biotech Co., Ltd . Foetal bovine serum (FBS) was purchased from Gibco . BD Matrigel, Tris-Base, glycine, SDS, Peroxidase-Conjugated Goat Anti-Rabbit IgG (H + L) (CAT:33101ES60) and Peroxidase-Conjugated Goat Anti-Mouse IgG (H + L) (CAT:33201ES60) were purchased from YEASEN . The anti-BRD4 antibody (ab128874), anti-c-Myc antibody (ab32072), anti-caspase-3 antibody (ab 184787), anti-GAPDH antibody (ab8245), anti-β-actin antibody (ab8226), anti-β-tubulin antibody (ab78078) were all purchased from Abcam (Shanghai). All other reagents and solvents were analytical grade and obtained from SinoPharm Chemical Reagent Co., Ltd. .2. All cell culture studies were performed in the logarithmic phase of cell growth in vitro.MDA-MB-231 human breast cancer cell line was obtained from the cell bank of Chinese Academy of Sciences . The cells were incubated in complete DMEM cell culture medium containing FBS 10% (V/V), penicillin G sodium and streptomycin sulfate (100 U/mL), and incubated at 37 °C under a humidified atmosphere containing 5% of COBalb/c nude mice  were obtained from Shanghai Experimental Animal Center . Animals were housed under SPF conditions in groups of 4-5 mice per cage, and maintained at a temperature of ~25 °C in a humidity-controlled environment with a 12 h light/dark cycle, with free access to standard food and water. All animal procedures were carried out under the guidelines approved by the Institutional Animal Care and Use Committee (IACUC) of Shanghai Institute of Material Medica, Chinese Academy of Sciences.113-GALGLPG-b-P(DPA42-r-ARV7712) (2.0 mg) and mPEG113-GALGLPG-b-P(DPA48-r-HEMA7) (1.0 mg) were dissolved in 100 μL of DMF, and the mixture was added into 1 mL of DI water under ultrasonication to obtain the POLY-PROTAC nanoparticles (termed as PGD7 nanoparticles). The organic solvent was removed by dialyzing against DI water. One set of the POLY-PROTAC nanoparticles were prepared by following the same procedure described above:Briefly, mPEG113-b-P(DPA46-r-ARV7712) + mPEG113-b-P(DPA52-r-HEMA6);POLY-ARV77 nanoparticles (PD7): mPEG113-GALGLPG-b-P(DPA46-r ARV7712) + mPEG113-GALGLPG-b-P(DPA48-r-PPa4);MMP-2-liable POLY-ARV77 nanoparticles (PGDA7): mPEG113-b-P(DPA46-r-ARV7712) + mPEG113-b-P(DPA52-r-PPa4);PPa-modified POLY-ARV771 nanoparticles (PDA7): mPEG113-b-P(DPA42-r-MZ12) + mPEG113-b-P(DPA52-HEMA6);POLY-MZ1 nanoparticles (PDM): mPEG113-GALGLPG-b-P(DPA46-r-MZ12) + mPEG113-GALGLPG-b-P(DPA48-r-HEMA7);MMP-2-liable POLY-MZ1 nanoparticles (PGDM): mPEG113-b-P(EPA60-r-DBCO4) (namely PED) and mPEG113-b-P(EPA60-r-PPa1);DBCO-loaded pretargeted nanoparticles (PEA): mPEG3@PGDA7): mPEG113-GALGLPG-b-P(DPA42-r-ARV7712) (1.7 mg) + mPEG113-GALGLPG-b-P(DPA48-r-PPa4) (0.85 mg) + N3-PEG113-GALGLPG-b-P(DPA41-r-mPEG113-GALGLPG-b-P(DPA48-r-PPa4) (0.45 mg) were dissolved into 100 μL of DMF, and added into 1 mL of DI water under ultrasonication. Then, DMF was removed via dialyzing against DI water to obtain the N3@PGDA7 nanoparticles.To prepare the azide-functionalized POLY-ARV771 nanoparticles  and TEM examination .The fluorescence emission profile of the PPa-labelled micelle suspension was examined by microplate reader , and the fluorescence images were recorded by IVIS imaging system .2O = 1:1, v/v) for pre-determined time duration at 37 °C, the concentration of ARV771 released was examined by HPLC measurement .To demonstrate reduction sensitivity of the POLY-PROTAC nanoparticles, ARV771 release from ARV771 methyl methacrylate (Me-ARV771) was investigated in vitro. Briefly, Me-ARV771 (50 μM) was incubated with 10 mM of DTT  Tween 80-containing buffer solution at 37 °C . ARV771 concentration in the buffer solution was examined by HPLC measurement at the predetermined time points .To investigate PROTAC-induced protein degradation in vitro, MBA-MB-231 tumour cells were incubated with free PROTACs or POLY-PROTAC nanoparticles at the predetermined condition. The cells were then lysed in RIPA lysis buffer  including 1 mM of phenylmethanesulfonyl fluoride (PMSF). The protein lysate was obtained by centrifugation at 12000 g for 15 min at 4 °C. Then, the lysates were denatured at 100 °C and resolved by SDS-polyacrylamide gel electrophoresis (SDS-PAGE). The gels were blotted onto PVDF membrane (Merck Millipore) and blocked by 5% BSA buffer for 2 h at room temperature. After incubated with the indicated primary antibodies  at 4 °C overnight, the membrane was washed several times with TBST buffer, incubated with corresponding secondary antibody (Peroxidase-Conjugated Goat Anti-Rabbit IgG (H + L), CAT:33101ES60, 1:5000 and Peroxidase-Conjugated Goat Anti-Mouse IgG (H + L), CAT:33201ES60, 1:5000) in 5% BSA solution for 1 h at room temperature, washed several times with TBST buffer, and then imaged with Bio-Rad Chemi Doc XRS imaging system.4 MDA-MB-231 cells were cultured in 96-well cell culture plate for 24 h, the cells were then treated with free PROTAC or POLY-PROTAC nanoparticles at predetermined condition for 72 h. The cell viability was then examined by CCK-8 assay.To investigate the cytotoxicity of the POLY-PROTAC nanoparticles in vitro, 1 × 10To investigate cellular uptake profile of the POLY-PROTAC nanoparticles, MDA-MB-231 cells cultured in 24-well tissue culture plate were incubated with various POLY-PROTAC nanoparticles at the identical PPa concentration of 5.0 μM for the desired time durations , the intracellular fluorescence intensity were then examined by flow cytometry . The intracellular distribution of the POLY-PROTAC nanoparticles was investigated by CLSM examination.3D multicellular spheroid (MCS) of the MDA-MB-231 breast tumour was employed to illustrate the tumour penetration profiles of the POLY-PROTAC nanoparticles in vitro. Briefly, the 3D tumour spheroids were prepared by culturing MDA-MB-231 cells in 48-well tissue culture plate (2000 cells/well) on 1% agarose gel. The 3D tumour spheroids were then incubated with the PGDA7 and PDA7 (MMP-2 pretreated) nanoparticles for 12 h. Nanoparticle distribution inside the tumour spheroids was then investgiated by CLSM examination at the predetermined time points.2) for 1 min, and the fluorescence intensity of SOSG were detected by microplate reader .To investigate photoactivity of the PPa-modified POLY-PROTAC nanoparticles, 671 nm laser irradiation-induced ROS generation was examined. Briefly, the PGDA suspension with different PPa concentrations  was incubated in pH 6.0 or pH 7.4 buffer solution for 30 min, and then added with singlet oxygen sensor green . The micellar suspension was then irradiated with 671 nm laser at different photodensity , and the intracellular fluorescence intensity of DCF was analysed by flow cytometry. Laser irradiation induced intracellular ROS generation was validated by CLSM examination.To examine the photoactivity in vitro, MDA-MB-231 cells were culture in 24-well tissue culture plate for 24 h, incubated with the PGDA nanoparticles for 12 h, and then incubated with DCFH-DA (10 μM) for 30 min. The cells were thereafter irradiated with 671 nm laser for 1 min at varied photodensity  into the fat pad of the Balb/c nude mice . The tumour-bearing mice were randomly grouped when the tumour volume reached ∼200 mm3 and intravenously (i.v.) injected with PPa-labelled POLY-PROTAC nanoparticles at an identical PPa dose of 5.0 mg/kg. Then, fluorescence imaging was collected with the IVIS imaging system at predetermined time points . The mice were sacrificed at 48 h post-injection, the major organs and tumour tissue were harvested for fluorescence imaging ex-vivo. Afterwards, the tumour tissues were fixed, sectioned and stained with identified antibodies and DAPI, the fluorescence signal of the tumour sections were measured by CLSM examination.MDA-MB-231 breast tumour model was established by subcutaneously injecting 100 μL of cell suspension (1 × 103 (n = 3). The DBCO-loaded pretargeted (PED) nanoparticle was i.v. injected at a DBCO dose of 1.0 mg/kg, and the N3@PGDA7 nanoparticle was i.v. injected 2 h post PED administration at an ARV771 dose of 10 mg/kg. The biodistribution of PED and N3@PGDA7 was then examined by IVIS fluorescence imaging systems in vivo.To investigate whether in-situ click reaction increased tumour accumulation of the POLY-PROTAC nanoparticles, the tumour-bearing nude mice were divided into three groups when the tumour volume reached ~ 200 mmTo evaluate in-situ bioorthogonal click reaction enhanced tumour distribution of PROTAC, the tumour-bearing mice were i.v. injected with the POLY-PROTAC nanoparticles and sacrificed at the predetermined time points . The major organs  and tumour tissue were harvested and homogenised. ARV771 was extracted with methanol, examined by HPLC measurement and normalised with tissue mass.7 cells, DMEM: Matrigel = 1:1, v/v). The tumour volume reached 100 mm3 at 15-days post inoculation. The tumour-bearing mice were randomly grouped (n = 5), and i.v. injected with PBS, ARV771, or PGD7 nanoparticle at an identical ARV771 dose of 10 mg/kg for five cycles at a time interval of 3 days. The tumour volume was monitored for 30-days post treatment.The anti-tumour performance of the POLY-PROTAC nanoparticle was evaluated in MDA-MB-231 orthotropic tumour model in vivo. The female Balb/c nude mice were s.b. injected with 100 μL of cell suspension (1 × 103 (n = 5), the tumour-bearing mice were then i.v. injected with PBS, ARV771, PGD7, or PED + N3@PGD7 every three days at an identical ARV771 dose of 10 mg/kg, and DBCO dose of 1.0 mg/kg for five cycles (PED was injected 2 h pre- POLY-PROTAC nanoparticle administration).To investigate the antitumor performance of the bioorthogonal POLY-PROTAC nanoparticles, the tumour-bearing mice were randomly grouped when the tumour volume reached 100 mm3 (n = 5), and then i.v. injected with PBS, ARV771, PED + N3@PGDA, PED + N3@PGD7 or PED + PGDA7 at the identical ARV771 dose of 10.0 mg/kg, PPa dose of 5.0 mg/kg and DBCO dose of 1.0 mg/kg, respectively (PED was i.v. injected 2 h pre-administration of the N3@PGD7 nanoparticles). Thirty-six hours post nanoparticle injection, the mice of the PED + N3@PGDA and PED + PGDA7 groups were treated with 671 nm laser irradiation at photodensity of 400 mW/cm2 for 5 min. The treatment was repeated for five cycles at a time interval of three days. The tumour volume and body weights of the animals were monitored during the whole experimental period. The mice were considered death when the tumour volume reached 1500 mm3 according to the animal ethics of our institute and animal welfare. The tumours and the major organs  of mice were harvested at the end of the antitumor studies, and examined by H&E and TUNEL staining. BRD4 degradation in the tumour tissue was validated by western blot assay of the tumour lysate. The tumour volume was calculated with the formula below:To investigate the antitumor performance of POLY-PROTAC nanoparticle-performed combinatory BRD4 degradation and PDT, the POLY-PROTAC nanoparticles were labelled with PPa for PDT. The tumour-bearing mice were grouped when the tumour volume reached 100 mmAll data were given as Mean ± SD. The GraphPad Prism software 6.01 was used for the statistical analyses. Two-tailed Student’s t-test was used for the statistical comparison between the two groups. One-way analysis of variance (ANOVA) with a Tukey post hoc test was used for statistical comparison among multiple (more than two) groups. Two-sided log-rank (Mantel-Cox) test was used for the statistical comparison of the survival study.Further information on research design is available in the ChemDraw files of chemical structureSupplementary Information Engineered Bioorthogonal POLY-PROTAC Nanoparticles for Tumor-Specific Protein Degradation and Precise Cancer TherapyReporting summaryPeer Review File


Candida, Aspergillus, and Pneumocystis spp. We evaluated the in vitro activity of RZF, caspofungin (CSF), micafungin (MCF), and anidulafungin (ANF) against a worldwide collection of fungal isolates causing invasive infection.Rezafungin (RZF) is a once-weekly echinocandin (ECH) with a long half-life and front-loaded drug exposure. RZF is in development to treat candidemia and invasive candidiasis and prevent invasive fungal disease caused by C. albicans , C. glabrata , C. parapsilosis , C. tropicalis , C. dubliniensis , C. krusei , Cryptococcus neoformans  A. fumigatus , and A. section Flavi . CLSI criteria was applied, including the recently approved rezafungin provisional breakpoints against Candida spp.830 isolates were collected from Europe , North America , Asia-Pacific , and Latin America , identified by MALDI-TOF and/or sequencing, and tested by CLSI broth microdilution. Isolates included 50/90 in Table) at the susceptibility (S) breakpoint (BP). RZF had similar activity to the other ECHs against CA (99.7%S), CG (95.7-96.3%S), CT (100.0%S), CK (100.0%S), and CD . Although CSF displayed lower MIC50/90 values (0.25/0.25 mg/L) than RZF , MCF , and ANF  against CP, all ECHs but ANF (87.2%S) inhibited 100% of CP isolates at the respective BP. Only 1 CA (EU), 1 CD (EU), and 3 CG (NA) were non-S to RZF, while 1 CA (EU), 6 CG , and 19 CP  were ANF non-S. Limited activity was noted for all ECHs against CN . All AF isolates were inhibited by RZF at ≤ 0.06 mg/L, and ANF, MCF, and CSF at ≤ 0.12 mg/L. RZF  and other ECHs  were also active against 7 voriconazole non-S AF isolates . RZF and other ECHs inhibited all ASF isolates at ≤ 0.06 mg/L.RFZ inhibited 99.7% of CA, 98.1% of CG, 95.2% of CD, and all CP, CT, and CK , Cidara: Grant/Research Support|Pfizer: Grant/Research Support Paul Rhomberg, BS, MT(ASCP), Cidara: Grant/Research Support|Pfizer: Grant/Research Support Greg Strand, MLS (ASCP)CM, Cidara: Grant/Research Support Abby L. Klauer, BS, Cidara: Grant/Research Support Mariana Castanheira, PhD, AbbVie: Grant/Research Support|Cidara: Grant/Research Support|GSK: Grant/Research Support|Melinta: Grant/Research Support|Pfizer: Grant/Research Support|Shionogi: Grant/Research Support.


Academic research has yet to provide a comprehensive view on how to capture individuals’ attention when a promotional e-mail reaches their inbox. This study investigates the variables that influence consumers’ attention toward promotional e-mails, operationalized as open rates, and proposes an integrative model that combines and integrates visible, temporal, and contextual elements. The empirical analysis uses ordinary least squares linear regression to validate the model with data obtained from a multinational sample. The dataset, which is global in nature, comprises 5765 different promotional e-mails sent between 2013 and 2018 by different multinational companies to 455 million users located in 73 countries. The analysis provides information about the relative importance of the variables that influence individuals’ decisions to open a promotional e-mail and shows that the frequency of mailing and the use of segmentation techniques significantly affect the individual’s attention to e-mail marketing communications. The results also show a non-transparent opportunity cost associated with every e-mail sent and give advice on how to control that virtual cost. The research provides further recommendations to marketing professionals to improve the effectiveness of e-mail marketing campaigns. By 2021, around 52 percent of the world population was expected to have access to e-mail services Radicati . In deveDue to the relevance of e-mail marketing, there is increasing interest from the corporate world in researching its effectiveness Gartner , especiaThis lack of literature is particularly striking when we consider the challenges that companies face in the current global, hyper-competitive, and digital context. In a world saturated by promotional messages, it is becoming increasingly difficult to capture the attention of users. Further, in contrast to other media that show the entire message to the consumer directly, e-mail marketing requires that users perform a certain behavior—opening the mail—in order to have access to its content, which hampers the effectiveness of e-mail marketing campaigns. As an example, in the first half of 2019 recipients only opened 22 percent of the promotional newsletters they received . While empirical determination of attention is a challenging task on most advertising channels, the particularities of e-mail marketing makes this job simpler: because of clutter, less relevant e-mails tend to be deprioritized and remain unopened Magee . TherefoConsidering that effectiveness refers to the “degree to which something is successful in producing a decided, decisive or desired effect” (Merriam-Webster Opening effectiveness can be measured through open rates (OR), a ratio that determines the percentage of sent e-mails that have been opened , temporal and contextual variables, an approach similar to that followed by previous studies of e-mail marketing performance  at which the message is delivered are traditionally considered important elements to optimize advertising campaigns, given their influence on the responsiveness of consumers to advertisements Barnes . There iHowever, there is an important difference between e-mail marketing and television commercials or paid search advertising: the asynchronous nature of e-mail marketing. The fact that e-mail marketing is an asynchronous means of communication means that the moment the newsletter is sent is not necessarily the moment at which subscribers consume the content. While e-mail marketers have tools to determine the precise moment a subscriber opens an e-mail, they cannot establish the moment a user checks the inbox and decides whether to open an e-mail. Thus, the only data available is the time the message was sent. Fortunately, checking one’s inbox is often the first activity that most users perform when they connect to the Internet, and most of them do it several times a day  based on a wide range of variables is one of main advantages of the use of digital media for commercial communications Baggott . In thisSending promotional e-mails that are tailored to the characteristics of specific user segments has a positive relationship with users’ attention to those e-mails.Figure In order to determine the right sample for this research, it is worth considering that the product category may influence the effectiveness of online advertising  is measured by open rates.As Table The data analysis involves ordinary least squares linear regression, a method commonly used in the analysis of the effectiveness of digital media Baltas . We used2 = 0.150) in open rates. The intercept is significant at 3.002, so the open rate of a typical e-mail is 20.13 percent, slightly under the average figures in industry reports  and explains 15 percent of the variance , the presence of numbers and subject length (Nums*SubjLength), and the presence of special characters and subject length (SpecChars*SubjLength).Whether formal variables may have interaction effects between them. The analyzed interactions include the presence of numbers and presence of special characters (Nums*DiscSav) and numbers and seasonal promotions (Nums*SeasProm).Whether the presence of numbers on the subject line of quantitative-themed promotions has an effect on performance. The potential interactions consider the two predominant types of e-mail and therefore analyze the interactions between numbers and discount/savings e-mails (Freq*SubjLength).Whether the length of e-mails may have a negative influence on the effect of high sending frequency; that is, the interaction effect between frequency and subject length (Freq*DiscSav), and between frequency and seasonal promotions (Freq*SeasProm).Whether higher frequency affects performance of the two most frequent content types: interaction between frequency and discount/savings e-mails (Seg*Freq).Whether the negative effect of frequency of sending is reduced when e-mails are segmented because they are better tailored to the recipient’s needs and interests —interaction between segmentation and frequency of sending (Seg*DiscSav).Whether discount promotions are more effective on segmented than on non-segmented e-mails; that is, interaction between segmentation and discount/savings e-mails The analysis also includes the study of interaction effects among variables to rule out the effect of specific combinations. More precisely, the analysis tested the following interaction effects:Nums*SubjLength and Freq*DiscSav were significative, albeit only contributing to a marginal improvement on the variance explained . Table Out of the 10 interactions tested, only the pairs Figure This research makes a relevant contribution to the study of effectiveness in e-mail marketing along the visible, temporal, and contextual dimensions of the phenomenon. As this section shows, the results of the study provide cues to digital marketers to improve the performance and relevance of their campaigns, and open interesting avenues of research for academics. From the perspective of this journal, the study also enriches current research by exploring themes beyond core management topics, such as corporate social responsibility , supporting H3. Interestingly, a closer look to the data reveals that 67 percent of the promotional e-mails include numbers, nearly the same percentage of e-mails that include special characters. This finding, which merits further investigation, might suggest that numbers might no longer be considered a distinctive element, but special characters might still have a disruptive component that facilitates capturing the recipient’s attention.The interaction analysis Table  suggestsRegarding the type of content of the subject line, the results support H4. It is particularly surprising that the addition of a discount to a generic promotional communication seems to reduce its effectiveness. The inclusion of economic incentives is a recurrent advertising technique  suggests the existence of an opportunity cost for each e-mail sent; this cost may not be cancelled out by subsequent e-mails, which are likely to have lower effectiveness. Contrary to other digital media based on pay-per-click or impression models, e-mail marketing campaigns have had a negligible cost so far; however, and considering this opportunity cost, advertisers must be selective when implementing their e-mail marketing campaigns, applying the same scarcity mindset used in other channels where budget limitations act as catalyst for a careful selection of messages.The creation of a virtual cost mechanism may be helpful for measuring and controlling the opportunity cost of each promotional e-mail sent. For example, the team responsible for e-mail marketing at a company could assign a limited number of credits per year to the different communication teams that regularly send promotional e-mails, so that every time a promotional team sends an e-mail, a credit would be deducted from their account. Additional ways to reduce this opportunity cost include the accommodation of multiple messages in a single newsletter, such as templates that contain areas for multiple stories.Database segmentation, the other variable with key influence on performance (H8), not only allows sending personalized communications to a reduced subset of the database, helping reduce sending frequency, but also has the added benefit of increasing open rates. The double effect on performance, both direct and indirect through frequency reduction, is likely to trigger a relevant improvement of open rates. Therefore, using segmentation techniques on all communications may be the single most impactful action e-mail marketers can take to improve attention to their e-mails. Voice-of-the-customer programs that facilitate the identification of consumer archetypes are a good starting point for segmenting database users, in addition to the tactics already mentioned in the previous section. Firms with limited resources that cannot afford detailed voice-of-the-customer programs can use tactics rooted in entrepreneurial marketing with proven impact on performance, such as increasing risk-taking  might also influence open rates and should not be neglected by marketers. For example, lower sending frequency provides some flexibility in the selection of the day of the week the e-mails are sent, and marketers should take advantage of this flexibility to increase effectiveness by choosing the best moment to send the e-mails, preferably at the beginning of the week.The study also provides insights into the effectiveness of the different topics covered by the subject line. As Table This finding warns about the perils of just focusing on promotional messages  that entice subscribers to complete one-time purchases. The result is also a wake-up call for marketers and companies to explore innovative ways to craft and design their messages, aiming to stand out, engage at a personal level, and leave a lasting impression, or even resort to off-the-beaten-path themes, such as free gifts or seasonal promotions. Once again, entrepreneurial marketing can offer an answer to the conundrum marketers face regarding content; for example, popular techniques such as crowdsourcing , opening a door to the inclusion of these variables in future studies, to both enrich the results and address the potential concerns about cross-country equivalence.This research provides information to e-mail marketers about how to improve the attention that subscribers pay to promotional e-mails by incorporating slight and inexpensive changes to their current practice. The results of the study highlight the importance of higher control over sending frequency and the need for application of segmentation techniques and personalization to increase recipients’ attention and improve opening effectiveness. Other priorities include the selection of non-quantitative topics, the inclusion of special characters in the subject line, and the delivery of personalized newsletters at the beginning of the week. Finally, the research makes a notable theoretical and methodological contribution to the study of e-mail marketing effectiveness by proposing a new categorization of influencing variables–visible, temporal, and contextual —that can facilitate future research. Such categorization could also be extended to research on effectiveness of any other digital marketing channel.


Tumour size measurement is pivotal for staging and stratifying patients with pancreatic ductal adenocarcinoma (PDA). However, computed tomography (CT) frequently underestimates tumour size due to insufficient depiction of the tumour rim. CT-derived fractal dimension (FD) maps might help to visualise perfusion chaos, thus allowing more realistic size measurement.In 46 patients with histology-proven PDA, we compared tumour size measurements in routine multiphasic CT scans, CT-derived FD maps, multi-parametric magnetic resonance imaging (mpMRI), and, where available, gross pathology of resected specimens. Gross pathology was available as reference for diameter measurement in a discovery cohort of 10 patients. The remaining 36 patients constituted a separate validation cohort with mpMRI as reference for diameter and volume.p = 0.03) underestimation of tumour diameter on CT compared with gross pathology (Δdiameter3D = −5.7 mm), while realistic diameter measurements were obtained from FD maps (Δdiameter3D = 0.6 mm) and mpMRI (Δdiameter3D = −0.9 mm), with excellent correlation between the two (R2 = 0.88). In the validation cohort, CT also systematically underestimated tumour size in comparison to mpMRI , especially in larger tumours. In contrast, FD map measurements agreed excellently with mpMRI . Quantitative perfusion chaos was significantly (p = 0.001) higher in the tumour rim (FDrim = 4.43) compared to the core (FDcore = 4.37) and remote pancreas (FDpancreas = 4.28).Median RECIST diameter of all included tumours was 40 mm (range: 18–82 mm). In the discovery cohort, we found significant  and volume (Δvolume = −10.2 mL), especially in larger tumours.• Fractal analysis provides maps of the fractal dimension (FD), which enable a more reliable and size-independent measurement using gross pathology or multi-parametric MRI as reference standards.• FD quantifies perfusion chaos—the underlying pathophysiological principle—and can separate the more chaotic tumour rim from the tumour core and adjacent non-tumourous pancreas tissue.•  The current edition  and written informed consent was waived. Clinical routine data were analysed and patients with histologically proven PDA either from surgery or biopsy were included if CT and MRI datasets acquired within 1 week at the time of diagnosis were available.CT imaging was performed in a single-centre, single-scanner  setting. Scanning parameters were as follows: helical scan mode with tube voltage of 120 kV and tube current of 140 mAs, 0.8-s gantry rotation time, pitch factor of 1.375, and 64 × 0.675 mm collimation. Images were reconstructed on 512 × 512 pixel image matrices with resolution on the order of 0.7 mm × 0.7 mm × 1.25 mm and 1.25-mm increment using a soft tissue convolution kernel. CT was performed in a non-enhanced phase and after intravenous administration of a non-ionic iodine-based contrast agent . The scanning delay for pancreatic parenchymal phase imaging was determined by using a bolus-tracking technique with automated scan-triggering software . Acquisition of the pancreatic parenchymal and hepatic venous phases was started automatically at 17 and 50 s, respectively, after the trigger threshold (100 HU) was reached at the level of the supracoeliac abdominal aorta .2). The contrast agent was either gadoteric acid  at a dose of 0.2 mL/kg or gadobutrol  at a dose of 0.1 mL/kg, injected at a flow rate of 2 mL/s and followed by a saline flush (40 mL at 2 mL/s). Apparent diffusion coefficient (ADC) maps were generated using a post-processing console (Advantage Windows) with a monoexponential decay model.All MRI examinations were performed on a single scanner  using body phased array coils. The patients were imaged after an overnight fast. The following pulse sequences were obtained: 2D T2-weighted fat-saturation (FS) fast-recovery fast spin echo (FRFSE); pre-contrast 3D T1-weighted gradient echo (GRE); 3D T1-weighted FS dynamic GRE sequences in the arterial phase (25 s), portal phase (70 s), and delayed phase (3 and 5 min) after gadolinium-based contrast agent injection; and diffusion-weighted imaging (DWI) sequences  employing a standard combination of 3D affine and 3D b-spline transformations. Second, images were standardised for voxel size, image noise, and signal intensity. All images were resampled to an isotropic voxel spacing of 0.7 mm as a common denominator. To standardise image noise, a noise-level-adapted denoising scheme was employed consisting of a 3D median filter with a radius set to 2 pixels and a 3D bilateral filter [I0) and related each voxel’s signal (Ivoxel) in the contrast-enhanced phases to the respective portal vein signal intensity (Ipv) to obtain a normalised signal as follows: I = (Ivoxel − I0) / (Ipv − I0) × 100. This was done to standardise image intensity by a physiological reference, thereby accounting for potential differences in circulation and mitigating the issue of potential variation in timing image acquisition. After pre-processing, four-dimensional, local A fractal analysis was performed to generate maps of the local FD. A previously published method [The first author developed the fractal analysis software in Python 3.6, which implements the pre-processing pipeline including image registration and image standardisation as well as fractal analysis and segmentation. The CT imaging data were processed as follows. First, image registration was performed with the SimpleElastix framework, version 4.9  and T2-weighted images for volumetric tumour segmentation and T1-weighted fat-saturated contrast-enhanced images to visually assess conspicuity [3 = 0.128 mL. From tumour segmentations, volume and maximum diameter were calculated [To characterise the patient cohort, tumour diameter was conventionally measured on CT using the revised RECIST recommendations , which rspicuity . Voxel slculated . The maxlculated –30. The t-test was used to assess measurement differences per method. Bland-Altman statistics were calculated to evaluate systematic size measurement differences for each method, and the f-test was performed to evaluate variances of the differences. In a subpopulation of 20 cases, we assessed inter-reader agreement  in terms of relative size measurement discrepancy (in %) and Spearman’s ρ. To test whether fractal analysis is capable of identifying the tumour rim, local chaos per anatomical region  was analysed using descriptive statistics as well as the Kruskal-Wallis test and pairwise group comparisons using the Mann-Whitney U-test with Bonferroni correction to test for perfusion chaos differences between those anatomical sites. A level of p ≤ 0.05 (after Bonferroni correction where appropriate) was considered statistically significant. Statistical analysis was performed with R .In the discovery cohort with gross pathology reference, diameter measurements were tested for linear correlation of CT, mpMRI, and fractal analysis with pathology ground truth. Differences in size estimation between each method and the reference standard were evaluated using the pairwise Wilcoxon rank sum test for paired samples and Bonferroni correction for multiple testing. In the validation cohort with mpMRI as reference, CT and fractal analysis measurements of tumour volume and diameter were evaluated for linear correlation with mpMRI as reference. Furthermore, the A total of 46 patients were retrospectively included. The median diameter of all included tumours was 40 mm range: 18–82 mm). Tumour characteristics and imaging findings are summarised in Table 8–82 mm. R2 = 0.96; FD: R2 = 0.92) and did not show significant diameter differences . Moreover, measurements on FD maps correlated excellently to mpMRI (R2 = 0.88) without significant differences between those methods (p = 0.63). In contrast, CT measurements systematically underestimated tumour diameter in comparison to gross pathology . A representative example with correlation to gross pathology is depicted in Figure Our initial discovery cohort consisted of 10 patients, in which diameter measurements on gross pathology were available as reference standard. Both mpMRI and FD size estimates correlated well with gross pathology measurements (mpMRI: n = 36), we used mpMRI as surrogate due to its excellent correlation with gross pathology measurements as demonstrated in the initial discovery cohort. Tumour volume on FD maps correlated well with mpMRI volumetry  and showed no size-dependent variation (p = 0.77). In contrast, tumour volume was consistently underestimated on CT in comparison to mpMRI  with the amount of underestimation increasing with absolute tumour size (p = 0.01).Since pathological reference was not available in our validation cohort (p = 0.63), while maximum tumour diameters were consistently underestimated on CT . None of the diameter measurement methods showed an evident dependence on the actual tumour diameter . In a subgroup of 20 PDA lesions, inter-reader agreement was excellent both for diameter measurement  and for volume measurement . Detailed statistics on correlation and bias of the methods, including Bland-Altman plots, can be found in Figure For diameter measurements, FD-derived maximum tumour diameters agreed well with MRI reference  higher in the tumour rim  than in the tumour core , and both were higher than the FD in remote pancreas tissue ; i.e., perfusion was highly chaotic in the tumour rim, less chaotic in the tumour core, and least chaotic in remote pancreas tissue  , fractaln = 46), our study cohort is still representative of a variety of sizes and common clinical conditions found in PDA. However, our study does not represent all clinical circumstances, including the condition after neoadjuvant chemotherapy or very small tumours (< 1 cm in diameter). Moreover, our study did not include extremely obese patients, in whom a more extensive denoising scheme might be required. Rigorous denoising might affect image texture and thus degrade analysis of perfusion chaos. Since only a mild denoising scheme with noise-level adaptation was required in our study, we were able to preserve biology-induced texture. This might not be possible in extremely obese patients. We performed conventional diameter measurement according to RECIST recommendations to characterise the tumours. However, all further analyses were carried out using Feret’s diameter obtained from 3D tumour volumetry. Feret’s diameter is less prone to inter-observer variability and represents a more realistic estimate of tumour diameter because it is independent of the spatial orientation of both the tumour and its longest axis [This study has limitations. We performed a single-centre study, and our results might therefore not be fully representative of clinical practice at other hospitals. However, we applied fractal analysis to a commonly used CT imaging protocol including unenhanced, pancreatic parenchymal, and portal-venous phases; however, some centres prefer to use CT protocols without an unenhanced scan. We did not investigate dual-energy CT (DECT), which has the potential to improve contrast-to-noise ratio and tumour conspicuity in low monochromatic energy images and iodine density images and allows reconstruction of virtual unenhanced images . Howeverest axis .In summary, our study establishes fractal dimension as an imaging biomarker that improves size measurement of PDA in CT imaging based on visualising perfusion chaos. Our study demonstrates consistent underestimation of PDA lesion size, in terms of both diameter and volume, whereas FD maps calculated from CT correlated well with mpMRI and gross pathology. Chaos of perfusion might be a relevant pathophysiological aspect that potentially explains incomplete tumour depiction on CT imaging.


The prediction accuracy of pulse pressure variation (PPV) for fluid responsiveness was proposed to be unreliable in low tidal volume (Vt) ventilation. It was suggested that changes in PPV obtained by transiently increasing Vt to 8 ml/kg accurately predicted fluid responsiveness even in subjects receiving low Vt. We assessed whether the changes in PPV induced by a Vt challenge predicted fluid responsiveness in our critically ill subjects ventilated with low Vt 6 ml/kg.This study is a prospective single-center study. PPV and other parameters were measured at a Vt of 6 mL/kg, 8 mL/kg, and after volume expansion. The prediction accuracy of PPV and other parameters for fluid responsiveness before and after tidal volume challenge was also analyzed using receiver operating characteristic (ROC) curves.6 showed unsatisfactory predictive capability with an area under the curve (AUC) of 0.69  at a Vt of 6 mL/kg. PPV8 andΔPPV6–8 showed good predictive capability with an AUC of 0.90  and 0.90  respectively. The corresponding cutoff values were 11% for PPV8 and 2% for ΔPPV6–8.Thirty-one of the 76 subjects enrolled in the study were responders (41%). Respiratory system compliance of all subjects decreased significantly (26 ± 4.3). The PPV values were significantly higher in the responder group than the non-responder group before (8.8 ± 2.7 vs 6.8 ± 3.1) or after (13.0 ± 1.7 vs 8.5 ± 3.0) Vt challenge. In the receiver operating characteristic curve (ROC) analysis, PPVPPV shows a poor operative performance as a predictor of fluid responsiveness in critically ill subjects ventilated with a tidal volume of 6 mL/ kg. Vt challenge could improve the predictive accuracy of PPV to a good but not excellent extent when respiratory system compliance decreased significantly.The online version contains supplementary material available at 10.1186/s12871-022-01676-8. Pulse pressure variation (PPV) has been used to predict preload fluid responsiveness in mechanically ventilated subjects. PPV interpretation is doubtful during low tidal volume ventilation , which is increasingly used in ICU subjects. Some studies suggested temporary tidal volume (Vt) challenge could improve the prediction accuracy of PPV. However, reports regarding the effect of the Vt challenge were conflicting.What this paper contributes to our knowledge.PPV shows a poor operative performance as a predictor of fluid responsiveness in critical care subjects ventilated with a tidal volume of 6 mL/ kg. Vt challenge could improve the predictive accuracy of PPV to a good but not excellent extent in the context of lung protective ventilation when respiratory system compliance decreased significantly.Fluid therapy is the primary resuscitation maneuver of acute circulatory failure management in critically ill subjects . Both unNevertheless, PPV interpretation is doubtful during low tidal volume ventilation , which is increasingly used in ICU subjects, especially those with sepsis and acute respiratory distress syndrome , 9. SomeTo evaluate the validity of the Vt challenge, we performed a study on septic shock patients with or without ARDS who were receiving low tidal mechanical ventilation. We also compared the ability of PPV to predict fluid responsiveness  with additional parameters.Subjects with septic shock who received low tidal mechanical ventilation between October 2017 to May 2020 in the Department of Critical Care Medicine at West China Hospital were screened in the study. The study protocol was reviewed and approved by the Ethics Committee of West China Hospital of Sichuan University (No. 2018–88), and written informed consent was obtained from the subjects' guardians or next of kin.2/FiO2 < 300 mm Hg and a minimum positive end-expiratory pressure ≥ 5 cm H2O, that was not fully explained by cardiac failure or fluid overload  and moderately sedated [Richmond Agitation-Sedation Scale (RASS) score − 3] state , 18. RASThe heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), CCI, PPV, central venous pressure (CVP), plateau pressure (Pplat), positive end-expiratory pressure (PEEP), driving pressure (Pplat – PEEP), and static compliance of the respiratory system (Cst) were recorded at baseline and specific intervals Fig. . All res8 (PPV at 8 ml/kg PBW) and other parameters were recorded during the 15 s before the end of the 2 min period. Then Vt was reduced back to 6 mL/kg PBW again for 2 min and relevant parameters were recorded (baseline 2). After that, 250 ml of crystalloid fluid bolus was given over 15 min, and measurements were repeated during the 1 min before the end of the 15 min period. Subjects were considered to be responders if there was an increase in the CITPTD of more than 15% after giving a fluid bolus at Vt 6 mL/kg PBW. Doses of vasoactive medications and PEEP were held constant. The change in PPV after transiently increasing tidal volume (ΔPPV6-8)was calculated.Firstly, all subjects were ventilated in volume-controlled mode with a Vt 6 ml/kg predicted body weight (PBW) at baseline (baseline 1). Secondly, the "tidal volume challenge" was conducted by transiently increasing Vt to 8 mL/kg PBW for 2 min. Following this procedure, PPVp < 0.05 was considered to be significantly different. Receiver operating characteristic (ROC) curves of PPV and other parameters were plotted under different tidal volume values. The Youden method was used to identify the threshold values of PPV and other parameters and to identify optimal sensitivity and specificity for diagnosing the volume responsiveness of subjects [Measurement data conforming to a normal distribution were reported as mean ± SD; data that did not conform to a normal distribution are reported as the medians (25–75% interquartile range). Enumeration data were reported as frequency (percentage). The two groups of measurement data were compared with independent samples Student's t-test . The Wilcoxon rank-sum test was used for data that did not conform to a normal distribution, and the chi-squared test or Fisher's exact test was utilized to compare two groups of enumeration data. Paired sample t-test or a signed rank-sum test was used to compare paired data. An alpha value of subjects . The difsubjects . The samsubjects . Accordisubjects . Under tn = 3), right ventricular dysfunction (n = 3), or abdominal compartment syndrome (n = 2). Four of the remaining guardians declined to sign informed consent. Data from 2 patients were excluded because of unstable baseline PPV. In the end, 76 subjects were analyzed . However, eight of the 90 subjects were excluded because of cardiac arrhythmias  were identified as responders because CO increased by greater than or equal to 15% after fluid challenge. Comparisons between responders and nonresponders are also shown in Table p = 0.025) and GEDVI  in the responders were lower than those in the nonresponders, while the PPV  and CITPTDin the responder group were higher than those found in the nonresponder group.It was found that the CVP  at the end of the Vt challenge while Cst remained the same. Before the fluid challenge, CVP, PPV, and GEDVI were recorded when a tidal volume of 6 ml/kg ventilation was performed (baseline 1). It was found that PPV (6.8 ± 3.1 vs 8.8 ± 2.7), CCI (2.88 ± 0.58 vs 3.14 ± 0.40), and CITPTD (2.89 ± 0.58 vs 3.16 ± 0.36) in the nonresponder group was lower than in the responder group, and the CVP (9.8 ± 2.0 vs 8.6 ± 2.5) and GEDVI (810 ± 88 vs 743 ± 119) in the nonresponder group were higher than those found in the responder group.The changes in hemodynamic parameters related to tidal volume challenge and fluid challenge are presented in Table When 8 mL/kg Vt ventilation was performed, it was observed that CVP (11.1 ± 2.3 vs 9.9 ± 2.4) remained higher while PPV (8.5 ± 3.0 vs 13.0 ± 1.7) was still lower in the nonresponder group than in the responder group. PPV increased in both groups. However, the change extent of PPV in the responder group was more significant (4.2 ± 1.6 vs 1.7 ± 1.1). The changing size of CVP showed no difference between the responder group and the nonresponder group. At baseline 2, all hemodynamic parameters in both groups were similar to those measured at baseline 1 (baseline 1 vs baseline 2). After the fluid challenge, CVP increased in both groups while PPV decreased in responder groups. Meanwhile, no significant difference could be noted in GEDVI in both groups.6 was limited with an AUC of 0.69 . While PPV8 significantly improved predictive ability with an AUC of 0.90 . The predictive power of ΔPPV6–8 was similar to PPV8 with an AUC of 0.90 . CCI, CVP6, CVP8 and ΔCVP6–8 showed weak predictability for fluid responsiveness with AUCs of 0.67 , 0.67 , 0.68  and 0.52  respectively. The optimal threshold values of PPV8 and ∆PPV6–8 were 11%  and 2%  respectively  can predict fluid responsiveness with similar predictive capability compared to PPV8. The optimal threshold of ∆PPV6–8 was > 2%.This study demonstrated that PPV was not reliable in predicting fluid responsiveness in our subjects under protective ventilation. However, the predictive ability could be enhanced by increasing the tidal volume from 6 ml/kg to 8 ml/kg temporarily. The tidal volume challenge did not improve the predictive power of CVP. Absolute change in PPV values obtained by the Vt challenge  seemed a little lower than those reported in that study . One of the possible reasons for these results was that subjects enrolled in our study had lower static compliance of the respiratory system than those enrolled in that study ( 26 ± 4 vs 29 ± 8). As it had been suggested, pulse pressure variation became less accurate for predicting fluid responsiveness when the compliance of the respiratory system was ≤ 30 ml/cm H2O [Our study showed that performing a tidal volume challenge mildly enhanced the reliability of the PPV test. Similar to our results, another study developed by Myatra confirmed that change in PPV after a "Vt challenge" reliably predicted fluid responsiveness . Howeverl/cm H2O .Our study also suggested that baseline central venous pressure did not accurately predict fluid responsiveness. This finding was consistent with the results of many other studies , 29. HowAnother interesting finding in our study was that CCI in the responder group was higher than in the non-responder group (3.14 ± 0.40 vs 2.88 ± 0.58), which appeared to contribute to fluid responsiveness prediction mildly (AUC 0.67). The possible mechanism behind this observation was that a subject's response to fluids depends on both preload and cardiac contractility. Fluid responsiveness could only be predicted accurately in cases with normal ventricular contractility . We suppThe present study had the following limitations. First, we did not measure fluctuation of intrapleural pressure. It was pointed out that PPV adjusted by respiratory variations in pleural pressure could improve the prediction of fluid responsiveness . HoweverThe change in PPV following the Vt challenge test has good but not exceptional reliability in predicting fluid responsiveness in subjects with low respiratory system compliance employing small tidal volume ventilation.Additional file 1.


The study was aimed to elucidate the influence of passage number of 4T1 cells for the development of the ideal tumour model.A total of 24 female BALB/c mice was divided equally into three groups: i) control ; ii) group A (subjected to 4T1 cells of passage number 9) and iii) group B (subjected to 4T1 cells of passage number 10). The injections were introduced at the 3rd mammary pad of the mice. The net volume of the tumours was examined. Histopathological analysis was conducted to compare the extent of metastasis in the different groups of mice.P = 0.042). The coefficient of variation in the net volume of 4T1 tumour for group A was higher (135.3%) as compared to group B (40.79%). Group A only exhibited metastasis on the lungs, liver and spleen whereas group B showed metastasis to the heart, spleen, lungs and liver.Group B had a higher net volume of 4T1 tumour as compared to group A (The use of 4T1 cells from passage number 10 is more ideal for the development of 4T1 tumour. The 4T1 mice model is a well-known model that has been widely used in research to study breast cancer –7. TherePassage number is the number of times, in which a cell culture has been sub-cultured and determining the ideal passage number can make or break an experiment. In the current study, we have attempted to develop a 4T1 orthotopic mice model by introducing 4T1 cells at the 3rd mammary fat pad of female BALB/c mice. The detailed protocol published by Pulaski and Ostrand-Rosenberg . HoweverAccording to a study by Hoon, Wang and Ramshaw , passagiSince passage number could play a role in modifying the biological profile of the culture cell, we have attempted to incorporate a similar idea in the development of 4T1 orthotopic mice. In the present study, we aimed to highlight the influence of the passage number of 4T1 cells on the volume of the 4T1 tumour bore by the host throughout the duration of tumour development and the pattern of tumour growth. Additionally, we would also like to compare the difference in the volume of 4T1 tumour between different passage numbers at five-week points of tumour development. The variation in the net volume of the 4T1 tumour due to the difference in passage numbers and the extent of metastasis within the hosts, were studied as well.n = 8 in each group) of mice in this study: i) control mice group; ii) group A (subjected to passage number 9: hereafter referred to as P9) and iii) group B (subjected to passage number 10: hereafter referred to as P10). The animal study was conducted at the Animal Research and Service Centre (ARASC), Universiti Sains Malaysia (USM), Health Campus, Kelantan, Malaysia. The ethical approval for the animal study was granted by the Institutional Animal Care and Use Committee (IACUC), USM.A total of 24 female BALB/c mice aged around 5–6 weeks old were used to develop the 4T1 tumour. There were three groups (The 4T1 cells were purchased from the American Type Culture Collection (ATCC) and cultured using complete DMEM media (Gibco), supplemented with 10% foetal bovine serum (FBS) (Gibco) and 1% antibiotics (penicillin and streptomycin) (Gibco). For groups A and B, cells from P9 and P10 were harvested using 0.25% Trypsin (Gibco), respectively. For P9 cells, the stock cells were retrieved from the cryovial which was originally from P7 whereas for P10 cells, the stock cells were retrieved from the cryovial that was originally from P8. Therefore, the sub-cultivation process was only performed once for both batches of cells regardless of their passage number.5 4T1 cells were isolated and introduced subcutaneously at the 3rd mammary fat pad of the BALB/c mice, in groups A and B. For the control mice, 200 μL of PBS was introduced at a similar site.Irrespective of the assigned passage number, the procedure for the preparation of 4T1 orthotopic injection was the same for both groups A and B. Approximately, 200 μL of 1×102 × diameter .Standard haematoxylin and eosin staining was used on paraffin-embedded target organs for histological examination of metastases. Stained sections were examined for signs of metastasis and photographed using Olympus BX41 light microscope and CellSensor software, respectively.t-test was conducted for parametric analyses and the Mann-Whitney U test was conducted for non-parametric analyses.Graphpad Prism 8 software was used to generate the statistical analyses. The error bars either represent standard deviation (SD) or interquartile range (IQR). For the data that consisted of more than two groups with repeated measures, the Friedman test and its post-hoc analysis, Wilcoxon signed-rank test with Bonferroni’s corrections were carried out. For the analysis that involved only two groups, independent In both groups A and B, palpable tumour generally appeared after 14 days of the introduction of the 4T1 orthotopic injection. In group A, palpable tumour was only present in six out of eight mice with varying sizes of tumour observed. Based on the physical appearance, only two mice displayed a larger size of tumour compared to the other four mice. Some prominent physical and behavioural changes were noted in these two mice which included pulled ears, rapid breathing, inactiveness and changes in the fur pattern from smooth to coarse . However(A)–(C) represents the normal physical appearance of the control mice: (A) The absence of palpable 4T1 tumour at the 3rd mammary fat pad of the control mouse. (B) The fur-coat of the control mouse was smooth till the end of the experimental duration. (C) The lids of the eyes of the control mouse did not appear as droopy. The lower panel (D)–(E) represents the physical appearance of the 4T1 orthotopic mice: (D) The fur-coat of the 4T1 orthotopic mouse seemed coarse (marked by the black circle) and the eyes lids were droopy (marked by the black arrow) at week 5. (E) There was a palpable tumour on the 3rd mammary fat pad of the 4T1 orthotopic mouse at week 5 (marked by the black circle)The upper panel In group B, the development of palpable tumour was successful in all eight mice with less variation in the size of tumour observed. Based on the physical appearance, by week 4 (day 22–28), all the mice showed extreme changes in their physical appearance. Among the changes noted were changes in the fur pattern, pulled ears, droopy eyes, breathing difficulties and reduced mobility due to the restriction caused by the growing 4T1 tumour . HoweverDespite the reduction in the size of the tumour noted in group B at week 5, the mass of pellet consumed was the lowest in that particular week as compared to the other weeks of tumour development . In addiP = 0.0005) and B (P = 0.0018). In group A, the tumour development seemed stagnant from week 2–4 and in week 5, a drastic increase was observed. In group B, the experimental variability is slightly lower and exhibits a biphasic pattern. The post-hoc test revealed none of the pairs within groups A  (t-test. The mean (SD) of net 4T1 tumour volume for group A was 1.74 (2.35) and for group B, it was higher, 4.01 (1.63). The co-efficient of variation in the net volume of 4T1 tumour retrieved from group A was 135.30%. However, the variation in the net volume was only 40.79% in group B. The differences in the variation were prominent based on the dot-plot presented  , using aresented .The histology of the 4T1 tumour included the presence of spindle-shaped tumour cells and infiltration of leukocytes . The hisThe 4T1 cells share similar molecular features as those noted in the triple-negative subtype of human breast cancer , which mInvasion and metastasis are generally influenced by various expressions of genes –15 and tBesides Hamad, Kqueen and Hashim , severalIn the present study, it was noted that the introduction of P9 cells reduces the capacity of the host to bear the invasiveness of cancer cells, which is reflected by the restriction in the duration of tumour development (only 30 days). The drastic increase resulted in a significant variability in the tumour volume of group A. The sudden increase in the tumour volume at week 5 may have affected the durability of the host to bear the fast-growing tumour. However, the scenario was majorly contributed only by two mice which bore the largest tumour volume in group A, thus providing little evidence on the lethal effect of P9 cells. Since a lower passage number of cells has higher chances of forming invadopodia as discussed previously, we assume that the invasiveness of P9 might be responsible for the signs of early death of 4T1 orthotopic mice and may not have distal metastatic potential. This is because metastasis was only observed in the lungs, liver and spleen of 4T1 orthotopic mice of group A. Sotillo et al.  highlighBased on the histopathological analysis, only group B (subjected to P10) showed signs of metastasis to all the target organs. However, the severity of metastasis on the target organs did not reduce the duration of tumour development. The tumour-bearing mice of group B even reported improved overall health by week 5 and slightly reduced variability in the tumour volume throughout the 6 weeks of tumour development, unlike in group A. During week 5, mice of group A showed signs of dying as described earlier. Despite the fact that, group B exhibited significantly higher 4T1 tumour volume, the overall health of mice in group B was better compared to group A.The greater extent of metastasis exhibited by P10 is in agreement with the findings reported by De Meulenaere et al. . The stuBased on the data generated from group A, it was evident that P9 contributes to a larger variation in the net volume of 4T1 tumour among BALB/c mice, as compared to P10. By using a higher passage number, the variation was reduced by 94.51%. In addition, the 4T1 tumours resected from group B (P10) exhibited a significantly larger mean of 4T1 tumour net volume with a lower standard deviation in comparison to those of group A (P9). Thus, compelling us to believe that the influence of passage number on the chromosomal stability or gene expression could play a role in the differences in the biological aspects of the development of 4T1 tumour and the absence of palpable tumour in some of the experimental BALB/c mice.In the present study, a higher passage number (P10) has clearly shown to have provided a sort of stability in terms of the capacity of the mice to resist the invasiveness of the 4T1 cells up to a certain extent and thus, allowing the progression of distal metastasis. The experiment conducted using P10, was observed to have prevented early death among the 4T1 orthotopic mice and was able to prolong the duration of 4T1 tumour growth up to week 6 (42 days). In a study by Tao et al. , it was The pattern of tumour growth displayed by group A (P9) over 30 days varied tremendously as compared to those of group B (P10) over 42 days. Group A displayed a stagnant development in the mean volume of the 4T1 tumour from weeks 2–5 whereas group B exhibited biphasic pattern of tumour growth with a drop in the 4T1 tumour volume in week 5. Our findings in the pattern of tumour development exhibited by group B are in agreement with those reported by Tao et al. . The stuThe non-significant differences in the pattern of 4T1 tumour growth observed in group A (P9) clearly showed that the progress of tumour development was not ideal and rather, it can be described as stagnant. However, the significant differences were reported in the weekly volume of 4T1 tumour among mice of group B (P10). The fluctuation and significant differences in the 4T1 tumour volume within different weeks validate the ongoing physiological progress within the host against the growing tumour.Furthermore, tumour development did not occur at all in some of the mice in group A indicating an early rejection which is in contrast with the findings from group B. In group B, all eight mice bore 4T1 tumour at the end of the tumour development. According to an analysis by Schrörs et al. , 4T1 shaJudging by the pattern of the tumour development in groups A and B, the presentation of 4T1 antigens (immunogenicity) to the immune system could differ among passages. The relapse in the tumour development of group B, could be a result of immune evasion  and may The attempt to highlight the role of passage number in the formation of in vivo 4T1 tumours was the paper’s greatest strength, given no previous research had been done in this area. This will assist future experiments involving the 4T1 mice model and reduce the cost required for optimisation. In terms of limitations, we believe that metastasis-related gene expression analysis should be added to further our understanding of the reasons behind the differences in tumour volume and metastatic pattern within one passage number difference. Moreover, due to the absence of gene expression analysis, we were not able to postulate as to why mice subjected to P9 showed early signs of dying as compared to P10. In future, we wish to look at the influence of other passage numbers, apart from P9 and P10, with the assistance of gene expression analysis.In a nutshell, P10 is a more ideal option for growing 4T1 tumour in BALB/c mice as compared to P9.The use of P10 prolongs the duration of tumour growth that could be endured by the host;P10 showed a biphasic pattern of the 4T1 tumour growth;the use of P10 reduced the variation in the net volume of the 4T1 tumour among the experimental BALB/c mice; andthe use of P10 to develop 4T1 orthotopic mice showed better prospects in the extent of metastasis within the hosts.


Radiotherapy is a major treatment option for patients with brain metastasis. However, response to radiotherapy is highly varied among the patients, and it may take months before the response of brain metastasis to radiotherapy is apparent on standard follow-up imaging. This is not desirable, especially given the fact that patients diagnosed with brain metastasis suffer from a short median survival. Recent studies have shown the high potential of machine learning methods for analyzing quantitative imaging features (biomarkers) to predict the response of brain metastasis before or early after radiotherapy. However, these methods require manual delineation of individual tumours on imaging that is tedious and time-consuming, hindering further development and widespread application of these techniques. Here, we investigated the impact of using less accurate but automatically generated tumour outlines on the efficacy of the derived imaging biomarkers for radiotherapy response prediction. Our findings demonstrate that while the effect of tumour delineation accuracy is considerable for automatic contours with low accuracy, imaging biomarkers and prediction models are rather robust to imperfections in the produced tumour masks. The results of this study open the avenue to utilizing automatically generated tumour contours for discovering imaging biomarkers without sacrificing their accuracy.Significantly affecting patients’ clinical course and quality of life, a growing number of cancer cases are diagnosed with brain metastasis (BM) annually. Stereotactic radiotherapy is now a major treatment option for patients with BM. However, it may take months before the local response of BM to stereotactic radiation treatment is apparent on standard follow-up imaging. While machine learning in conjunction with radiomics has shown great promise in predicting the local response of BM before or early after radiotherapy, further development and widespread application of such techniques has been hindered by their dependency on manual tumour delineation. In this study, we explored the impact of using less-accurate automatically generated segmentation masks on the efficacy of radiomic features for radiotherapy outcome prediction in BM. The findings of this study demonstrate that while the effect of tumour delineation accuracy is substantial for segmentation models with lower dice scores (dice score ≤ 0.85), radiomic features and prediction models are rather resilient to imperfections in the produced tumour masks. Specifically, the selected radiomic features (six shared features out of seven) and performance of the prediction model  were fairly similar for the ground-truth and automatically generated segmentation masks, with dice scores close to 0.90. The positive outcome of this work paves the way for adopting high-throughput automatically generated tumour masks for discovering diagnostic and prognostic imaging biomarkers in BM without sacrificing accuracy. While the exact incidence of brain metastasis (BM) is difficult to determine, about 70,000 to 400,000 new cases of BM are annually diagnosed in the United States alone . The incRadiation therapy, chemotherapy, immunotherapy, and surgery are the main treatment options for the management of metastatic brain tumours. Because systemic therapy often fails to penetrate the blood–brain barrier, local brain-directed therapies such as radiation or neurosurgical resection are commonly used , althougSince the conventional response assessment is based on the changes in tumour size following treatment, it may take months before a local response is apparent on standard follow-up images. This is not desirable, especially given the fact that patients diagnosed with BM suffer from a short median survival. To make things more complicated, lesion enlargement after treatment on MRI is not necessarily a sign of tumour progression, but also of a condition known as pseudoprogression due to adverse radiation effect .To mitigate these complications, and since the local response is highly varied even among the patients going through the same treatment regimen (because of the patient and/or tumour-related factors), there have been efforts to develop a tailored treatment strategy based on the patient’s subgroup and predicted survival . Early eThe successful application of artificial intelligence (AI) for diagnostic purposes has led to the development of AI-based cancer imaging analysis, which is now being employed to meet more sophisticated therapeutic requirements, such as patient stratification and therapy outcome prediction. Neuroimaging data can be used to extract quantitative and semiquantitative image features that are often beyond human vision. Given the abundance of MRI and CT data acquired as part of the standard of care for patients with BM, there is a huge amount of data available for mining useful prognostic features to help with response prediction before or early after therapy. Radiomics has been introduced as a formal approach for extracting and discovering quantitative diagnostic and prognostic features from medical images . The quaNew studies have shown connections between tumour radiomic signatures and their phenotypes, genomic, and proteomic profiles ,20,21,22In quantitative cancer imaging and radiomics, the entire tumour volume should be segmented to determine the region of interest (ROI) for analysis. The segmented tumour boundaries also determine other relevant regions such as the peritumoural areas for further analysis. Therefore, accurate tumour delineation is a fundamental step in oncologic radiomics. Manual segmentation of tumour on volumetric images acquired at several imaging sessions for each patient is a tedious and time-consuming job. Automatic segmentation of tumours facilitates radiomic analyses and streamlines the standard process of therapy outcome evaluation in clinic considerably, possibly at the cost of less accuracy.In this paper, we evaluate the impact of tumour segmentation accuracy on efficacy of the quantitative MRI biomarkers for radiotherapy outcome prediction in BM. A cascaded attention-guided framework is proposed to accurately segment the tumour on the baseline and first follow-up automatically. Using the segmentation masks generated with this framework, we extracted radiomic biomarkers associated with the tumour and peritumoural areas from T1-weighted (T1w) and T2-weighted fluid attenuation inversion recovery (T2-FLAIR) MR images to develop predictive models of radiotherapy outcome. The study results show that to extract meaningful and distinguishing biomarkers, tumour masks should be reasonably accurate but not necessarily matching completely the ground-truth identified manually by expert clinicians. In particular, the results of outcome prediction using the ground-truth and the automatically generated masks are comparable with the top selected biomarkers shared between the two approaches.This research was carried out in compliance with the institutional research ethics board approval from Sunnybrook Health Sciences Centre, Toronto, ON, Canada. The imaging data were obtained from 124 patients who had been diagnosed with BM and were treated with hypofractionated SRT over five fractions. Gadolinium contrast-enhanced T1w and T2-FLAIR images were acquired before the treatment (baseline) and at the first follow-up after SRT. Both the T1w and the T2-FLAIR had an in-plane resolution of 0.5 mm. The slice thickness for the T1w and T2-FLAIR images was 1.5 mm and 5 mm, respectively. T2-FLAIR images were coregistered on the T1w images, and both images were resampled to make the voxel size isotropic  with a Gaussian kernel was adapted as the classifier for outcome prediction because of its demonstrated performance, versatility coming from different kernels, and effectiveness in high-dimensional space . The selAccurate segmentation of brain tumours on the baseline and follow-up images is an essential yet laborious task. It is required for therapy response assessment as well as for extracting imaging biomarkers in various diagnostic and prognostic applications. An automatic segmentation method streamlines the therapy outcome prediction and evaluation workflow , potentially at the cost of less accuracy. In this study, we investigated the effect of tumour segmentation accuracy on efficacy of the MRI radiomic biomarkers extracted from the tumour and tumour margin for radiotherapy outcome prediction in BM. The results of our study show that while the impact of tumour delineation accuracy is considerable for less accurate segmentation models (dice score ≤ 0.85), the radiomic features and prediction models are relatively robust to imperfections in the generated tumour masks. In particular, the list of selected features associated with the ground-truth tumour masks and those generated using the cascaded 2D and 3D UNets + MSGA model (with an average dice score of about 0.90) shared six out of the seven features selected based on the mRMR method. Furthermore, the features extracted using the tumour masks generated by this segmentation model resulted in an outcome prediction model with fairly close performance metrics to those obtained by the ground-truth model, including the accuracy, sensitivity, specificity, AUC, and F1-score of 80% vs. 80%, 77% vs. 83%, 83% vs. 78%, 0.78 vs. 0.81, and 77% vs. 78%, respectively. Progression-free survival analyses demonstrated that both the outcome prediction models could stratify the patients into two cohorts (low-risk vs. high-risk) with statistically significantly different survival curves.The effect of segmentation accuracy on the performance of radiomic features for different cancer sites and imaging modalities is a subject yet to be explored in the literature. Among research done so far, Jin et al. studied the effect of automatic segmentation using multiple UNet-based architectures on the accuracy of radiomic features for transvaginal ultrasound images of cervical cancer . The resThe findings of this study show that radiomics in conjunction with machine learning can be used to predict radiotherapy outcome in brain metastasis early after treatment, where automatic tumour segmentation could potentially be utilized instead of manual segmentation to facilitate prediction model development and investigation. In clinic, these implications could be significant, as an early prediction of treatment response may lead to therapy adjustments which, in turn, enhance patients’ survival and quality of life. The observation of this study that radiotherapy outcome prediction in brain metastasis is not very sensitive to small inaccuracies in tumour segmentation permits high-throughput implementation and exploration of new computational prediction models to develop robust systems for clinical decision support.The promising results of this study open the avenue to applying automatically generated segmentation masks for discovering diagnostic and prognostic biomarkers in BM without sacrificing their accuracy. This is a significant contribution considering the heavy burden that manual segmentation imposes on image-guided therapeutic systems in neuro-oncology, including the models for therapy outcome prediction and the platforms for therapy outcome evaluation. While the findings of this paper are promising and pave the way for future research, future investigations are required to further assess the conclusions of this study on a larger scale when imaging data are available from larger patient cohorts and possibly multicenter studies.


Posttherapy, in vivo tumour retention of [18F]AlF-mNOTA-GZP was correlated to changes in tumour volume and tumour-infiltrating immune cells. [18F]AlF-mNOTA-GZP successfully stratified response to immune checkpoint inhibition in the syngeneic HEPA 1-6 model. FACS indicated significant changes in the immune environment including a decrease in immune suppressive CD4+ T regulatory cells and increases in tumour-associated GZB+ NK+ cells, which correlated well with tumour radiopharmaceutical uptake. While the immune response to ICI therapies differs in HCC compared to many other cancers, [18F]AlF-mNOTA-GZP retention is able to stratify response to ICI therapy associated with tumour infiltrating GZB+ NK+ cells in this complex tumour microenvironment.Hepatocellular carcinoma (HCC) is a notoriously difficult cancer to treat. The recent development of immune checkpoint inhibitors has revolutionised HCC therapy; however, successful response is only observed in a small percentage of patients. Biomarkers typically used to predict treatment response in other tumour types are ineffective in HCC, which arises in an immune-suppressive environment. However, imaging markers that measure changes in tumour infiltrating immune cells may supply information that can be used to determine which patients are responding to therapy posttreatment. We have evaluated [ First-lβ-Ala-Gly-Gly-Ile-Glu-Phe-Asp-CHO (mNOTA-GZP) and characterisation details have been described previously [18F]AlF-mNOTA-GZP has also been described previously [18F]fluoride ion was produced via the [18O18F] nuclear reaction (GE PETtrace 860 cyclotron). Quality control analytical radio-HPLC was performed on a UFLC Shimazdu HPLC system equipped with dual-wavelength UV detector and a NaI/PMT-radiodetector . Radioactivity measurements were made with a CRC-55tPET dose calibrator . [18F]AlF-mNOTA-GZP was formulated as a colourless solution of 10% ethanol in saline (pH = 7.4) with a nondecay corrected radiochemical yield of 12-18%, a radiochemical purity of 99%, and molar activity of 50-81 GBq/μmol (n = 3) after a total reaction and purification time of 50 minutes.The synthesis of NOTA–eviously . The radeviously . No-carrμg/mL streptomycin at 37°C in a humidified atmosphere at 5% CO2. HEPA 1-6 cells were mixed 1 : 1 with Matrigel (Sigma) and injected subcutaneously into the right shoulder with a final concentration of 2X10 [6] per mouse. Tumour volumes were quantified using Vernier by callipers every 3 days from day 6 after tumour implantation. Tumour volumes were calculated as previously described using the modified ellipsoid formula (0.5 × Length × Width [2]).Animal procedures adhered to Institutional Animal Care and Use Committee Singapore regulations (IACUC No. 181399). C57/BL6 mice were acquired from In Vivos (Singapore) at 6-8 weeks of age, housed at standard room temperature with food and water provided ad libitum. HEPA 1-6 cells were purchased from ATCC, cultured in RPMI supplemented with 10% FBS, 100 U/mL penicillin, and 100 α-trinitrophenol mAb), rat IgG2a anti-mouse PD-1 (αPD1 mAb RMP1-14), and mouse IgG2b anti-mouse CTLA-4 (αCTLA4 mAb 9D9)) and dosed by intraperitoneal (i.p.) injection on days 6, 9, and 12 after tumour implantation .Immune checkpoint inhibitor antibodies were purchased from Bio-X Cell (rat IgG2a isotype control (Response to therapy was determined using tumour growth inhibition (%TGI) on day 19 as previously described using the formula %TGI = (Vc − Vt)/(Vc − Vo) × 100  unless otherwise indicated.All data sets were assessed for normal distribution and analysed using GraphPad Prism 8.0.0. A Kruskal-Wallis 1-way ANOVA with a Dunn's posttest was used for analysis , and tumour volumes varied depending on the treatment regime and individual response . Successful response to therapy was determined based on tumour volumes at day 19 using a reductionist approach, which separated the tumours into treatment responders  or treatment nonresponders (TNR) depending on final tumour volume at day 19. The cut-off value used to determine TRs was derived from the mean of the control group , those tumours with volumes less than 190 mm3 were designated as TR and all others as TNR , αCTLA4 , and combined αPD1 + αCTLA4 , when compared to the TNR group .We analysed the changes in HEPA 1-6 tumour uptake of different infiltrating immune cells in response to therapy, and t-SNE and Rphenoptype clustering were used to determine immunophenotypic changes across the different treatment arms comparing each TR group against the TNR group . Many im18F]AlF-mNOTA-GZP was significantly higher in treatment responsive tumours compared to TNRs (The liver is a tolerogenic organ, able to regulate immune responses to a constant stream of antigens from the gut , this im to TNRs ; howeverRecently, new granzyme B targeting tracers have been developed whose tumour retention is dependent on granzyme B proteolytic activity as opposed to the current aldehyde tracer which quantifies the amount of biochemically active GZMB molecules at the tumour . One of 18F]AlF-mNOTA-GZP demonstrates the ability to accurately stratify ICI response in HCCs, showing that granzyme B radiopharmaceuticals can be used across multiple tumour types, including those arising in immune suppressive environments. While the immune response to ICI therapies differs in HCC compared to many other cancers, granzyme B may still be a potential biomarker for immunotherapy efficacy in liver cancer providing useful information to help improve patient management.Overall, [


Adenovirus (AdV) is a common cause of acute respiratory illness (ARI). Multiple respiratory AdV types have been identified in humans, but it remains unclear which are the most common in U.S. children with ARI.We conducted a multicenter, prospective viral surveillance study at seven U.S. children’s hospitals, the New Vaccine Surveillance Network, during 12/1/16–11/30/19, prior to the COVID-19 pandemic. Children < 18 years of age seen in the emergency department or hospitalized with fever and/or respiratory symptoms were enrolled, and mid-turbinate nasal +/- throat swabs were tested using multiplex respiratory pathogen assays or real time polymerase chain reaction (PCR) test for AdV, respiratory syncytial virus (RSV), human metapneumovirus, rhinovirus/enterovirus (RV), influenza, parainfluenza viruses, and endemic coronaviruses. AdV-positive specimens were subsequently typed using single-plex qPCR assays targeting sequences in the hexon gene specific for types 1-7, 11, 14, 16 and 21. Demographics, clinical characteristics, and outcomes were compared between AdV types.Figure 1a). Demographic and clinical characteristics varied by AdV types, including age, race/ethnicity, smoke exposure, daycare/school attendance, and hospitalization (Table 1). Co-detection with other viruses was common among all AdV types, with RV and RSV being the most frequently co-detected . Fever and cough were the most common symptoms for all AdV types . Children with AdV-7 detected as single pathogen had higher odds of hospitalization .Of 29,381 enrolled children, 2,106 (7.2%) tested positive for AdV. The distribution of types among the 1,330 (63.2%) successfully typed specimens were as follows: 31.7% AdV-2, 28.9% AdV-1, 15.3% AdV-3, 7.9% AdV-5, 5.9% AdV-7, 1.4% AdV-4, 1.2% AdV-6, 0.5% AdV-14, 0.2% AdV-21, 0.1% AdV-11, and 7.0% ≥1 AdV type. Most children with AdV-1 or AdV-2 detection were < 5 years of age , FIDSA, F(AAM), BioFire: Grant/Research Support|Luminex: Grant/Research Support John Williams, MD, GlaxoSmithKline: Advisor/Consultant|Quidel: Advisor/Consultant Mary A. Staat, MD, MPH, Centers for Disease Control and Prevention: Grant/Research Support|Cepheid: Grant/Research Support|National Institute of Health: Grant/Research Support|Uptodate: Royalties Christopher J Harrison, MD, Astellas: Grant/Research Support|GSK: Grant/Research Support|Merck: Grant/Research Support|Pediatric news: Honoraria|Pfizer: Grant/Research Support Mary E. Moffatt, M.D., Becton and Dickinson and Company: Stocks/Bonds|Biogen: Stocks/Bonds|Coloplast B: Stocks/Bonds|Express Scripts: Stocks/Bonds|Novo Nordisk A/S Spons ADR: Stocks/Bonds|Novo Nordisk A/S-B: Stocks/Bonds|Steris PLC: Stocks/Bonds|Stryker Corp: Stocks/Bonds|Thermo Fisher Scientific: Stocks/Bonds Geoffrey A. Weinberg, MD, Merck & Co.: Honoraria|Merck & Co.: Honoraria for composing and reviewing textbook chapters, Merck Manual of Therapeutics Janet A. Englund, MD, AstraZeneca: Advisor/Consultant|AstraZeneca: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Meissa Vaccines: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Grant/Research Support|Sanofi Pasteur: Advisor/Consultant Natasha B. Halasa, MD, Quidel: Grant/Research Support|Quidel: equipment donation|Sanofi: Grant/Research Support|Sanofi: HAI testing and vaccine donation.


Mycobacterium smegmatis mc2155. DuncansLeg has a 75,593-bp circular genome that contains 126 predicted protein-coding genes and 10 tRNA genes. DuncansLeg is assigned to actinobacteriophage cluster L3.Bacteriophage DuncansLeg is a siphovirius isolated in 2021 from soil on the Coastal Carolina University campus in Conway, South Carolina, using the host  Actinobacteria within the genus Mycobacterium are of biomedical interest as potential therapeutics for treating patients infected with mycobacterial pathogens, such as Mycobacterium abscessus . Using standard protocols  as measured using ImageJ software (https://imagej.nih.gov/ij).Bacteriophages that target bscessus . Here, wncansLeg  displaye9 PFU/mL) of DuncansLeg using the Promega Wizard DNA cleanup kit and prepared for sequencing on an Illumina MiSeq platform (v3 reagents) using the New England BioLabs (NEB) Ultra II library kit. This sequencing protocol resulted in 361,011 single-end 150-bp reads across the DuncansLeg genome, providing 677-fold coverage. Untrimmed reads were assembled using Newbler v2.9 and then were checked for completeness with Consed v29 following the methods outlined in Russell (TCGATCAGCC-3′). Based upon a gene content similarity of 35% or higher to phages in the Actinobacteriophage database (http://phagesDB.org) and using previously described criteria, DuncansLeg is assigned to subcluster L3  and then manually refined using PECAAN (http://discover.kbrinsgd.org) and Starterator v1.0.1 (https://seaphages.org/software/#Starterator). In total, 136 protein-coding genes were predicted for DuncansLeg, of which functions could be assigned to 50 predicted genes using Phamerator v472  no. SRX14443497.DuncansLeg is available at GenBank with accession no.