Antigen-Clustered Nanovaccine Achieves Long-Term Tumor Remission by Promoting B/CD 4 T Cell Crosstalk.

Current cancer vaccines using T cell epitopes activate antitumor T cell immunity through dendritic cell/macrophage-mediated antigen presentation, but they lack the ability to promote B/CD4 T cell crosstalk, limiting their anticancer efficacy. We developed antigen-clustered nanovaccine (ACNVax) to achieve long-term tumor remission by promoting B/CD4 T cell crosstalk. The topographic features of ACNVax were achieved using an iron nanoparticle core attached with an optimal number of gold nanoparticles, where the clusters of HER2 B/CD4 T cell epitopes were conjugated on the gold surface with an optimal intercluster distance of 5-10 nm. ACNVax effectively trafficked to lymph nodes and cross-linked with BCR, which are essential for stimulating B cell antigen presentation-mediated B/CD4 T cell crosstalk in vitro and in vivo. ACNVax, combined with anti-PD-1, achieved long-term tumor remission (>200 days) with 80% complete response in mice with HER2+ breast cancer. ACNVax not only remodeled the tumor immune microenvironment but also induced a long-term immune memory, as evidenced by complete rejection of tumor rechallenge and a high level of antigen-specific memory B, CD4, and CD8 cells in mice (>200 days). This study provides a cancer vaccine design strategy, using B/CD4 T cell epitopes in an antigen clustered topography, to achieve long-term durable anticancer efficacy through promoting B/CD4 T cell crosstalk.

Two-stage hydrothermal oxygenation for efficient removal of Cr(VI) by starch-based polyporous carbon: Wastewater application and removal mechanism.

Cr(VI) is of concern because of its high mobility and toxicity. In this work, a two-stage hydrothermal strategy was used to activate the O sites of starch, and by inserting K-ion into the pores, starch-based polyporous carbon (S-PC) adsorption sites was synthesized for removal of Cr(VI). Physicochemical characterization revealed that the O content of the S-PC reached 20.66 % after activation, indicating that S-PC has excellent potential for adsorption of Cr(VI). The S-PC removal rate for 100 mg/L Cr(VI) was 96.29 %, and the adsorption capacity was 883.86 mg/g. Moreover, S-PC showed excellent resistance to interference, and an equal concentration of hetero-ions reduced the activity by less than 5 %. After 8 cycles of factory wastewater treatment, the S-PC maintained 81.15 % of its original activity, which indicated the possibility of practical application. Characterization and model analyses showed that the removal of Cr(VI) from wastewater by the S-PC was due to CC, δ-OH, ν-OH, and C-O-C groups, and the synergistic effect of adsorption and reduction was the key to the performance. This study provides a good solution for treatment of Cr(VI) plant wastewater and provides a technical reference for the use of biological macromolecules such as starch in the treatment of heavy metals.

Integrating Full Bayesian Inference and Student's t-Distribution Method for Enhanced Outlier Handling in Caffeine Population Pharmacokinetics: Assessing Drug-Drug Interactions with Enasidenib in Relapsed or Refractory AML and MDS Patients.

As the first-in-class, selective, and potent inhibitor of the isocitrate dehydrogenase-2 (IDH2) mutant protein, enasidenib was approved by the US Food and Drug Administration (FDA) in 2017 for the treatment of adult patients with relapsed or refractory acute myeloid leukemia (AML) with an IDH2 mutation. Known for its interactions with various cytochrome P450 (CYP) enzymes and transporters in vitro, a clinical pharmacokinetics (PK) trial was initiated to assess the impact of multiple doses of enasidenib on the single-dose PK of sensitive probe substrates of several cytochrome P450 enzymes and transporters. In this study, a population pharmacokinetic analysis approach was employed to address challenges posed by high, nonzero baseline caffeine concentrations. Moreover, we integrated full Bayesian inference into this approach innovatively for a more detailed understanding of parameter uncertainty and greater modeling flexibility, alongside Student's t-distribution for robust error modeling in handling the abnormal outlier caffeine concentration data observed in this trial. Our analyses demonstrated that multiple doses of enasidenib altered caffeine clearance to a clinically meaningful extent, as evidenced by an approximate 8-fold decrease. This finding led to a specific recommendation in the package insert to avoid the concurrent use of certain CYP1A2 substrates with enasidenib, unless directed otherwise in the prescribing information. Furthermore, this research underlines the technical benefits of integrating full Bayesian inference and incorporating Student's t-distribution for residual error modeling in the PK field.

Exploring Transformer Model in Longitudinal Pharmacokinetic/Pharmacodynamic Analyses and Comparing with Alternative Natural Language Processing Models.

There remains a substantial need for a comprehensive assessment of various natural language processing (NLP) algorithms in longitudinal pharmacokinetic/pharmacodynamic (PK/PD) modeling despite recent advances in machine learning in the space of quantitative pharmacology. We herein investigated the application of the transformer model and further compared the performance among several different NLP models, including long short-term memory (LSTM) and neural-ODE (Ordinary Differential Equation) in analyzing longitudinal PK/PD data using virtual data containing three different regimens. Results suggested that LSTM and neural-ODE, along with their respective variants provide a strong performance when predicting from training-included (seen) regimens, albeit with slight information loss for training-excluded (unseen) regimens. Similarly, as with neural-ODE, the transformer exhibited superior performance in describing time-series PK/PD data. Nonetheless, when extrapolating to unseen regimens, while outlining the general data trends, it encountered difficulties in precisely capturing data fluctuations. Remarkably, a small integration of unseen data into the training dataset significantly bolsters predictive performance for both seen and unseen regimens. Our study marks a pioneering effort in deploying the transformer model for time-series PK/PD analysis and provides a systematic exploration of the currently available NLP models in this field.

Effects of Straw Returning and New Fertilizer Substitution on Rice Growth, Yield, and Soil Properties in the Chaohu Lake Region of China.

Recently, replacing chemical fertilizers with straw returning and new fertilizers has received considerable attention in the agricultural sector, as it is believed to increase rice yield and improve soil properties. However, less is known about rice growth and soil properties in paddy fields with the addition of different fertilizers. Thus, in this paper, we investigated the effects of different fertilizer treatments, including no fertilization (CK), optimized fertilization based on the medium yield recommended fertilizer amount (OF), 4.50 Mg ha-1 straw returning with chemical fertilizers (SF), 0.59 Mg ha-1 slow-release fertilizer with chemical fertilizers (SRF), and 0.60 Mg ha-1 water-soluble fertilizer with chemical fertilizers (WSF), on rice growth, yield, and soil properties through a field experiment. The results show that compared with the OF treatment, the new SF, SRF, and WSF treatments increased plant height, main root length, tiller number, leaf area index, chlorophyll content, and aboveground dry weight. The SF, SRF, and WSF treatments improved rice grain yield by 30.65-32.51% and 0.24-1.66% compared to the CK and OF treatments, respectively. The SRF treatment increased nitrogen (N) and phosphorus (P) uptake by 18.78% and 28.68%, the harvest indexes of N and P by 1.75% and 0.59%, and the partial productivity of N and P by 2.64% and 2.63%, respectively, compared with the OF treatment. However, fertilization did not significantly affect the average yield, harvest indexes of N and P, and partial productivity of N and P. The contents of TN, AN, SOM, TP, AP, and AK across all the treatments decreased significantly with increasing soil depth, while soil pH increased with soil depth. The SF treatment could more effectively increase soil pH and NH4+-N content compared to the SRF and WSF treatments, while the SRF treatment could greatly enhance other soil nutrients and enzyme activities compared to the SF and WSF treatments. A correlation analysis showed that rice yield was significantly positively associated with tiller number, leaf area index, chlorophyll, soil NO3--N, NH4+-N, SOM, TP, AK, and soil enzyme activity. The experimental results indicate that SRF was the best fertilization method to improve rice growth and yield and enhance soil properties, followed by the SF, WSF, and OF treatments. Hence, the results provide useful information for better fertilization management in the Chaohu Lake region of China.

The efficacy and safety of low-dose rituximab in the treatment of pemphigus vulgaris: a cohort study.

BACKGROUND: Rituximab (RTX) is considered the first-line treatment for pemphigus vulgaris (PV), which is a B-cell-mediated acquired autoimmune disease. However, no consensus on the optimum dosage has been achieved. OBJECTIVES: To investigate the efficacy and safety of low-dose RTX (a single infusion of 500 mg) for the treatment of PV, a cohort study was conducted for patients with PV, along with a 12-month follow-up following the administration of RTX. METHODS: Patients with moderate or severe PV were divided into group A (low-dose RTX combined with corticosteroids) and group B (corticosteroids alone). Data on complete remission (CR) rates, doses of corticosteroids, cumulative doses of corticosteroids at the third, sixth, and twelfth months, pemphigus disease area index and adverse effects (AEs) were collected. RESULTS: Forty-four patients with moderate or severe PV were enrolled in this study (19 in group A and 25 in group B). Patients treated with low-dose RTX had higher CR rates, lower doses of corticosteroids at the third, sixth, and twelfth months, lower cumulative doses of corticosteroids at the sixth and twelfth months, and fewer AEs than those who received corticosteroids alone. CONCLUSIONS: This study indicated that low-dose RTX may be a beneficial and secure therapy option for patients with moderate to severe PV.

Ultrasound-based detection of inflammatory changes for early diagnosis and risk model construction of psoriatic arthritis.

OBJECTIVES: Psoriatic arthritis (PsA) is the most prevalent coexisting condition associated with psoriasis. Early-stage PsA patients always present unspecific and subtle clinical manifestations causing delayed diagnosis and leading to unfavorable health outcomes. The application of ultrasound enables precise identification of inflammatory changes in musculoskeletal structures. Hence, we constructed ultrasound models to aid early diagnosis of PsA. METHODS: This is a cross-sectional study carried out in the Department of Dermatology at West China Hospital (October 2018-April 2021). All participants underwent thorough ultrasound examinations. Participants were classified into the under 45 group (18 ≤ age ≤ 45) and over 45 group (age > 45) and then randomly grouped into derivation and test cohort (7:3). Univariable logistic regression, least absolute shrinkage and selection operator, and multivariable logistic regression visualized by nomogram were conducted in order. Receiver operating characteristic (ROC), calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CICA) were performed for model verification. RESULTS: A total of 1256 participants were included, with 767 participants in the under 45 group and 489 in the over 45 group. Eleven and sixteen independent ultrasonic variables were finally selected to construct the under 45 and over 45 model with the area under the ROC of 0.83 (95%CI: 0.78-0.87) and 0.83 (95%CI: 0.78-0.88) in derivation cohort, respectively. The DCA and CICA analyses showed good clinical utility of the two models. CONCLUSION: The implementation of the ultrasound models could streamline the diagnostic process for PsA in psoriasis patients, leading to expedited evaluations while maintaining diagnostic accuracy.

A gastrointestinal locally activating Janus kinase inhibitor to treat ulcerative colitis.

In this study, we integrated machine learning (ML), structure-tissue selectivity-activity-relationship (STAR), and wet lab synthesis/testing to design a gastrointestinal (GI) locally activating JAK inhibitor for ulcerative colitis treatment. The JAK inhibitor achieves site-specific efficacy through high local GI tissue selectivity while minimizing the requirement for JAK isoform specificity to reduce systemic toxicity. We used the ML model (CoGT) to classify whether the designed compounds were inhibitors or noninhibitors. Then we used the regression ML model (MTATFP) to predict their IC50 against related JAK isoforms of predicted JAK inhibitors. The ML model predicted MMT3-72, which was retained in the GI tract, to be a weak JAK1 inhibitor, while MMT3-72-M2, which accumulated in only GI tissues, was predicted to be an inhibitor of JAK1/2 and TYK2. ML docking methods were applied to simulate their docking poses in JAK isoforms. Application of these ML models enabled us to limit our synthetic efforts to MMT3-72 and MMT3-72-M2 for subsequent wet lab testing. The kinase assay confirmed MMT3-72 weakly inhibited JAK1, and MMT3-72-M2 inhibited JAK1/2 and TYK2. We found that MMT3-72 accumulated in the GI lumen, but not in GI tissue or plasma, but released MMT3-72-M2 accumulated in colon tissue with minimal exposure in the plasma. MMT3-72 achieved superior efficacy and reduced p-STAT3 in DSS-induced colitis. Overall, the integration of ML, the structure-tissue selectivity-activity-relationship system, and wet lab synthesis/testing could minimize the effort in the optimization of a JAK inhibitor to treat colitis. This site-specific inhibitor reduces systemic toxicity by minimizing the need for JAK isoform specificity.

Fault Detectability of Asynchronous Switched Boolean Networks: A Set Reachability Approach.

This article addresses the fault detectability problem of asynchronous switched Boolean networks, which is focused on whether occurrence of the faults would have an impact on the outputs of the considered network. By applying the semi-tensor product method, the asynchronous switching scheme of the considered system is converted into multiple switching signals. Based on them, an augmented system is established to transform the fault detectability issue of the original system into a set reachability problem. Moreover, some criteria for the fault detectability of the asynchronous switched Boolean control networks are also proposed. Additionally, two algorithms are given to design feasible control sequences after explicitly analyzing the considered augmented system. Finally, an example is provided to illustrate the significance of the obtained theoretical results.

Enhancement of Cr(VI) adsorption on lignin-based carbon materials by a two-step hydrothermal strategy: Performance and mechanism.

Cr(VI) is a carcinogenic heavy metal that forms an oxygen-containing anion, which is difficult to remove from water by adsorbents. Here, industrial alkali lignin was transformed into a Cr(VI) adsorbent (N-LC) by using a two-step hydrothermal strategy. The characterization results of the adsorbent showed that O and N were uniformly distributed on the surface of the adsorbent, resulting in a favorable morphology and structure. The Cr(VI) adsorption of N-LC was 13.50 times that of alkali lignin, and the maximum was 326.10 mg g-1, which confirmed the superiority of the two-step hydrothermal strategy. After 7 cycles, the adsorption of N-LC stabilized at approximately 62.18 %. In addition, in the presence of coexisting ions, N-LC showed a selective adsorption efficiency of 85.47 % for Cr(VI), which is sufficient to support its application to actual wastewaters. Model calculations and characterization showed that N and O groups were the main active factors in N-LC, and CO, -OH and pyridinic-N were the main active sites. This study provides a simple and efficient method for the treatment of heavy metals and the utilization of waste lignin, which is expected to be widely applied in the environmental, energy and chemical industries.

Effects of continuous straw returning on bacterial community structure and enzyme activities in rape-rice soil aggregates.

Straw returning is an effective management measure to improve or maintain soil fertility in agricultural ecosystems. This study investigated the effects of straw returning combined with compound fertilizer on the bacterial community, enzyme activities, and soil nutrients' contents in a rape-rice rotation soil aggregates. To do so, a 5-year field trial (November 2016 to October 2021) was carried out in a paddy soil with three treatments: no straw + no fertilization (CK), compound fertilizer (F), and straw returning + compound fertilizer (SF). Soil aggregates were classified into mega-aggregates (> 2 mm), macro-aggregates (0.25-2 mm), micro-aggregates (0.053-0.25 mm), and silt-clay (< 0.053 mm) using the wet sieve method. High-throughput sequencing was employed to characterize the bacterial community, and Pearson correlation coefficient was used to identify the relationships among bacterial community, organic carbon, nitrogen, phosphorus, and enzyme activities in soil aggregates. Compared with F, the results showed that straw returning increased the content of > 2 mm aggregates by 3.17% and significantly decreased the content of 0.053-0.25 mm aggregates by 20.27%. The contents of organic carbon and total nitrogen in > 0.053 mm straw amended aggregates increased by 15.29 and 18.25%, respectively. Straw returning significantly increased the urease activity of > 0.053 mm aggregates with an average of 43.08%, while it decreased the phosphatase and invertase activities of soil aggregates by 7.71-40.66%. The Shannon indices of the bacterial community in each particle sizes soil aggregates decreased by an average of 1.16% and the Chao indices of the bacterial community in < 2 mm aggregates increased by an average of 3.90% in straw amended soils. Nevertheless, the relative abundances of Chloroflexi and Nitrospirotain in all soil aggregates increased by 6.17-71.77% in straw amended soils. Altogether, our findings suggest that straw returning is an efficient approach to enhance soil structure, carbon and nitrogen contents, and the richness of soil bacterial diversity.

Feasibility and preclinical efficacy of CD7-unedited CD7 CAR T cells for T cell malignancies.

Chimeric antigen receptor (CAR)-mediated targeting of T lineage antigens for the therapy of blood malignancies is frequently complicated by self-targeting of CAR T cells or their excessive differentiation driven by constant CAR signaling. Expression of CARs targeting CD7, a pan-T cell antigen highly expressed in T cell malignancies and some myeloid leukemias, produces robust fratricide and often requires additional mitigation strategies, such as CD7 gene editing. In this study, we show fratricide of CD7 CAR T cells can be fully prevented using ibrutinib and dasatinib, the pharmacologic inhibitors of key CAR/CD3ζ signaling kinases. Supplementation with ibrutinib and dasatinib rescued the ex vivo expansion of unedited CD7 CAR T cells and allowed regaining full CAR-mediated cytotoxicity in vitro and in vivo on withdrawal of the inhibitors. The unedited CD7 CAR T cells persisted long term and mediated sustained anti-leukemic activity in two mouse xenograft models of human T cell acute lymphoblastic leukemia (T-ALL) by self-selecting for CD7-, fratricide-resistant CD7 CAR T cells that were transcriptionally similar to control CD7-edited CD7 CAR T cells. Finally, we showed feasibility of cGMP manufacturing of unedited autologous CD7 CAR T cells for patients with CD7+ malignancies and initiated a phase I clinical trial (ClinicalTrials.gov: NCT03690011) using this approach. These results indicate pharmacologic inhibition of CAR signaling enables generating functional CD7 CAR T cells without additional engineering.

Application of chelate GLDA for remediating Cd-contaminated farmlands using Tagetes patula L.

In the present study, via a 180-day field trial, the indicators of soil total cadmium, DTPA-Cd, organic matter, and plant cadmium extraction were tested after the application of chelate tetrasodium glutamate diacetate (GLDA) to investigate the potential of GLDA combined with Tagetes patula L. to remediate cadmium-contaminated soil. To do so, five GLDA treatments (e.g., 0, 292.5, 585, 1170, and 2340 kg hm-2) were practiced. For each treatment, the total GLDA was divided into two applications with 15-day intervals (0.25, 0.47, and 0.61 mg·kg-1) under T. patula plantation. Compared with the control, our results showed that GLDA application significantly increased the biomass of aerial parts of T. patula by 21.9% (p < 0.05). Likewise, Cd content in aboveground and underground parts of T. patula increased by 94.7% and 60.5%, respectively, compared with the control (p < 0.05). GLDA application caused significant increases in Cd accumulations in cell soluble fraction and cell wall by 290% and 123%, respectively (p < 0.05); soil pH and DTPA-Cd content increased with the increase of total application of GLDA. Co-application of GLDA (2340 kg hm-2) and T. patula reduced the total soil Cd content by 12.87% compared with the soil background. Altogether, our findings conclude on the efficacy of GLDA application for the remediation of Cd-contaminated farmlands under T. patula cultivation.

[Effects of Continuous Straw Returning with Chemical Fertilizer on the Carbon Pool and Crop Yield of Rice-Rape Rotation Soils].

According to the positioning experiment of straw returning in the continuous field 7a, the effects of straw returning combined with chemical fertilizer on soil total organic carbon (TOC), dissolved organic carbon (DOC), particulate organic carbon (POC), labile organic carbon (LOC), carbon pool management index (CPMI), and crop yield in farmland soil profiles (0-20, 20-50, and 50-80 cm) in the Chaohu Lake area were studied. There were four treatments:no straw returning+no fertilization (CK), conventional fertilization (F), straw returning+conventional fertilization (SF1), and straw returning+80% conventional fertilization (SF2). The changes in soil total organic carbon and component content, CPMI, and rape rice yield in different soil layers were analyzed. Taking CK as a reference, conventional fertilization and straw returning combined with chemical fertilizer increased the content of total organic carbon and components in the soil vertical profile, and the content of total organic carbon and components in different soil layers decreased gradually with the increase in soil depth. In the 0-20 cm soil layer, compared with that in the F treatment, the SF1 and SF2 treatments significantly increased the contents of TOC, DOC, POC, and LOC by 14.23%-28.97%, 7.86%-27.01%, 16.46%-24.24%, and 5.89%-6.64%, respectively (P<0.05). In the 20-50 cm soil layer, the contents of TOC and LOC in SF1 were significantly increased by 9.43% and 8.34%, respectively, compared with those in the F treatment (P<0.05), and the contents of DOC and POC in SF2 were significantly increased by 17.51% and 65.83% compared with those in the F treatment (P<0.05). In the 50-80 cm soil layer, there was no significant difference in the contents of total organic carbon and components among the treatments. The effect of straw returning and chemical fertilizer on the soil carbon pool management index was significant. SF1 significantly improved the CPMI of the 0-50 cm soil layer compared with that in the F treatment, whereas the CPMI of the F treatment was the largest in the 50-80 cm soil layer; however, there was no significant difference among all treatments. Straw returning combined with chemical fertilizer had a significant effect on crop yield, and the yield of the SF1 treatment was the highest; compared with that of the F treatment, the rice, rape, and annual yields were significantly increased by 6.19%, 7.67%, and 6.54%, respectively (P<0.05). In general, straw returning combined with chemical fertilizer was of great significance to improve the soil carbon pool, soil fertility, and crop yield in the Chaohu Lake area.

Chemical forms of cadmium in soil and its distribution in French marigold sub-cells in response to chelator GLDA.

The use of degradable chelating agents to facilitate phytoextraction is a promising low-cost method for the remediation of heavy metal-contaminated soils. However, there are few studies on how plants and soils respond to the chelating agents. In this study, the responses of French marigold (Tagetes patula L.) and soil cadmium (Cd) to the chelator tetrasodium glutamate (GLDA) was investigated in a 180 d field trial. Five GLDA treatments (0, 292.5, 585, 1170, and 2340 kg hm-2) were carried out in a Cd-contaminated soil (0.47 mg kg-1) under French marigold plantation. The results showed that the application of GLDA promoted the transformation of other forms of Cd in soil to exchangeable state, and the exchangeable Cd and Fe-Mn oxide bound state increased by 42.13% and 32.97% (p < 0.05), respectively. The cell wall Cd accumulations significantly increased 9.39% (p < 0.05) and the percentages of soluble fractions increased by 460.33% (p < 0.05). Furthermore, increases occurred in soil pH, as well as DOC and DTPA-Cd contents with increasing the total amount of GLDA. The composite application of GLDA (2340 kg hm-2) with French marigold reduced the total soil Cd content by 7.59% compared with the soil background. Altogether, results of this study suggested that the application of GLDA can effectively activate soil Cd and enhance the capability of French marigold for the remediation of Cd-contaminated soils.

Optimization of the Prodrug Moiety of Remdesivir to Improve Lung Exposure/Selectivity and Enhance Anti-SARS-CoV-2 Activity.

COVID-19 patients with severe symptoms still lack antiviral treatment options. Although remdesivir is the only FDA-approved drug for those patients, its efficacy is limited by premature hydrolysis to nucleoside (NUC), low accumulation in the disease-targeted tissue (lungs), and low antiviral potency. In this study, we synthesized a new series of remdesivir analogues by modifying the ProTide moiety. In comparison with remdesivir, the lead compound MMT5-14 showed 2- to 7-fold higher antiviral activity in four variants of SARS-CoV-2. By reducing premature hydrolysis in hamsters, MMT5-14 increased the prodrug concentration by 200- to 300-fold in the plasma and lungs but also enhanced lung accumulation of the active metabolite triphosphate nucleosides (NTP) by 5-fold. Compared to remdesivir, MMT5-14 also increased the intracellular uptake and activation in lung epithelial cells by 4- to 25-fold. These data suggest that MMT5-14 could be a potential antiviral drug to treat COVID-19 patients with severe symptoms.

Why 90% of clinical drug development fails and how to improve it?

Ninety percent of clinical drug development fails despite implementation of many successful strategies, which raised the question whether certain aspects in target validation and drug optimization are overlooked? Current drug optimization overly emphasizes potency/specificity using structure‒activity-relationship (SAR) but overlooks tissue exposure/selectivity in disease/normal tissues using structure‒tissue exposure/selectivity-relationship (STR), which may mislead the drug candidate selection and impact the balance of clinical dose/efficacy/toxicity. We propose structure‒tissue exposure/selectivity-activity relationship (STAR) to improve drug optimization, which classifies drug candidates based on drug's potency/selectivity, tissue exposure/selectivity, and required dose for balancing clinical efficacy/toxicity. Class I drugs have high specificity/potency and high tissue exposure/selectivity, which needs low dose to achieve superior clinical efficacy/safety with high success rate. Class II drugs have high specificity/potency and low tissue exposure/selectivity, which requires high dose to achieve clinical efficacy with high toxicity and needs to be cautiously evaluated. Class III drugs have relatively low (adequate) specificity/potency but high tissue exposure/selectivity, which requires low dose to achieve clinical efficacy with manageable toxicity but are often overlooked. Class IV drugs have low specificity/potency and low tissue exposure/selectivity, which achieves inadequate efficacy/safety, and should be terminated early. STAR may improve drug optimization and clinical studies for the success of clinical drug development.

Structure‒tissue exposure/selectivity relationship (STR) correlates with clinical efficacy/safety.

Drug optimization, which improves drug potency/specificity by structure‒activity relationship (SAR) and drug-like properties, is rigorously performed to select drug candidates for clinical trials. However, the current drug optimization may overlook the structure‒tissue exposure/selectivity-relationship (STR) in disease-targeted tissues vs. normal tissues, which may mislead the drug candidate selection and impact the balance of clinical efficacy/toxicity. In this study, we investigated the STR in correlation with observed clinical efficacy/toxicity using seven selective estrogen receptor modulators (SERMs) that have similar structures, same molecular target, and similar/different pharmacokinetics. The results showed that drug's plasma exposure was not correlated with drug's exposures in the target tissues (tumor, fat pad, bone, uterus), while tissue exposure/selectivity of SERMs was correlated with clinical efficacy/safety. Slight structure modifications of four SERMs did not change drug's plasma exposure but altered drug's tissue exposure/selectivity. Seven SERMs with high protein binding showed higher accumulation in tumors compared to surrounding normal tissues, which is likely due to tumor EPR effect of protein-bound drugs. These suggest that STR alters drug's tissue exposure/selectivity in disease-targeted tissues vs. normal tissues impacting clinical efficacy/toxicity. Drug optimization needs to balance the SAR and STR in selecting drug candidate for clinical trial to improve success of clinical drug development.

Albumin nanoparticle containing a PI3Kγ inhibitor and paclitaxel in combination with α-PD1 induces tumor remission of breast cancer in mice.

Immunomodulators that remodel the tumor immunosuppressive microenvironment have been combined with anti-programmed death 1 (α-PD1) or anti-programmed death ligand 1 (α-PDL1) immunotherapy but have shown limited success in clinical trials. However, therapeutic strategies to modulate the immunosuppressive microenvironment of lymph nodes have been largely overlooked. Here, we designed an albumin nanoparticle, Nano-PI, containing the immunomodulators PI3Kγ inhibitor (IPI-549) and paclitaxel (PTX). We treated two breast cancer mouse models with Nano-PI in combination with α-PD1, which remodeled the tumor microenvironment in both lymph nodes and tumors. This combination achieved long-term tumor remission in mouse models and eliminated lung metastases. PTX combined with IPI-549 enabled the formation of a stable nanoparticle and enhanced the repolarization of M2 to M1 macrophages. Nano-PI not only enhanced the delivery of both immunomodulators to lymph nodes and tumors but also improved the drug accumulation in the macrophages of these two tissues. Immune cell profiling revealed that the combination of Nano-PI with α-PD1 remodeled the immune microenvironment by polarizing M2 to M1 macrophages, increasing CD4+ and CD8+ T cells, B cells, and dendritic cells, decreasing regulatory T cells, and preventing T cell exhaustion. Our data suggest that Nano-PI in combination with α-PD1 modulates the immune microenvironment in both lymph nodes and tumors to achieve long-term remission in mice with metastatic breast cancer, and represents a promising candidate for future clinical trials.

A Distributed Lyapunov-Based Redesign Approach for Heterogeneous Uncertain Agents With Cooperation-Competition Interactions.

A swarming behavior problem is investigated in this article for heterogeneous uncertain agents with cooperation-competition interactions. In such a problem, the agents are described by second-order continuous systems with different intrinsic nonlinear terms, which satisfies the "linearity-in-parameters" condition, and the agents' models are coupled together through a distributed protocol containing the information of competitive neighbors. Then, for four different types of cooperation-competition networks, a distributed Lyapunov-based redesign approach is proposed for the heterogeneous uncertain agents, where the distributed controller and the estimation laws of unknown parameters are obtained. Under their joint actions, the heterogeneous uncertain multiagent system can achieve distributed stabilization for structurally unbalanced networks and output bipartite consensus for structurally balanced networks. In particular, the concept of coherent networks is proposed for structurally unbalanced directed networks, which is beneficial to the design of distributed controllers. Finally, four illustrative examples are given to show the effectiveness of the designed distributed controller.