bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Figure S1 from Biomarker Identification and Risk Prediction Model Development for Differentiated Thyroid Carcinoma Lung Metastasis Based on Primary Lesion Proteomics
Authors: Peng Xiaoqi , Zhao Hongbo , Ye Lijuan , Hou Fei , Yi Zihan , Ren Yanxin , Lu Lin , Chen Fukun , Lv Juan , Wang Yinghui , Cai Haolin , Zheng Xihua , Yang Qing , Chen Ting
Published: July 2024

Figure S1. Statistical chart of protein identification results.
Supplementary Figure S5 from MYC Inhibition Potentiates CD8+ T Cells Against Multiple Myeloma and Overcomes Immunomodulatory Drug Resistance
Authors: Davis Lorraine N. , Walker Zachary J. , Reiman Lauren T. , Parzych Sarah E. , Stevens Brett M. , Jordan Craig T. , Forsberg Peter A. , Sherbenou Daniel W.
Published: July 2024

Supplemental Figure S5. Effects of MYCi975 on immune checkpoint and cytokine expression.
Supplementary Figure S4 from MYC Inhibition Potentiates CD8+ T Cells Against Multiple Myeloma and Overcomes Immunomodulatory Drug Resistance
Authors: Davis Lorraine N. , Walker Zachary J. , Reiman Lauren T. , Parzych Sarah E. , Stevens Brett M. , Jordan Craig T. , Forsberg Peter A. , Sherbenou Daniel W.
Published: July 2024

Supplemental Figure S4. Effect of 1 μM MYCi975 on CD4+ T cells and healthy donor T cells.
Supplementary Table S8 from Clinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers
Authors: Son Ji , Zhang Yingao , Lin Heather , Mirallas Oriol , Alvarez Ballesteros Pablo , Nardo Mirella , Clark Natalie , Hillman R. Tyler , Campbell Erick , Holla Vijaykumar , Johnson Amber M. , Biter Amadeo B. , Yuan Ying , Cobb Lauren P. , Gershenson David M. , Jazaeri Amir A. , Lu Karen H. , Soliman Pamela T. , Westin Shannon N. , Euscher Elizabeth D. , Lawson Barrett C. , Yang Richard K. , Meric-Bernstam Funda , Hong David S.
Published: July 2024

Co-mutation analysis of gynecologic cancers with KRAS G12C-mutation
Supplementary Table 1 from Cervicovaginal Metabolome and Tumor Characteristics for Endometrial Cancer Detection and Risk Stratification
Authors: Lorentzen Georgia M. , Łaniewski Paweł , Cui Haiyan , Mahnert Nichole D. , Mourad Jamal , Borst Matthew P. , Willmott Lyndsay , Chase Dana M. , Roe Denise J. , Herbst-Kralovetz Melissa M.
Published: July 2024

Breakdown of diagnoses of hyperplasia and endometrial cancer subtypes. Values are n (%). Benign diagnosis breakdown is not included as these participants had a mixture of both singular and co-occurring conditions such as adenomyosis, endometriosis, and fibroids.
Supplementary Table S3 from Clinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers
Authors: Son Ji , Zhang Yingao , Lin Heather , Mirallas Oriol , Alvarez Ballesteros Pablo , Nardo Mirella , Clark Natalie , Hillman R. Tyler , Campbell Erick , Holla Vijaykumar , Johnson Amber M. , Biter Amadeo B. , Yuan Ying , Cobb Lauren P. , Gershenson David M. , Jazaeri Amir A. , Lu Karen H. , Soliman Pamela T. , Westin Shannon N. , Euscher Elizabeth D. , Lawson Barrett C. , Yang Richard K. , Meric-Bernstam Funda , Hong David S.
Published: July 2024

(a) Univariate and (b) multivariable analyses of factors associated with overall survival in gynecologic cancer patients undergoing somatic molecular profiling
Supplementary Figure1 from Cervicovaginal Metabolome and Tumor Characteristics for Endometrial Cancer Detection and Risk Stratification
Authors: Lorentzen Georgia M. , Łaniewski Paweł , Cui Haiyan , Mahnert Nichole D. , Mourad Jamal , Borst Matthew P. , Willmott Lyndsay , Chase Dana M. , Roe Denise J. , Herbst-Kralovetz Melissa M.
Published: July 2024

MetOrigin analysis reveals origin of metabolites. Origin was determined based on information from KEGG and HMDB information.
Supplementary Table S1 from Clinical and Genomic Landscape of RAS Mutations in Gynecologic Cancers
Authors: Son Ji , Zhang Yingao , Lin Heather , Mirallas Oriol , Alvarez Ballesteros Pablo , Nardo Mirella , Clark Natalie , Hillman R. Tyler , Campbell Erick , Holla Vijaykumar , Johnson Amber M. , Biter Amadeo B. , Yuan Ying , Cobb Lauren P. , Gershenson David M. , Jazaeri Amir A. , Lu Karen H. , Soliman Pamela T. , Westin Shannon N. , Euscher Elizabeth D. , Lawson Barrett C. , Yang Richard K. , Meric-Bernstam Funda , Hong David S.
Published: July 2024

Unique somatic molecular profiling panels used to test RAS in gynecologic cancer patients
Supplementary Figure S3 from Toripalimab Plus Bevacizumab as First-line Treatment for Advanced Hepatocellular Carcinoma: A Prospective, Multicenter, Single-Arm, Phase II Trial
Authors: Chen Yajin , Du Chengyou , Shen Shunli , Zhang Wu , Shan Yunfeng , Lyu Ang , Wu Jianhui , Shang Changzhen , Luo Xuan , Wei Jinxing , Xiao Heng , Qiu Jianguo , Hua Yunpeng , Wang Shutong , Wang Ting , Dai Shengjie , Zhang Shuhao , Xie Bingying , Wu Yinghao , Hao Chunyi
Published: July 2024

PFS by ALBI grade
Supplementary Figure S1 from Toripalimab Plus Bevacizumab as First-line Treatment for Advanced Hepatocellular Carcinoma: A Prospective, Multicenter, Single-Arm, Phase II Trial
Authors: Chen Yajin , Du Chengyou , Shen Shunli , Zhang Wu , Shan Yunfeng , Lyu Ang , Wu Jianhui , Shang Changzhen , Luo Xuan , Wei Jinxing , Xiao Heng , Qiu Jianguo , Hua Yunpeng , Wang Shutong , Wang Ting , Dai Shengjie , Zhang Shuhao , Xie Bingying , Wu Yinghao , Hao Chunyi
Published: July 2024

Patient disposition
Supplementary Table S2 from Phase II Study to Determine the Antitumor Activity and Safety of Simlukafusp Alfa (FAP-IL2v) Combined with Atezolizumab in Esophageal Cancer
Authors: Prenen Hans , Deva Sanjeev , Keam Bhumsuk , Lindsay Colin R. , Lugowska Iwona , Yang James C. , Longo Federico , de Miguel Maria , Ponz-Sarvise Mariano , Ahn Myung-Ju , Gumus Mahmut , Champiat Stephane , Italiano Antoine , Salas Sébastien , Perets Ruth , Arslan Cagatay , Cho Byoung C. , Evers Stefan , Boetsch Christophe , Marbach Daniel , Dejardin David , Sleiman Nassim , Ardeshir Caroline , Richard Muriel , Charo Jehad , Kraxner Anton , Keshelava Nino , Teichgräber Volker , Moreno Victor
Published: July 2024

Duration of most common AEs (reported in ≥20% of patients)
Supplementary Results S1 from Phase II Study to Determine the Antitumor Activity and Safety of Simlukafusp Alfa (FAP-IL2v) Combined with Atezolizumab in Esophageal Cancer
Authors: Prenen Hans , Deva Sanjeev , Keam Bhumsuk , Lindsay Colin R. , Lugowska Iwona , Yang James C. , Longo Federico , de Miguel Maria , Ponz-Sarvise Mariano , Ahn Myung-Ju , Gumus Mahmut , Champiat Stephane , Italiano Antoine , Salas Sébastien , Perets Ruth , Arslan Cagatay , Cho Byoung C. , Evers Stefan , Boetsch Christophe , Marbach Daniel , Dejardin David , Sleiman Nassim , Ardeshir Caroline , Richard Muriel , Charo Jehad , Kraxner Anton , Keshelava Nino , Teichgräber Volker , Moreno Victor
Published: July 2024

Class-specific adverse events
Supplementary Table S4 from Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors
Authors: Zhao Yue , Hu Zheyi , Bathena Sai Praneeth , Keidel Sarah , Miller-Moslin Karen , Statkevich Paul , Bello Akintunde , Roy Amit , Suryawanshi Satyendra
Published: July 2024

Parameter Estimates of the Full Nivolumab Population Pharmacokinetic Model
Supplementary Figure S9 from Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors
Authors: Zhao Yue , Hu Zheyi , Bathena Sai Praneeth , Keidel Sarah , Miller-Moslin Karen , Statkevich Paul , Bello Akintunde , Roy Amit , Suryawanshi Satyendra
Published: July 2024

Distribution of Model Predicted Relatlimab Exposures (Cavg1 and Cavgss) at 160 mg Q4W by ADA Status
Supplementary Figure S1 from Antibody–Drug Conjugate Sacituzumab Govitecan Enables a Sequential TOP1/PARP Inhibitor Therapy Strategy in Patients with Breast Cancer
Authors: Bardia Aditya , Sun Sheng , Thimmiah Nayana , Coates James T. , Wu Bogang , Abelman Rachel O. , Spring Laura , Moy Beverly , Ryan Phoebe , Melkonyan Mark N. , Partridge Ann , Juric Dejan , Peppercorn Jeffrey , Parsons Heather , Wander Seth A. , Attaya Victoria , Lormil Brenda , Shellock Maria , Nagayama Aiko , Bossuyt Veerle , Isakoff Steven J. , Tolaney Sara M. , Ellisen Leif W.
Published: July 2024

Figure S1. Schematic illustrating proposed temporal window created by SG-mediated drug delivery to enable sequential TOP1i/PARP1i dosing
Data from Biomarker Identification and Risk Prediction Model Development for Differentiated Thyroid Carcinoma Lung Metastasis Based on Primary Lesion Proteomics
Authors: Peng Xiaoqi , Zhao Hongbo , Ye Lijuan , Hou Fei , Yi Zihan , Ren Yanxin , Lu Lin , Chen Fukun , Lv Juan , Wang Yinghui , Cai Haolin , Zheng Xihua , Yang Qing , Chen Ting
Published: July 2024

AbstractPurpose:
The rising global high incidence of differentiated thyroid carcinoma (DTC) has led to a significant increase in patients presenting with lung metastasis of DTC (LMDTC). This population poses a significant challenge in clinical practice, necessitating the urgent development of effective risk stratification methods and predictive tools for lung metastasis.
Experimental Design:
Through proteomic analysis of large samples of primary lesion and dual validation employing parallel reaction monitoring and IHC, we identified eight hub proteins as potential biomarkers. By expanding the sample size and conducting statistical analysis on clinical features and hub protein expression, we constructed three risk prediction models.
Results:
This study identified eight hub proteins—SUCLG1/2, DLAT, IDH3B, ACSF2, ACO2, CYCS, and VDAC2—as potential biomarkers for predicting LMDTC risk. We developed and internally validated three risk prediction models incorporating both clinical characteristics and hub protein expression. Our findings demonstrated that the combined prediction model exhibited optimal predictive performance, with the highest discrimination (AUC: 0.986) and calibration (Brier score: 0.043). Application of the combined prediction model within a specific risk threshold (0–0.97) yielded maximal clinical benefit. Finally, we constructed a nomogram based on the combined prediction model.
Conclusions:
As a large sample size study in LMDTC research, the identification of biomarkers through primary lesion proteomics and the development of risk prediction models integrating clinical features and hub protein biomarkers offer valuable insights for predicting LMDTC and establishing personalized treatment strategies.
Data from Plasma Metabolic Profiles-Based Prediction of Induction Chemotherapy Efficacy in Nasopharyngeal Carcinoma: Results of a Bidirectional Clinical Trial
Authors: Tang Tingxi , Zhou Zhenhua , Chen Min , Li Nan , Sun Jianda , Chen Zekai , Xiao Ting , Wang Xiaoqing , Zhang Longshan , Wang Yingqiao , Zhang Hanbin , Zheng Xiuting , Chen Bei , Ye Feng , Guan Jian
Published: July 2024

AbstractPurpose:
The efficacy of induction chemotherapy (IC) as a primary treatment for advanced nasopharyngeal carcinoma (NPC) remains a topic of debate, with a lack of dependable biomarkers for predicting its efficacy. This study seeks to establish a predictive classifier using plasma metabolomics profiles.
Patients and Methods:
A total of 166 NPC patients enrolled in the clinical trial NCT05682703 who were undergoing IC were included in the study. Plasma lipoprotein profiles were obtained using 1H-nuclear magnetic resonance before and after IC treatment. An artificial intelligence-assisted radiomics method was developed to effectively evaluate its efficacy. Metabolic biomarkers were identified through a machine learning approach based on a discovery cohort and subsequently validated in a validation cohort that mimicked the most unfavorable real-world scenario.
Results:
Our research findings indicate that the effectiveness of IC varies among individual patients, with a correlation observed between efficacy and changes in metabolite profiles. Using machine learning techniques, it was determined that the extreme gradient boosting model exhibited notable efficacy, attaining an area under the curve (AUC) value of 0.792 (95% CI, 0.668–0.913). In the validation cohort, the model exhibited strong stability and generalizability, with an AUC of 0.786 (95% CI, 0.533–0.922).
Conclusions:
In this study, we found that dysregulation of plasma lipoprotein may result in resistance to IC in NPC patients. The prediction model constructed based on the plasma metabolites’ profile has good predictive capabilities and potential for real-world generalization. This discovery has implications for the development of treatment strategies and may offer insight into potential targets for enhancing the effectiveness of IC.
Data from Toripalimab Plus Bevacizumab as First-line Treatment for Advanced Hepatocellular Carcinoma: A Prospective, Multicenter, Single-Arm, Phase II Trial
Authors: Chen Yajin , Du Chengyou , Shen Shunli , Zhang Wu , Shan Yunfeng , Lyu Ang , Wu Jianhui , Shang Changzhen , Luo Xuan , Wei Jinxing , Xiao Heng , Qiu Jianguo , Hua Yunpeng , Wang Shutong , Wang Ting , Dai Shengjie , Zhang Shuhao , Xie Bingying , Wu Yinghao , Hao Chunyi
Published: July 2024

AbstractPurpose:
This phase II, multicenter, prospective, single-arm study aimed to evaluate the efficacy and safety of toripalimab plus bevacizumab for treating advanced hepatocellular carcinoma (HCC).
Patients and Methods:
Treatment-naïve patients with advanced HCC received toripalimab 240 mg plus bevacizumab 15 mg/kg every 3 weeks. The primary endpoints included safety and tolerability and objective response rate (ORR) assessed by the investigator per Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1.
Results:
Fifty-four patients were enrolled between April 17, 2020, and December 11, 2020. As assessed by the investigator according to RECIST v1.1, the ORR was 31.5% [95% confidence interval (CI), 19.5–45.6] and the lower bound of the 95% CI was above the prespecified boundary of 10%. The independent review committee (IRC) assessed ORR according to the modified RECIST (mRECIST), which was 46.3% (95% CI, 32.6–60.4). The median progression-free survival was 8.5 (95% CI, 5.5–11.0) and 9.8 months (95% CI, 5.6 to not evaluable) as assessed by the investigator according to RECIST v1.1 and IRC according to mRECIST criteria, respectively. The median overall survival (OS) was not reached, and the 12- and 24-month OS rates were 77.3% and 63.5%, respectively. Grade 3 or higher treatment-emergent adverse events (TEAEs) occurred in 27 patients (50.0%). The most common TEAEs were proteinuria (59.3%), hypertension (38.9%), increased aspartate aminotransferase (33.3%), increased amylase (29.6%), decreased platelet count (27.8%), and increased bilirubin levels (27.8%).
Conclusions:
Toripalimab plus bevacizumab showed a favorable efficacy and safety profile, supporting further studies on this combination regimen as a first-line treatment for advanced HCC.
Data from T-Cell Characteristics Impact Response and Resistance to T-Cell–Redirecting Bispecific Antibodies in Multiple Myeloma
Authors: Verkleij Christie P.M. , O’Neill Chloe A. , Broekmans Marloes E.C. , Frerichs Kristine A. , Bruins Wassilis S.C. , Duetz Carolien , Kruyswijk Sandy , Baglio Serena R. , Skerget Sheri , Montes de Oca Rocio , Zweegman Sonja , Verona Raluca I. , Mutis Tuna , van de Donk Niels W.C.J.
Published: July 2024

AbstractPurpose:
Bispecific antibodies (BsAb) directed against B-cell maturation antigen (teclistamab) or the orphan G protein-coupled receptor GPRC5D (talquetamab) induce deep and durable responses in heavily pretreated patients with multiple myeloma. However, mechanisms underlying primary and acquired resistance remain poorly understood.
Experimental Design:
The anti–multiple myeloma activity of teclistamab and talquetamab was evaluated in bone marrow (BM) samples from patients with multiple myeloma. T-cell phenotype and function were assessed in BM/peripheral blood samples obtained from patients with multiple myeloma who were treated with these BsAb.
Results:
In ex vivo killing assays with 41 BM samples from BsAb-naive patients with multiple myeloma, teclistamab- and talquetamab-mediated multiple myeloma lysis was strongly correlated (r = 0.73, P < 0.0001). Both BsAb exhibited poor activity in samples with high regulatory T-cell (Treg) numbers and a low T-cell/multiple myeloma cell ratio. Furthermore, comprehensive phenotyping of BM samples derived from patients treated with teclistamab or talquetamab revealed that high frequencies of PD-1+ CD4+ T cells, CTLA4+ CD4+ T cells, and CD38+ CD4+ T cells were associated with primary resistance. Although this lack of response was linked to a modest increase in the expression of inhibitory receptors, increasing T-cell/multiple myeloma cell ratios by adding extra T cells enhanced sensitivity to BsAb. Further, treatment with BsAb resulted in an increased proportion of T cells expressing exhaustion markers (PD-1, TIGIT, and TIM-3), which was accompanied by reduced T-cell proliferative potential and cytokine secretion, as well as impaired antitumor efficacy in ex vivo experiments.
Conclusions:
Primary resistance is characterized by a low T-cell/multiple myeloma cell ratio and Treg-driven immunosuppression, whereas reduced T-cell fitness due to continuous BsAb-mediated T-cell activation may contribute to the development of acquired resistance.
Data from Spatially Preserved Multi-Region Transcriptomic Subtyping and Biomarkers of Chemoimmunotherapy Outcome in Extensive-Stage Small Cell Lung Cancer
Authors: Peressini Melina , Garcia-Campelo Rosario , Massuti Bartomeu , Martí Cristina , Cobo Manuel , Gutiérrez Vanesa , Dómine Manuel , Fuentes José , Majem Margarita , de Castro Javier , Córdoba Juan F. , Diz María P. , Isla Dolores , Esteban Emilio , Carcereny Enric , Vila Laia , Moreno-Vega Alberto , Ros Silverio , Moreno Amaia , García Francisco J. , Huidobro Gerardo , Aguado Carlos , Cebey-López Victor , Valdivia Javier , Palmero Ramón , Lianes Pilar , López-Brea Marta , Vidal Oscar J. , Provencio Mariano , Arriola Edurne , Baena Javier , Herrera Mercedes , Bote Helena , Molero Magdalena , Adradas Vera , Ponce-Aix Santiago , Nuñez-Buiza Angel , Ucero Álvaro , Hernandez Susana , Lopez-Rios Fernando , Conde Esther , Paz-Ares Luis , Zugazagoitia Jon
Published: July 2024

AbstractPurpose:
Transcriptomic subtyping holds promise for personalized therapy in extensive-stage small cell lung cancer (ES-SCLC). In this study, we aimed to assess intratumoral transcriptomic subtype diversity and to identify biomarkers of long-term chemoimmunotherapy benefit in human ES-SCLC.
Experimental Design:
We analyzed tumor samples from 58 patients with ES-SCLC enrolled in two multicenter single-arm phase IIIb studies evaluating frontline chemoimmunotherapy in Spain: n = 32 from the IMfirst trial and n = 26 from the CANTABRICO trial. We used the GeoMx Digital Spatial Profiler system to perform multi-region transcriptomic analysis. For subtype classification, we performed hierarchical clustering using the relative expression of ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P), and YAP1 (SCLC-Y).
Results:
Subtype distribution was found to be similar between bothcohorts, except for SCLC-P, which was not identified in the CANTABRICO_DSP cohort. A total of 44% of the patients in both cohorts had tumors with multiple coexisting transcriptional subtypes. Transcriptional subtypes or subtype heterogeneity was not associated with outcomes. Most potential targets did not show subtype-specific expression. Consistently in both cohorts, tumors from patients with long-term benefit (time to progression ≥12 months) contained an IFNγ-dominated mRNA profile, including enhanced capacity for antigen presentation. Hypoxia and glycolytic pathways were associated with resistance to chemoimmunotherapy.
Conclusions:
This work suggests that intratumoral heterogeneity, inconsistent association with outcome, and unclear subtype-specific target expression might be significant challenges for subtype-based precision oncology in SCLC. Preexisting IFNγ-driven immunity and mitochondrial metabolism seem to be correlates of long-term efficacy in this study, although the absence of a chemotherapy control arm precludes concluding that these are predictive features specific for immunotherapy.
Figure 2 from Tumor-Immune Signatures of Treatment Resistance to Brentuximab Vedotin with Ipilimumab and/or Nivolumab in Hodgkin Lymphoma
Authors: Gonzalez-Kozlova Edgar , Huang Hsin-Hui , Jagede Opeyemi A. , Tuballes Kevin , Del Valle Diane M. , Kelly Geoffrey , Patel Manishkumar , Xie Hui , Harris Jocelyn , Argueta Kimberly , Nie Kai , Barcessat Vanessa , Moravec Radim , Altreuter Jennifer , Duose Dzifa Y. , Kahl Brad S. , Ansell Stephen M. , Yu Joyce , Cerami Ethan , Lindsay James R. , Wistuba Ignacio I. , Kim-Schulze Seunghee , Diefenbach Catherine S. , Gnjatic Sacha
Published: July 2024

Association of plasma cytokines with clinical benefit. A, C, and E, PFS survival analysis shows the Kaplan–Meier curves for VEGFR2, CXCL9, and MUC16, respectively. Statistics using log-rank test and Cox proportional hazard models are shown. Higher than median VEGFR2 levels were associated with slower progression whereas higher than median levels of CXCL9 and MUC16 were associated with faster progression. B, D, and F, Forest plots for VEGFR2, CXCL9, and MUC16, respectively. Here, we show the multivariate statistics for each of these proteins including sex, age, treatment type, and cancer stage (Ann Arbor stage). These figures verify the directionality of the KM curves shown and show that these three proteins are independent of these clinically relevant covariates. G, Shows the receiver operating characteristic (ROC) curves for the prediction of PFS using VEGFR2, MUC16, CXCL9, PDL1, and clinical variables. Ordered from most relevant to least relevant model, reflected on the AUC values. H, Univariate PFS Cox modeling of Olink analytes. I, Univariate OS Cox modeling of Olink analytes. Both I and H, show on the x-axis the HR and the y-axis shows the −log10 (P values) based on the log-rank test.
Figure 1 from Tumor-Immune Signatures of Treatment Resistance to Brentuximab Vedotin with Ipilimumab and/or Nivolumab in Hodgkin Lymphoma
Authors: Gonzalez-Kozlova Edgar , Huang Hsin-Hui , Jagede Opeyemi A. , Tuballes Kevin , Del Valle Diane M. , Kelly Geoffrey , Patel Manishkumar , Xie Hui , Harris Jocelyn , Argueta Kimberly , Nie Kai , Barcessat Vanessa , Moravec Radim , Altreuter Jennifer , Duose Dzifa Y. , Kahl Brad S. , Ansell Stephen M. , Yu Joyce , Cerami Ethan , Lindsay James R. , Wistuba Ignacio I. , Kim-Schulze Seunghee , Diefenbach Catherine S. , Gnjatic Sacha
Published: July 2024

Protein dynamics in HL during checkpoint blockade treatment. A, Overview of the clinical trial E4412 experimental design. Three treatment arms included: (i) BV + ipilimumab (I), (ii) BV + nivolumab (N), and (iii) BV + I + N, with participant number (n) indicated. B, Regression modeling strategy using mixed effect models applied to analyze independently four different assay methodologies. Each assay was modeled considering relevant clinical variables and adjusted for multiple testing using FDR correction. C, Summary heatmap showing the log2-fold change (log2FC) between time points and treatments. The changes with a positive log2FC over time in color blue are associated with a decrease over time and red with an increase over time. The −log10 (P value) is represented by the size of the circles, indicating statistical significance as the circles increase. D, Line and boxplot figures showing the changes in expression for markers increased posttreatment such as PDCD1, GMZA, PTN, CAIX, IL18, CD28, and markers decreased posttreatment such as CCL17, ANGPT2, IL13, and CXCL13. E, Summary heatmap of differential expression associated with response. The changes with a positive log2FC in color blue are associated with a lower expression in nonresponders and red with higher expression in nonresponders. F, Line and boxplot examples of significant (P < 0.05 & FDR < 0.05) proteins associated with response (blue) or nonresponse (red) over time.
Guidance device for visually impaired people based on ultrasonic signals and open hardware
Authors: Yauri Ricardo , Alvarez Kevin , Cotaquispe Junior , Ynquilla Jordy , Llerena Oscar
Published: July 2024

Visual impairment is a complex challenge that affects people of all ages, and it is estimated that around 2.2 billion people worldwide lack adequate access to medical treatment and support. In Latin America, there is a lack of attention to people with visual disabilities, evidenced by poor urban infrastructure and lack of compliance with inclusion laws. Some projects stand out for the use of prototypes with artificial vision technology, global positioning system (GPS) and smart canes. Therefore, the objective of the project is to use ultrasonic sensors and a low-cost electronic device coupled to canes, for obstacle detection and mobility using an open hardware embedded system. The results confirmed the efficiency in the detection and operation of the ultrasonic sensor by activating the light emitting diode (LED), the buzzer and the vibrating motor according to the programmed distances. Challenges were identified, such as adapting the sensor to the tilt of the cane and the importance of accurate calibration of the ultrasonic sensor. The system met its objectives by detecting objects in a range of 2 to 50 cm and providing sound alerts to improve the perception of blind people.
Adaptive tunicate swarm optimization with partial transmit sequence for phase optimization in MIMO-OFDM
Authors: Shaik Abdul Lateef Haroon Phulara , Madhavan Sowmya , Divakarachari Parameshachari Bidare , De Prado Rocío Pérez , Parameshwarappa Paramesh Siddappa , Gowda Kavitha Malali Vishveshwarappa
Published: July 2024

Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are widely utilized in wireless systems and maximum data rate communications. The MIMO-OFDM technology increases the efficiency of spectrum utilization. The peak-to-average-power ratio (PAPR) minimization in MIMO-OFDM is a complex task in wireless communications systems. In this research, an adaptive tunicate swarm optimization with partial transmit sequence (ATSO-PTS) algorithm is proposed for a reduction of PAPR in MIMO-OFDM. The nonsquare-matrix-based differential space time coding (N-DSTC) scheme is used for the encoding and decoding process of MIMO-OFDM. The N-DSTC encoding and decoding are linear error-correcting codes that are utilized for message transmission over noisy channels. The pre-specified quadrate phase shift keying (QPSK) symbol is deployed for the modulation and demodulation scheme. On the receiver side, the serial to parallel (S/P) conversion, and fast Fourier transform (FFT) are accomplished, alongside the received data bits being demodulated to obtain the output bits. The proposed ATSO-PTS method achieves better results according to performance metrices PAPR, bit error rate (BER) and signal-to-noise-ratio (SNR), with values of about 2.9, 0.01 and 0.025, respectively. This ensures superior results when compared to the existing methods of twin symbol hybrid optimization applied to partial transmit sequence (TSHO-PTS), selective level mapping and PTS (SLM-PTS), and particle swarm and grey wolf (PS-GW) with PTS, respectively.
Design of a linear motor-based magnetic levitation train prototype
Authors: Mohd Zaidi Muhammad Syafiq , Mohd Hassan Siti Lailatul , Abdul Halim Ili Shairah , Sulaiman Nasri
Published: July 2024

This study explores the modelling of a magnetic levitation train and its implementation using a microcontroller. Magnetic levitation (maglev) is a technology that enables vehicles to levitate and move without wheels. Maglev research has been conducted globally, but maglev trains haven't received much attention. Due to the sophisticated linear motor technology for contactless transit, building a maglev train requires enormous investments. This paper is crucial for understanding the linear motor technologies necessary for levitation and propulsion. The primary objectives of this study include creating a model of the maglev train using a linear motor circuit, investigating the maglev effect concerning different coil and magnet types, and monitoring the train's propulsion and levitation using a microcontroller. This work constructs a linear motor system for the maglev train, comprising a mechanical structure with a permanent magnet for levitation and electromagnets for propulsion. A microcontroller is employed to sense the magnetic field, produced by the permanent magnet and electromagnets. In summary, this paper successfully designed a maglev train prototype using a linear motor circuit to establish the repulsive mechanism for both levitation and propulsion, with levitation~1 cm from the track and demonstrated the ability to move along a 30 cm track.
Embedded systems as programmable square wave generator in wireless power transfer
Authors: Akbar Sabriansyah Rizqika , Setiawan Eko , Basuki Achmad
Published: July 2024

This study focuses on the design and development of programmable frequency generator using embedded devices that are able to produce square wave signals in the wireless power transfer (WPT) transmitter. We validate the accuracy of the output signal by measuring distance error. We validate that our system can change and sweep the frequency and produce high power by measuring the absorbed power in the load. We conduct the frequency sweep analysis to find optimal frequency and the frequency splitting phenomenon. The experiments show that the system can produce and sweep the square wave signals with less than 1% error. We also find that the frequency splitting occurred when distance among two coils in the range 0.5-6.5 cm and the splitting disappeared when the distance is above 7.5 cm. The frequency splitting shows that the measured optimum frequency differs from the calculation. The difference confirms that the programmable frequency generator is needed to adjust the frequency that can transfer maximum power to the load.
Air quality monitoring system based on low power wide area network technology at public transport stops
Authors: Yauri Ricardo , Loayza Bill , Yauri Alvaro , Aquino Anyela
Published: July 2024

Mass migration from rural areas to urban areas has caused problems of traffic congestion, high industrial concentration and inequity in the distribution of housing in the world's capitals, generating a significant threat to sustainable development and public health due to air pollution air. In the Peruvian context, the importance of real-time monitoring of air quality is highlighted according to the standards established by the government. Several studies propose real-time environmental monitoring systems using internet of thing (IoT) technologies, electrochemical and optical sensors to measure pollutants, highlighting the need for data analysis. The objective of the paper is to show the implementation of IoT devices called sensor nodes, with long range wide area network (LoRaWAN) transmission technology for continuous monitoring of polluting gas concentrations. In addition, they are integrated into a central node called gateway to perform real-time monitoring through a web application. As an initial result, IoT devices demonstrated their effectiveness for real-time monitoring. Despite being a prototype-level result, the next stage involves its deployment at public transport stops in Lima. Overcoming the limitations of the solution, this paper establishes the foundation for future research on pollution and public health.
Precision medicine in hepatology: harnessing IoT and machine learning for personalized liver disease stage prediction
Authors: Swain Satyaprakash , Mohanty Mihir Narayan , Pattanayak Binod Kumar
Published: July 2024

In this research, we used a dataset from Siksha ‘O’ Anusandhan (S’O’A) University Medical Laboratory containing 6,780 samples collected manually and through internet of things (IoT) sensor sources from 6,780 patients to perform a thorough investigation into liver disease stage prediction. The dataset was carefully cleaned before being sent to the machine learning pipeline. We utilised a range of machine learning models, such as Naïve Bayes (NB), sequential minimal optimisation (SMO), K-STAR, random forest (RF), and multi-class classification (MCC), using Python to predict the stages of liver disease. The results of our simulations demonstrated how well the SMO model performed in comparison to other models. We then expanded our analysis using different machine learning boosting models with SMO as the base model: adaptive boosting (AdaBoost), gradient boost, extreme gradient boosting (XGBoost), CatBoost, and light gradient boosting model (LightGBM). Surprisingly, gradient boost proved to be the most successful, producing an astounding 96% accuracy. A closer look at the data showed that when AdaBoost was combined with the SMO base model, the accuracy results were 94.10%, XGBoost 90%, CatBoost 92%, and LightGBM 94%. These results highlight the effectiveness of proposed model i.e. gradient boosting in improving the prediction of liver disease stage and provide insightful information for improving clinical decision support systems in the field of medical diagnostics.
Portable neonatus incubator based on global positioning system
Authors: Salahuddin Nur Sultan , Sari Sri Peornomo , Musyaffa Aqilla Rahman
Published: July 2024

The role of baby incubator is crucial in assisting premature babies to adjust to their new surroundings. However, the current baby incubator causes challenges when used for emergency first aid. The challenge is often because of its cumbersome size, which makes transportation to referral hospitals difficult. To address this issue, portable neonate incubator based on the global positioning system (GPS) was developed. The results of implementation testing showed that the incubator system effectively monitored longitude and latitude coordinates, as well as the temperature and humidity of the incubator room, and the body temperature of neonates. Weighing approximately 5.8 kg, this incubator was versatile, compatible with both AC and DC voltage power sources, and came equipped with a carrying bag for easy transportation by midwives or medical personnel. Consequently, this development marked an innovative advancement in neonate incubator medical equipment, facilitating the swift tracking of the neonate incubator's coordinate position in case of unexpected events on the way to the hospital.
Experiencias en la interacción de estudiantes y profesores universitarios durante la educación virtual en pandemia
Authors: Manrique-Tisnés Horacio , Ramírez-Castaño Juan Carlos
Published: July 2024

(analytical)The Covid-19 pandemic posed major challenges for students and professors in terms of online education.This study, which used a phenomenological-hermeneutic method, analyzed professor-studentinteractions that occurred as part of remote learning during this period. The collection techniques included semi-structured interviews and a focus group. A total of 29 people participated (professors and students from different universities, programs and academic levels). The researchers established three categories for these experiences: sensorial (vision and touch), cognitive (knowledge) and ethical (faces). Both students' and professors' experiences of space were affected by online education, as this concept was limited by their computer's peripheral devices and the inadequate learning environment. Consequently, this situation affected professor-student interactions. The results of the study aimed to answer questions about participants' experiences of professor-student interactions within online education during the pandemic.
Novel Metabolites Associated With Blood Pressure After Dietary Interventions
Authors: Sun Yixi , Zhang Ruiyuan , Tian Ling , Pan Yang , Sun Xiao , Huang Zhijie , Fan Jia , Chen Jing , Zhang Kai , Li Shengxu , Chen Wei , Bazzano Lydia A. , Kelly Tanika N. , He Jiang , Bundy Joshua D. , Li Changwei
Published: July 2024

BACKGROUND:

The blood pressure (BP) etiologic study is complex due to multifactorial influences, including genetic, environmental, lifestyle, and their intricate interplays. We used a metabolomics approach to capture internal pathways and external exposures and to study BP regulation mechanisms after well-controlled dietary interventions.

METHODS:

In the ProBP trail (Protein and Blood Pressure), a double-blinded crossover randomized controlled trial, participants underwent dietary interventions of carbohydrate, soy protein, and milk protein, receiving 40 g daily for 8 weeks, with 3-week washout periods. We measured plasma samples collected at baseline and at the end of each dietary intervention. Multivariate linear models were used to evaluate the association between metabolites and systolic/diastolic BP. Nominally significant metabolites were examined for enriching biological pathways. Significant ProBP findings were evaluated for replication among 1311 participants of the BHS (Bogalusa Heart Study), a population-based study conducted in the same area as ProBP.

RESULTS:

After Bonferroni correction for 77 independent metabolite clusters (α=6.49×10
−4
), 18 metabolites were significantly associated with BP at baseline or the end of a dietary intervention, of which 11 were replicated in BHS. Seven emerged as novel discoveries, which are as follows: 1-linoleoyl-GPE (18:2), 1-oleoyl-GPE (18:1), 1-stearoyl-2-linoleoyl-GPC (18:0/18:2), 1-palmitoyl-2-oleoyl-GPE (16:0/18:1), maltose, N-stearoyl-sphinganine (d18:0/18:0), and N6-carbamoylthreonyladenosine. Pathway enrichment analyses suggested dietary protein intervention might reduce BP through pathways related to G protein–coupled receptors, incretin function, selenium micronutrient network, and mitochondrial biogenesis.

CONCLUSIONS:

Seven novel metabolites were identified to be associated with BP at the end of different dietary interventions. The beneficial effects of protein interventions might be mediated through specific metabolic pathways.
A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth, and interactive QC with afni_proc.py and more
Authors: Taylor Paul A. , Glen Daniel R. , Chen Gang , Cox Robert W. , Hanayik Taylor , Rorden Chris , Nielson Dylan M. , Rajendra Justin K. , Reynolds Richard C.
Published: July 2024

Quality control (QC) assessment is a vital part of FMRI processing and analysis, and a typically underdiscussed aspect of reproducibility. This includes checking datasets at their very earliest stages (acquisition and conversion) through their processing steps (e.g., alignment and motion correction) to regression modeling (correct stimuli, no collinearity, valid fits, enough degrees of freedom, etc.) for each subject. There are a wide variety of features to verify throughout any single-subject processing pipeline, both quantitatively and qualitatively. We present several FMRI preprocessing QC features available in the AFNI toolbox, many of which are automatically generated by the pipeline-creation tool, afni_proc.py. These items include a modular HTML document that covers full single-subject processing from the raw data through statistical modeling, several review scripts in the results directory of processed data, and command line tools for identifying subjects with one or more quantitative properties across a group (such as triaging warnings, making exclusion criteria, or creating informational tables). The HTML itself contains several buttons that efficiently facilitate interactive investigations into the data, when deeper checks are needed beyond the systematic images. The pages are linkable, so that users can evaluate individual items across a group, for increased sensitivity to differences (e.g., in alignment or regression modeling images). Finally, the QC document contains rating buttons for each “QC block,” as well as comment fields for each, to facilitate both saving and sharing the evaluations. This increases the specificity of QC, as well as its shareability, as these files can be shared with others and potentially uploaded into repositories, promoting transparency and open science. We describe the features and applications of these QC tools for FMRI.
Agreement Switch in Verb-Echo Answers: Evidence for Distributed Ellipsis
Authors: Mendes Gesoel , Ruda Marta , Willer-Gold Jana , Ristić Bojana , Arsenijević Boban , Čordalija Nermina , Leko Nedžad , Malenica Frane , Marušič Franc Lanko , Masnikosa Irina , Milićev Tanja , Milićević Nataša , Mišmaš Petra , Mitić Ivana , Peti-Stantić Anita , Stanković Branimir , Tolić Matea , Tušek Jelena , Nevins Andrew
Published: July 2024

In this article, we claim that syntactic objects undergoing ellipsis can be targeted by both narrow syntactic and PF operations. We base this conclusion on experimental evidence from the interaction between single conjunct agreement and verb-echo answers in South Slavic, which we show to be derived via verb-stranding VP ellipsis. Adopting the view that Vocabulary Insertion replaces Q-variables on lexical heads (Halle 1991) and ellipsis is a syntactic operation which deletes Q-variables (Saab 2022), we demonstrate that constituents properly included in the ellipsis site can undergo Internal Merge in the narrow syntax, and can participate in PF processes from the derived position. The interaction between ellipsis, Internal Merge and Agree-Copy that accounts for these patterns of data follows naturally within the Distributed Ellipsis approach.
Nomenclatural and taxonomic notes on Mallomonas Perty (Chrysophyceae). I. Typification of Mallomonas denticulata Matvienko
Authors: KAPUSTIN DMITRY A. , KULIKOVSKIY MAXIM S.
Published: July 2024

Mallomonas denticulata was described by Matvienko in the 1940s, however the ultrastructure of its scales and bristles remained unknown, so the species was considered to be dubious. Mallomonas asmundiae (≡M. cratis var. asmundiae) is a rather rare and widely accepted species but this name is invalid. In this report we discuss the similarity in the scale and bristle morphology between these two species and designate lectotype and epitype for M. denticulata. An emended description is provided.
Contribution to Egypt’s Flora: new records from Nile Islands, South Valley, Egypt
Authors: SHEDED MOHAMED G. , AYED FATMA A.A. , RADWAN TAREK A.A. , AHMED DALIA A.
Published: July 2024

The rate at which people are introducing species to formerly uninhabited places shows no signs of slowing down. Wild plants can roam freely across international borders. From September 2021 to June 2023, 45 field excursions were made to Egypt’s southern Nile Islands in the Aswan Governorate to undertake vegetation surveys. Depending on the literature reviewed and herbaria consulted during this study, three plant taxa, as well as one additional genus (Macroptilium), found during these field excursions were not previously recorded in the Egyptian Flora. These new records are Acanthospermum hispidum (Asteraceae), Geranium carolinianum (Geraniaceae), and Macroptilium atropurpureum (Fabaceae). These plants are classed as noxious weeds that harm agriculture. A complete description, occurrence and distribuion maps, plant photos and illustrations are provided. This study underlines the importance of carrying out extensive and ongoing research on the flora of Aswan’s Nile Islands to have a better knowledge of flowering plant distribution patterns. In addition, it might be regarded as a great starting point for expanding floristic knowledge of this interesting territory and its surroundings.
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting
Authors: Orlova Elena , Liu Haokun , Rossellini Raphael , Cash Benjamin A. , Willett Rebecca
Published: July 2024

Producing high-quality forecasts of key climate variables, such as temperature and precipitation, on subseasonal time scales has long been a gap in operational forecasting. This study explores an application of machine learning (ML) models as postprocessing tools for subseasonal forecasting. Lagged numerical ensemble forecasts (i.e., an ensemble where the members have different initialization dates) and observational data, including relative humidity, pressure at sea level, and geopotential height, are incorporated into various ML methods to predict monthly average precipitation and 2-m temperature 2 weeks in advance for the continental United States. For regression, quantile regression, and tercile classification tasks, we consider using linear models, random forests, convolutional neural networks, and stacked models (a multimodel approach based on the prediction of the individual ML models). Unlike previous ML approaches that often use ensemble mean alone, we leverage information embedded in the ensemble forecasts to enhance prediction accuracy. Additionally, we investigate extreme event predictions that are crucial for planning and mitigation efforts. Considering ensemble members as a collection of spatial forecasts, we explore different approaches to using spatial information. Trade-offs between different approaches may be mitigated with model stacking. Our proposed models outperform standard baselines such as climatological forecasts and ensemble means. In addition, we investigate feature importance, trade-offs between using the full ensemble or only the ensemble mean, and different modes of accounting for spatial variability.

Significance Statement

Accurately forecasting temperature and precipitation on subseasonal time scales—2 weeks–2 months in advance—is extremely challenging. These forecasts would have immense value in agriculture, insurance, and economics. Our paper describes an application of machine learning techniques to improve forecasts of monthly average precipitation and 2-m temperature using lagged physics-based predictions and observational data 2 weeks in advance for the entire continental United States. For lagged ensembles, the proposed models outperform standard benchmarks such as historical averages and averages of physics-based predictions. Our findings suggest that utilizing the full set of physics-based predictions instead of the average enhances the accuracy of the final forecast.
The 2023 Atlantic Hurricane Season: An Above-Normal Season despite Strong El Niño Conditions
Authors: Klotzbach Philip J. , Jones Jhordanne J. , Wood Kimberly M. , Bell Michael M. , Blake Eric S. , Bowen Steven G. , Caron Louis-Philippe , Chavas Daniel R. , Collins Jennifer M. , Gibney Ethan J. , Schreck Carl J. , Truchelut Ryan E.
Published: July 2024

The 2023 Atlantic hurricane season was above normal, producing 20 named storms, 7 hurricanes, 3 major hurricanes, and seasonal accumulated cyclone energy that exceeded the 1991–2020 average. Hurricane Idalia was the most damaging hurricane of the year, making landfall as a Category 3 hurricane in Florida, resulting in eight direct fatalities and 3.6 billion U.S. dollars in damage. The above-normal 2023 hurricane season occurred during a strong El Niño event. El Niño events tend to be associated with increased vertical wind shear across the Caribbean and tropical Atlantic, yet vertical wind shear during the peak hurricane season months of August–October was well below normal. The primary driver of the above-normal season was likely record warm tropical Atlantic sea surface temperatures (SSTs), which effectively counteracted some of the canonical impacts of El Niño. The extremely warm tropical Atlantic and Caribbean were associated with weaker-than-normal trade winds driven by an anomalously weak subtropical ridge, resulting in a positive wind–evaporation–SST feedback. We tested atmospheric circulation sensitivity to SSTs in both the tropical and subtropical Pacific and the Atlantic using the atmospheric component of the Community Earth System Model, version 2.3. We found that the extremely warm Atlantic was the primary driver of the reduced vertical wind shear relative to other moderate/strong El Niño events. The concentrated warmth in the eastern tropical Pacific in August–October may have contributed to increased levels of vertical wind shear than if the warming had been more evenly spread across the eastern and central tropical Pacific.